This document summarizes a study on using electrical conductivity measurements to quantify the smectite and chlorite content in rock cores from Krafla, Iceland. The study finds that electrical conductivity, when normalized by formation factor and porosity, correlates strongly with smectite content as determined by cation exchange capacity measurements. Smectite has weaker molecular bondings than chlorite, allowing it to contribute more to electrical conductivity. Between 7-20% clay content corresponds to 5-18% chlorite in whole rock samples. The ability to measure smectite content electrically could help locate transitions between hydrothermal heat convection and conduction zones.
Water ice is thought to be trapped in large permanently shadowed regions in the Moon’s polar regions, due to their extremely
low temperatures. Here, we show that many unmapped cold traps exist on small spatial scales, substantially augmenting the
areas where ice may accumulate. Using theoretical models and data from the Lunar Reconnaissance Orbiter, we estimate the
contribution of shadows on scales from 1 km to 1 cm, the smallest distance over which we find cold-trapping to be effective for
water ice. Approximately 10–20% of the permanent cold-trap area for water is found to be contained in these micro cold traps,
which are the most numerous cold traps on the Moon. Consideration of all spatial scales therefore substantially increases the
number of cold traps over previous estimates, for a total area of ~40,000 km2, about 60% of which is in the south. A majority of
cold traps for water ice is found at latitudes > 80° because permanent shadows equatorward of 80° are typically too warm to
support ice accumulation. Our results suggest that water trapped at the lunar poles may be more widely distributed and accessible
as a resource for future missions than previously thought.
Molecular water detected on the sunlit Moon by SOFIASérgio Sacani
Widespread hydration was detected on the lunar surface
through observations of a characteristic absorption feature
at 3 µm by three independent spacecraft1–3
. Whether the
hydration is molecular water (H2O) or other hydroxyl (OH)
compounds is unknown and there are no established methods to distinguish the two using the 3 µm band4. However, a
fundamental vibration of molecular water produces a spectral
signature at 6 µm that is not shared by other hydroxyl compounds5
. Here, we present observations of the Moon at 6 µm
using the NASA/DLR Stratospheric Observatory for Infrared
Astronomy (SOFIA). Observations reveal a 6 µm emission
feature at high lunar latitudes due to the presence of molecular water on the lunar surface. On the basis of the strength
of the 6 µm band, we estimate abundances of about 100 to
400 µg g−1
H2O. We find that the distribution of water over the
small latitude range is a result of local geology and is probably
not a global phenomenon. Lastly, we suggest that a majority of
the water we detect must be stored within glasses or in voids
between grains sheltered from the harsh lunar environment,
allowing the water to remain on the lunar surface.
Pore scale dynamics and the interpretation of flow processes - Martin Blunt, Imperial College London, at UKCCSRC specialist meeting Flow and Transport for CO2 Storage, 29-30 October 2015
Modelling Fault Reactivation, Induced Seismicity, and Leakage During Underground CO2 Injection, Jonny Rutquvist - Geophysical Modelling for CO2 Storage, Leeds, 3 November 2015
Assessing Uncertainty of Time Lapse Seismic Response Due to Geomechanical Deformation, Doug Angus - Geophysical Modelling for CO2 Storage, Leeds, 3 November 2015
Passive seismic monitoring for CO2 storage sites - Anna Stork, University of Bristol at UKCCSRC specialist meeting Geophysical modelling for CO2 storage, monitoring and appraisal, 3 November 2015
Water ice is thought to be trapped in large permanently shadowed regions in the Moon’s polar regions, due to their extremely
low temperatures. Here, we show that many unmapped cold traps exist on small spatial scales, substantially augmenting the
areas where ice may accumulate. Using theoretical models and data from the Lunar Reconnaissance Orbiter, we estimate the
contribution of shadows on scales from 1 km to 1 cm, the smallest distance over which we find cold-trapping to be effective for
water ice. Approximately 10–20% of the permanent cold-trap area for water is found to be contained in these micro cold traps,
which are the most numerous cold traps on the Moon. Consideration of all spatial scales therefore substantially increases the
number of cold traps over previous estimates, for a total area of ~40,000 km2, about 60% of which is in the south. A majority of
cold traps for water ice is found at latitudes > 80° because permanent shadows equatorward of 80° are typically too warm to
support ice accumulation. Our results suggest that water trapped at the lunar poles may be more widely distributed and accessible
as a resource for future missions than previously thought.
Molecular water detected on the sunlit Moon by SOFIASérgio Sacani
Widespread hydration was detected on the lunar surface
through observations of a characteristic absorption feature
at 3 µm by three independent spacecraft1–3
. Whether the
hydration is molecular water (H2O) or other hydroxyl (OH)
compounds is unknown and there are no established methods to distinguish the two using the 3 µm band4. However, a
fundamental vibration of molecular water produces a spectral
signature at 6 µm that is not shared by other hydroxyl compounds5
. Here, we present observations of the Moon at 6 µm
using the NASA/DLR Stratospheric Observatory for Infrared
Astronomy (SOFIA). Observations reveal a 6 µm emission
feature at high lunar latitudes due to the presence of molecular water on the lunar surface. On the basis of the strength
of the 6 µm band, we estimate abundances of about 100 to
400 µg g−1
H2O. We find that the distribution of water over the
small latitude range is a result of local geology and is probably
not a global phenomenon. Lastly, we suggest that a majority of
the water we detect must be stored within glasses or in voids
between grains sheltered from the harsh lunar environment,
allowing the water to remain on the lunar surface.
Pore scale dynamics and the interpretation of flow processes - Martin Blunt, Imperial College London, at UKCCSRC specialist meeting Flow and Transport for CO2 Storage, 29-30 October 2015
Modelling Fault Reactivation, Induced Seismicity, and Leakage During Underground CO2 Injection, Jonny Rutquvist - Geophysical Modelling for CO2 Storage, Leeds, 3 November 2015
Assessing Uncertainty of Time Lapse Seismic Response Due to Geomechanical Deformation, Doug Angus - Geophysical Modelling for CO2 Storage, Leeds, 3 November 2015
Passive seismic monitoring for CO2 storage sites - Anna Stork, University of Bristol at UKCCSRC specialist meeting Geophysical modelling for CO2 storage, monitoring and appraisal, 3 November 2015
Advances in Rock Physics Modelling and Improved Estimation of CO2 Saturation, Giorgos Papageorgiou - Geophysical Modelling for CO2 Storage, Leeds, 3 November 2015
Droplet thermal behavior study with light scattering techniqueAnurak Atthasit
THE 10TH INTERNATIONAL SYMPOSIUM ON FLOW VISUALIZATION
August 26 - 29, 2002, Kyoto, Japan
To present the results obtained from a basic experiment on droplet interaction in a dense linear droplet stream. The interaction of individual droplet with one another and with surrounding influences their transport characteristics.
A vibrating orifice generator produces a stream of monosized droplets. The experiments have been performed by using the electrostatic deviator to obtain the evolution of the main droplet characteristics in a wide range of the spacing parameter value Co (ratio between droplet spacing to droplet diameter). The basic experiment allows quantifying precisely the evolution of the drag coefficient and the droplet evaporation rate for different droplet spacings.
Evidence for plumes of water on Europa has previously been found using the Hubble Space Telescope using two
different observing techniques. Roth et al. found line emission from the dissociation products of water. Sparks et al.
found evidence for off-limb continuum absorption as Europa transited Jupiter. Here, we present a new transit
observation of Europa that shows a second event at the same location as a previous plume candidate from Sparks
et al., raising the possibility of a consistently active source of erupting material on Europa. This conclusion is
bolstered by comparison with a nighttime thermal image from the Galileo Photopolarimeter-Radiometer that shows
a thermal anomaly at the same location, within the uncertainties. The anomaly has the highest observed brightness
temperature on the Europa nightside. If heat flow from a subsurface liquid water reservoir causes the thermal
anomaly, its depth is ≈1.8–2 km, under simple modeling assumptions, consistent with scenarios in which a liquid
water reservoir has formed within a thick ice shell. Models that favor thin regions within the ice shell that connect
directly to the ocean, however, cannot be excluded, nor modifications to surface thermal inertia by subsurface
activity. Alternatively, vapor deposition surrounding an active vent could increase the thermal inertia of the surface
and cause the thermal anomaly. This candidate plume region may offer a promising location for an initial
characterization of Europa’s internal water and ice and for seeking evidence of Europa’s habitability.
Cassini finds molecular hydrogen in the Enceladus plume: Evidence for hydroth...Sérgio Sacani
Saturn’s moon Enceladus has an ice-covered ocean; a plume of material erupts from
cracks in the ice. The plume contains chemical signatures of water-rock interaction
between the ocean and a rocky core.We used the Ion Neutral Mass Spectrometer onboard
the Cassini spacecraft to detect molecular hydrogen in the plume. By using the instrument’s
open-source mode, background processes of hydrogen production in the instrument were
minimized and quantified, enabling the identification of a statistically significant signal of
hydrogen native to Enceladus.We find that the most plausible source of this hydrogen is
ongoing hydrothermal reactions of rock containing reduced minerals and organic materials.
The relatively high hydrogen abundance in the plume signals thermodynamic disequilibrium
that favors the formation of methane from CO2 in Enceladus’ ocean.
Glover P.W.J, Petrophysics Msc Courses Notes. The Potential Spontaneous. The spontaneous potential log (SP) measures the natural or spontaneous potential difference
(sometimes called self-potential) that exists between the borehole and the surface in the absence of any
artificially applied current
A New Approximation of Water Saturation Estimation Based on Vertical Seismic ...IJERA Editor
Water saturation is the ratio between the volumes of fluid in the rock pores. Water saturation is one of the
important reservoir parameters to be known in the exploration or exploitation of oil and gas. I have developed a
new technique to estimate the distribution of water saturation values based on the seismic wave attenuation
analysis, frequency and porosity from the equation of Biot-Turgut-Yamamoto-Sismanto. It is applied to the real
data using the vertical seismic profiling (VSP) data in Pasir Cantang well, West Java for some layers.
The obtained values of water saturation have not been calibrated to the known value of the well. This step needs
to be done, so that the results that have been corrected can be performed to estimate the area around the well
Pasir Cantang guided by seismic section. Regardless of the calibration factor, the method of the water saturation
estimation on VSP data can technically be well done but still needs necessary calibration for the accuracy.
Class notes of Geotechnical Engineering course I used to teach at UET Lahore. Feel free to download the slide show.
Anyone looking to modify these files and use them for their own teaching purposes can contact me directly to get hold of editable version.
Advances in Rock Physics Modelling and Improved Estimation of CO2 Saturation, Giorgos Papageorgiou - Geophysical Modelling for CO2 Storage, Leeds, 3 November 2015
Droplet thermal behavior study with light scattering techniqueAnurak Atthasit
THE 10TH INTERNATIONAL SYMPOSIUM ON FLOW VISUALIZATION
August 26 - 29, 2002, Kyoto, Japan
To present the results obtained from a basic experiment on droplet interaction in a dense linear droplet stream. The interaction of individual droplet with one another and with surrounding influences their transport characteristics.
A vibrating orifice generator produces a stream of monosized droplets. The experiments have been performed by using the electrostatic deviator to obtain the evolution of the main droplet characteristics in a wide range of the spacing parameter value Co (ratio between droplet spacing to droplet diameter). The basic experiment allows quantifying precisely the evolution of the drag coefficient and the droplet evaporation rate for different droplet spacings.
Evidence for plumes of water on Europa has previously been found using the Hubble Space Telescope using two
different observing techniques. Roth et al. found line emission from the dissociation products of water. Sparks et al.
found evidence for off-limb continuum absorption as Europa transited Jupiter. Here, we present a new transit
observation of Europa that shows a second event at the same location as a previous plume candidate from Sparks
et al., raising the possibility of a consistently active source of erupting material on Europa. This conclusion is
bolstered by comparison with a nighttime thermal image from the Galileo Photopolarimeter-Radiometer that shows
a thermal anomaly at the same location, within the uncertainties. The anomaly has the highest observed brightness
temperature on the Europa nightside. If heat flow from a subsurface liquid water reservoir causes the thermal
anomaly, its depth is ≈1.8–2 km, under simple modeling assumptions, consistent with scenarios in which a liquid
water reservoir has formed within a thick ice shell. Models that favor thin regions within the ice shell that connect
directly to the ocean, however, cannot be excluded, nor modifications to surface thermal inertia by subsurface
activity. Alternatively, vapor deposition surrounding an active vent could increase the thermal inertia of the surface
and cause the thermal anomaly. This candidate plume region may offer a promising location for an initial
characterization of Europa’s internal water and ice and for seeking evidence of Europa’s habitability.
Cassini finds molecular hydrogen in the Enceladus plume: Evidence for hydroth...Sérgio Sacani
Saturn’s moon Enceladus has an ice-covered ocean; a plume of material erupts from
cracks in the ice. The plume contains chemical signatures of water-rock interaction
between the ocean and a rocky core.We used the Ion Neutral Mass Spectrometer onboard
the Cassini spacecraft to detect molecular hydrogen in the plume. By using the instrument’s
open-source mode, background processes of hydrogen production in the instrument were
minimized and quantified, enabling the identification of a statistically significant signal of
hydrogen native to Enceladus.We find that the most plausible source of this hydrogen is
ongoing hydrothermal reactions of rock containing reduced minerals and organic materials.
The relatively high hydrogen abundance in the plume signals thermodynamic disequilibrium
that favors the formation of methane from CO2 in Enceladus’ ocean.
Glover P.W.J, Petrophysics Msc Courses Notes. The Potential Spontaneous. The spontaneous potential log (SP) measures the natural or spontaneous potential difference
(sometimes called self-potential) that exists between the borehole and the surface in the absence of any
artificially applied current
A New Approximation of Water Saturation Estimation Based on Vertical Seismic ...IJERA Editor
Water saturation is the ratio between the volumes of fluid in the rock pores. Water saturation is one of the
important reservoir parameters to be known in the exploration or exploitation of oil and gas. I have developed a
new technique to estimate the distribution of water saturation values based on the seismic wave attenuation
analysis, frequency and porosity from the equation of Biot-Turgut-Yamamoto-Sismanto. It is applied to the real
data using the vertical seismic profiling (VSP) data in Pasir Cantang well, West Java for some layers.
The obtained values of water saturation have not been calibrated to the known value of the well. This step needs
to be done, so that the results that have been corrected can be performed to estimate the area around the well
Pasir Cantang guided by seismic section. Regardless of the calibration factor, the method of the water saturation
estimation on VSP data can technically be well done but still needs necessary calibration for the accuracy.
Class notes of Geotechnical Engineering course I used to teach at UET Lahore. Feel free to download the slide show.
Anyone looking to modify these files and use them for their own teaching purposes can contact me directly to get hold of editable version.
Keynote presentation at GEORG Geothermal Workshop, Nov. 24, 2016ThinkGeoEnergy
This is a keynote presentation, I gave at the GEORG Geothermal Workshop in Reykjavik/ Iceland on November 24, 2016. It was held as part of my role as President of the International Geothermal Association with data from my activities at ThinkGeoEnergy.
Removal of 137Cs from contaminated soil using pilot electrokinetic decontamin...Agriculture Journal IJOEAR
—The removal efficiencies of 137Cs for 10 days were 50-70%. The removal efficiencies according to the elapsed time after 10 days were reduced. When an electric current density of 25-75 mA/cm2, sulfuric acid, nitric acid, acetic acid as electrolyte, a 0.5-2.0 cm/min hydraulic conductivity of soil were applied, respectively, the time required for the removal efficiency of 137Cs to reach 80% was 20-30 days. For improving removal efficiency of 137Cs from contaminated soil, it is necessary to increase an electric current density using sulfuric acid as an electrolyte and to decrease hydraulic conductivity of soil in the soil cell.
Magnetic Gold; Structure Dependent Ferromagnetism in Au4VDamon Jackson
A description of the ferromagnetic interactions found in crystallographic Au4V is investigated through high pressure (P<35 GPa) electrical resistivity measurements. The results suggest an intimate connection between crystallographic structure and ferromagnetism for this material.
Dielectric Constant Measurement on Calcium and Lanthanum Doped Triglycine Sul...IOSR Journals
Triglycine Sulphate (TGS) salts were synthesized. Calcium and lanthanum doped TGS crystals were grown from aqueous solutions by slow evaporation technique. The dielectric constant and AC conductivity measurement were carried out at various temperature ranging from 30°C to 120°C at different frequencies, the variation of dielectric constant with temperature and frequency were studied and it is found that the dielectric constant values decreases with increase in frequency and the AC conductivity increases with increase in frequency.
So far only a limited number of publications have been
concerned with the study of the mixed alkali effect in
glasses with the former TeO2. To our knowledge all were
focused on Li2O–Na2O–TeO2 glasses. The importance
of studying such a phenomenon in TeO2 glasses is due to
many industrial and technological applications concerning
this type. In the present work five different glass samples
of the system (20-x)K2O.xNa2O.80TeO2 were
selected for the present study, here x=0, 5, 10, 15 and 20
mol%. Bulk density and infrared absorption spectroscopy
were measured at room temperature. Quantitative
evaluation of the infrared absorption spectra showed that
the molecular groups were affected by changing the type
of the nearest neighbour alkali species. AC and dc isothermal
electrical conductivity were measured in the temperature
range 300–600 K and in the frequency range
0–100 kHz. Electrical parameters such as dielectric constant,
loss factor and conductivity were extracted from
these experiments and show mixed alkali effect. The glass
transition temperature was obtained from DTA as well
as from the dc electrical conductivity with a minimum
at Tg=485 K for x=10 mol%. The present results were
discussed in the light of ionic diffusion and interchange
transport mechanism of conduction along with structure
in TeO2 based glasses.
GEORG Geothermal Workshop 2016
Presentation Title: Hydrogen Sulfide concentration in the vicinity of the Reykjavik Capital area due to two Geothermal Power Plants
GEORG Geothermal Workshop 2016
Presentation Title: Willingness to pay for the preservation of geothermal areas in Iceland – the contingent valuation studies of Eldvörp and Hverahl
GEORG Geothermal Workshop 2016
Presentation Title: Volcano-tectonostratigraphic characteristics of the Jan Mayen microcontinent and Iceland shelf area, lessons learned for geothermal exploration
Democratizing Fuzzing at Scale by Abhishek Aryaabh.arya
Presented at NUS: Fuzzing and Software Security Summer School 2024
This keynote talks about the democratization of fuzzing at scale, highlighting the collaboration between open source communities, academia, and industry to advance the field of fuzzing. It delves into the history of fuzzing, the development of scalable fuzzing platforms, and the empowerment of community-driven research. The talk will further discuss recent advancements leveraging AI/ML and offer insights into the future evolution of the fuzzing landscape.
Cosmetic shop management system project report.pdfKamal Acharya
Buying new cosmetic products is difficult. It can even be scary for those who have sensitive skin and are prone to skin trouble. The information needed to alleviate this problem is on the back of each product, but it's thought to interpret those ingredient lists unless you have a background in chemistry.
Instead of buying and hoping for the best, we can use data science to help us predict which products may be good fits for us. It includes various function programs to do the above mentioned tasks.
Data file handling has been effectively used in the program.
The automated cosmetic shop management system should deal with the automation of general workflow and administration process of the shop. The main processes of the system focus on customer's request where the system is able to search the most appropriate products and deliver it to the customers. It should help the employees to quickly identify the list of cosmetic product that have reached the minimum quantity and also keep a track of expired date for each cosmetic product. It should help the employees to find the rack number in which the product is placed.It is also Faster and more efficient way.
Event Management System Vb Net Project Report.pdfKamal Acharya
In present era, the scopes of information technology growing with a very fast .We do not see any are untouched from this industry. The scope of information technology has become wider includes: Business and industry. Household Business, Communication, Education, Entertainment, Science, Medicine, Engineering, Distance Learning, Weather Forecasting. Carrier Searching and so on.
My project named “Event Management System” is software that store and maintained all events coordinated in college. It also helpful to print related reports. My project will help to record the events coordinated by faculties with their Name, Event subject, date & details in an efficient & effective ways.
In my system we have to make a system by which a user can record all events coordinated by a particular faculty. In our proposed system some more featured are added which differs it from the existing system such as security.
Welcome to WIPAC Monthly the magazine brought to you by the LinkedIn Group Water Industry Process Automation & Control.
In this month's edition, along with this month's industry news to celebrate the 13 years since the group was created we have articles including
A case study of the used of Advanced Process Control at the Wastewater Treatment works at Lleida in Spain
A look back on an article on smart wastewater networks in order to see how the industry has measured up in the interim around the adoption of Digital Transformation in the Water Industry.
CFD Simulation of By-pass Flow in a HRSG module by R&R Consult.pptxR&R Consult
CFD analysis is incredibly effective at solving mysteries and improving the performance of complex systems!
Here's a great example: At a large natural gas-fired power plant, where they use waste heat to generate steam and energy, they were puzzled that their boiler wasn't producing as much steam as expected.
R&R and Tetra Engineering Group Inc. were asked to solve the issue with reduced steam production.
An inspection had shown that a significant amount of hot flue gas was bypassing the boiler tubes, where the heat was supposed to be transferred.
R&R Consult conducted a CFD analysis, which revealed that 6.3% of the flue gas was bypassing the boiler tubes without transferring heat. The analysis also showed that the flue gas was instead being directed along the sides of the boiler and between the modules that were supposed to capture the heat. This was the cause of the reduced performance.
Based on our results, Tetra Engineering installed covering plates to reduce the bypass flow. This improved the boiler's performance and increased electricity production.
It is always satisfying when we can help solve complex challenges like this. Do your systems also need a check-up or optimization? Give us a call!
Work done in cooperation with James Malloy and David Moelling from Tetra Engineering.
More examples of our work https://www.r-r-consult.dk/en/cases-en/
Final project report on grocery store management system..pdfKamal Acharya
In today’s fast-changing business environment, it’s extremely important to be able to respond to client needs in the most effective and timely manner. If your customers wish to see your business online and have instant access to your products or services.
Online Grocery Store is an e-commerce website, which retails various grocery products. This project allows viewing various products available enables registered users to purchase desired products instantly using Paytm, UPI payment processor (Instant Pay) and also can place order by using Cash on Delivery (Pay Later) option. This project provides an easy access to Administrators and Managers to view orders placed using Pay Later and Instant Pay options.
In order to develop an e-commerce website, a number of Technologies must be studied and understood. These include multi-tiered architecture, server and client-side scripting techniques, implementation technologies, programming language (such as PHP, HTML, CSS, JavaScript) and MySQL relational databases. This is a project with the objective to develop a basic website where a consumer is provided with a shopping cart website and also to know about the technologies used to develop such a website.
This document will discuss each of the underlying technologies to create and implement an e- commerce website.
Explore the innovative world of trenchless pipe repair with our comprehensive guide, "The Benefits and Techniques of Trenchless Pipe Repair." This document delves into the modern methods of repairing underground pipes without the need for extensive excavation, highlighting the numerous advantages and the latest techniques used in the industry.
Learn about the cost savings, reduced environmental impact, and minimal disruption associated with trenchless technology. Discover detailed explanations of popular techniques such as pipe bursting, cured-in-place pipe (CIPP) lining, and directional drilling. Understand how these methods can be applied to various types of infrastructure, from residential plumbing to large-scale municipal systems.
Ideal for homeowners, contractors, engineers, and anyone interested in modern plumbing solutions, this guide provides valuable insights into why trenchless pipe repair is becoming the preferred choice for pipe rehabilitation. Stay informed about the latest advancements and best practices in the field.
COLLEGE BUS MANAGEMENT SYSTEM PROJECT REPORT.pdfKamal Acharya
The College Bus Management system is completely developed by Visual Basic .NET Version. The application is connect with most secured database language MS SQL Server. The application is develop by using best combination of front-end and back-end languages. The application is totally design like flat user interface. This flat user interface is more attractive user interface in 2017. The application is gives more important to the system functionality. The application is to manage the student’s details, driver’s details, bus details, bus route details, bus fees details and more. The application has only one unit for admin. The admin can manage the entire application. The admin can login into the application by using username and password of the admin. The application is develop for big and small colleges. It is more user friendly for non-computer person. Even they can easily learn how to manage the application within hours. The application is more secure by the admin. The system will give an effective output for the VB.Net and SQL Server given as input to the system. The compiled java program given as input to the system, after scanning the program will generate different reports. The application generates the report for users. The admin can view and download the report of the data. The application deliver the excel format reports. Because, excel formatted reports is very easy to understand the income and expense of the college bus. This application is mainly develop for windows operating system users. In 2017, 73% of people enterprises are using windows operating system. So the application will easily install for all the windows operating system users. The application-developed size is very low. The application consumes very low space in disk. Therefore, the user can allocate very minimum local disk space for this application.
Sachpazis:Terzaghi Bearing Capacity Estimation in simple terms with Calculati...Dr.Costas Sachpazis
Terzaghi's soil bearing capacity theory, developed by Karl Terzaghi, is a fundamental principle in geotechnical engineering used to determine the bearing capacity of shallow foundations. This theory provides a method to calculate the ultimate bearing capacity of soil, which is the maximum load per unit area that the soil can support without undergoing shear failure. The Calculation HTML Code included.
Hybrid optimization of pumped hydro system and solar- Engr. Abdul-Azeez.pdffxintegritypublishin
Advancements in technology unveil a myriad of electrical and electronic breakthroughs geared towards efficiently harnessing limited resources to meet human energy demands. The optimization of hybrid solar PV panels and pumped hydro energy supply systems plays a pivotal role in utilizing natural resources effectively. This initiative not only benefits humanity but also fosters environmental sustainability. The study investigated the design optimization of these hybrid systems, focusing on understanding solar radiation patterns, identifying geographical influences on solar radiation, formulating a mathematical model for system optimization, and determining the optimal configuration of PV panels and pumped hydro storage. Through a comparative analysis approach and eight weeks of data collection, the study addressed key research questions related to solar radiation patterns and optimal system design. The findings highlighted regions with heightened solar radiation levels, showcasing substantial potential for power generation and emphasizing the system's efficiency. Optimizing system design significantly boosted power generation, promoted renewable energy utilization, and enhanced energy storage capacity. The study underscored the benefits of optimizing hybrid solar PV panels and pumped hydro energy supply systems for sustainable energy usage. Optimizing the design of solar PV panels and pumped hydro energy supply systems as examined across diverse climatic conditions in a developing country, not only enhances power generation but also improves the integration of renewable energy sources and boosts energy storage capacities, particularly beneficial for less economically prosperous regions. Additionally, the study provides valuable insights for advancing energy research in economically viable areas. Recommendations included conducting site-specific assessments, utilizing advanced modeling tools, implementing regular maintenance protocols, and enhancing communication among system components.
Saudi Arabia stands as a titan in the global energy landscape, renowned for its abundant oil and gas resources. It's the largest exporter of petroleum and holds some of the world's most significant reserves. Let's delve into the top 10 oil and gas projects shaping Saudi Arabia's energy future in 2024.
Courier management system project report.pdfKamal Acharya
It is now-a-days very important for the people to send or receive articles like imported furniture, electronic items, gifts, business goods and the like. People depend vastly on different transport systems which mostly use the manual way of receiving and delivering the articles. There is no way to track the articles till they are received and there is no way to let the customer know what happened in transit, once he booked some articles. In such a situation, we need a system which completely computerizes the cargo activities including time to time tracking of the articles sent. This need is fulfilled by Courier Management System software which is online software for the cargo management people that enables them to receive the goods from a source and send them to a required destination and track their status from time to time.
A3 Léa Lévy Electrical conduction of low-salinity hydrothermal systems: a quantitative measure of the smectite and chlorite content
1. ELECTRICAL CONDUCTION: A QUANTITATIVE MEASURE OF
THE SMECTITE AND CHLORITE CONTENT?
STUDY BASED ON CORES FROM KRAFLA
24.11.2016 Léa Lévy - GEORG conference 1
LÉA LÉVY
IN COLLABORATION WITH:
ÓLAFUR G. FLÓVENZ
GYLFI PÁLL HERSIR
FREYSTEINN SIGMUNDSSON
BENOIT GIBERT
AND MANY MORE
2. What is clay?
• CEC = Cation Exchange Capacity
• Between T sheets „Internal exchange“
• Only in smectite
• On the edges „External exchange“
• Minimal compared to internal
• Unit = meq/100g or C/kg
• Measured by chemical titration
24.11.2016 Léa Lévy - GEORG conference 2
Chlorite
Illite
Smectite
• Phyllosilicates
• T = tetrahedral sheet (Si)
• O = octahedral sheet (Al or Mg)
• Sequences T-O-T
• Substitutions Negative charge
• Compensation between sheets
From multiple sources. Ex: Lyklema, 2001
3. Charge and mobility
24.11.2016 Léa Lévy - GEORG conference 3
Internal CEC (meq/100g)
100
Smectites Illite Chlorite
# water layers
0
1
2
|Total charge|0 0.70.50.3 10.9 2
T-O
No charge
T-O-T
low charge
T-O-T
high charge
higher charge stronger bondings structure more stable
Stability
Brucitic
layer
Cation with 2 water shellsNothing Cations with 1 water shell Cations with 0 water shell
Weak Coulombian attraction Van der Waals bondings of increasing strength H bondings
Montmorillonite
2 water shells
From Meunier, 2000
Beidellite
1 water shell
4. The smectite chlorite transition
• Kinetic vs thermodynamics
• Intermediary step
• Hydrothermal convection vs heat
conduction
• Presence/absence of smectite
24.11.2016 Léa Lévy - GEORG conference 4
„Smectite is a kinetic step in the formation of chlorite by hydrothermal convection.“
Electrical
conduction
Unstable
smectite
Weak
bondings
Low
charge
5. Context of the study
24.11.2016 Léa Lévy - GEORG conference 5
(b)
KH-5 (a) 288m – Epidote, quartz, wairakite. (b) 279 m –
Epidote overprinted by laumontite.
(c) (d)
KH6. 594 m – Zeolite transforming into wairakite.
(b)
KH-3 – 273 m. Precipitation of MLC
and chlorite in vesicles.
KH-1. 74 m – Stilbite and smectite.
Map by Þorbergsson and Víkingsson, 2016
6. Clay content and CEC
24.11.2016 Léa Lévy - GEORG conference 6
0
5
10
15
20
25
30
35
40
45
50
0% 10% 20% 30% 40% 50%
CECmeq/100g
Clay fraction (XRD)
CEC and clay fraction of whole rock samples
Based on XRD {d(001) + d(002)}
7. Clay content and CEC
24.11.2016 Léa Lévy - GEORG conference 7
y = 109.55x
R² = 0.9669
y = 85.673x
R² = 0.9959
0
5
10
15
20
25
30
35
40
45
50
0% 10% 20% 30% 40% 50%
CECmeq/100g
Clay fraction (XRD)
CEC and clay fraction of whole rock samples
Based on XRD {d(001) + d(002)}
100% smectite
75% smectite
𝐶𝐸𝐶0 = 110 meq/100g
8. Clay content and CEC
24.11.2016 Léa Lévy - GEORG conference 8
y = 109.55x
R² = 0.9669
y = 85.673x
R² = 0.9959
y = 67.361x
R² = 0.9863
0
5
10
15
20
25
30
35
40
45
50
0% 10% 20% 30% 40% 50%
CECmeq/100g
Clay fraction (XRD)
CEC and clay fraction of whole rock samples
Based on XRD {d(001) + d(002)}
100% smectite
75% smectite
60% smectite
𝐶𝐸𝐶0 = 110 meq/100g
9. Clay content and CEC
24.11.2016 Léa Lévy - GEORG conference 9
y = 109.55x
R² = 0.9669
y = 85.673x
R² = 0.9959
y = 67.361x
R² = 0.9863
y = 41.798x
R² = 0.9567
y = 22.927x
R² = 0.9509
0
5
10
15
20
25
30
35
40
45
50
0% 10% 20% 30% 40% 50%
CECmeq/100g
Clay fraction (XRD)
CEC and clay fraction of whole rock samples
Based on XRD {d(001) + d(002)}
100% smectite
75% smectite
60% smectite
40% smectite
20% smectite
𝐶𝐸𝐶0 = 110 meq/100g
10. Clay content and CEC
24.11.2016 Léa Lévy - GEORG conference 10
y = 109.55x
R² = 0.9669
y = 85.673x
R² = 0.9959
y = 67.361x
R² = 0.9863
y = 41.798x
R² = 0.9567
y = 22.927x
R² = 0.9509
y = 11.465x
R² = 0.6641
0
5
10
15
20
25
30
35
40
45
50
0% 10% 20% 30% 40% 50%
CECmeq/100g
Clay fraction (XRD)
CEC and clay fraction of whole rock samples
Based on XRD {d(001) + d(002)}
100% smectite
75% smectite
60% smectite
40% smectite
20% smectite
10% smectite
𝐶𝐸𝐶0 = 110 meq/100g
11. Conductivity and CEC
24.11.2016 Léa Lévy - GEORG conference 11
𝜎 𝑏𝑢𝑙𝑘 =
𝜎 𝑤
𝐹
+ 𝜎𝑠
y = 3.75x-1.89
R² = 0.76
10
100
1,000
1% 10% 100%
Formationfactor
Porosity
Formation factor and porosity
1.E-03
1.E-02
1.E-01
1.E+00
0.01 0.1 1 10
Bulkconductivity(S/m)
Fluid conductivity (S/m)
Bulk conductivity vs fluid conductivity
𝑚 = 1.89
1/F
𝜎𝑠
R² = 0.888
R² = 0.637
1.E-04
1.E-03
1.E-02
1.E-01
1.E+00
0 1 10 100
Conductivity(S/m)
CEC (meq/100g)
Interface conductivity vs CEC
Cs*F*Por
Cs
m Rock type Published in
1.33 Seafloor MAR Pezard, 1990
1.74-2.43 Shaly sands Waxman & Smits, 1968
2.45 Hawaiian basalt Revil et al., 2016
2.75 Icelandic basalt Flóvenz et al., 2005
Fluid
conductivity
Formation
factor
Clay „Interface“
conductivity
𝜎𝑠 = f(CEC, F, ∅)
𝐹 = a∅−𝑚
Porosity
(Waxman & Smits, 1968)
(Archie, 1942)
Contribution of clay
Small
Moderate
High
12. Conductivity and smectite
24.11.2016 Léa Lévy - GEORG conference 12
𝜎𝑠 ∗ F ∗ ∅ = f CEC = f(smec%)
1.E-03
1.E-02
1.E-01
1.E+00
1% 10% 100%
Clay fraction in the whole rock (XRD)
Normalized interface conductivity vs clay%
Clay >50% smectite
Clay 20-50% smectite
Clay < 20% smectite
Whole rock < 2% smectite
Between 7 and 20% of clay
5 to 18% chlorite in whole rock
R² = 0.912
1.E-03
1.E-02
1.E-01
1.E+00
0% 1% 10% 100%
Conductivity(S/m)
Smectite fraction in the whole rock (CEC)
Normalized interface conductivity vs smectite%
Meaningful smectite content (> 1 %)
Clay < 20% smectite
𝑤𝑡%(𝑠𝑚𝑒𝑐) =
𝐶𝐸𝐶
𝐶𝐸𝐶0
𝜎𝑏𝑢𝑙𝑘 =
𝜎 𝑤
𝐹
+ 𝜎𝑠
𝜎𝑠 = f(CEC, F, ∅)
𝐶𝐸𝐶0 = 110 meq/100g
13. Conclusions
• Electrical conductivity measures the smectite content
• At low-salinity
• Normalized by F*φ
• Independent of chlorite content
• Weak bondings in smectite are a key in geothermal exploration
• Smectite content is a measure of hydrothermal activity (unstability)
• Smectite content can be measured by electrical conduction (CEC)
Could we use the evolution of the smectite
content to locate the transition between heat
convection and heat conduction?
24.11.2016 Léa Lévy - GEORG conference 13
14. Thank you !
OTHER SCIENTISTS I WOULD LIKE TO ACKNOWLEDGE INCLUDE
PHILIPPE PEZARD
PIERRE BRIOLE
SIGURÐUR SVEINN JÓNSSON
ÞRÁINN FRIÐRIKSSON
HELGA M. HELGADÓTTIR
HJALTI FRANZSON
ANDRÉ REVIL
ALAIN MEUNIER
PHILIPPE COSENZA
24.11.2016 Léa Lévy - GEORG conference 14
17. Comparison between
borehole conductivity (from
the 64'' resistivity log) and
CEC from cuttings in
borehole KJ-18
Conductivity and CEC in borehole KJ-18
CEC (cuttings) and conductivity (borehole log)
24.11.2016 Léa Lévy - GEORG conference 17
18. Thermodynamics of cation exchange
0
5
10
15
20
25
30
35
40
0 100 200 300 400 500 600 700 800
CECapparent(meq/100g)
mass of rock / initial concentration in mg/(mol/L)
Variation of apparent CEC with rock mass
Initial concentration of Cu-trien varies between 1.52x10-3 and 1.73x10-3 mol/L
L81
L82
L96
L40
L31
L22
L16
L14
L11
L09
L06
L99
24.11.2016 Léa Lévy - GEORG conference 18
19. 0
5
10
15
20
25
30
0 50 100 150 200
L22 - CEC and K Determination
K = 100
CEC = 24,2
(e)
0
5
10
15
20
25
30
35
40
0 50 100 150 200
Cu(trien)consumedbythe
reactioninmeq/100g
L14 - CEC and K Determination
K = 20
CEC = 38
0
5
10
15
20
25
30
35
40
0 100 200
L09 - CEC and K Determination
K = 25
CEC = 37
0
5
10
15
20
25
30
35
0 50 100 150 200
Cu(trien)consumedbythereactionin
meq/100g
2VCi/m = Initial Cu(trien) content in
meq/100g
L06 - CEC and K Determination
K = 20
CEC = 32.8
0
5
10
15
20
25
30
35
40
0 100 200
2VCi/m = Initial Cu(trien) content in
meq/100g
L99 - CEC and K Determination
K = 30
CEC = 34
(a) (c)
(d)(b)
0
5
10
15
20
25
0 50 100 150 200
2VCi/m = Initial Cu(trien) content in
meq/100g
L11 - CEC and K Determination
K = 50 or 25
CEC = 23,2 or 21,8
(f)
Analytical fit of experimental observations
24.11.2016 Léa Lévy - GEORG conference 19
21. References
• Flóvenz, Ó. G., Spangenberg, E., Kulenkampff, J., Árnason, K., Karlsdóttir, R. and Huenges, E. (2005). The role
of electrical interface conduction in geothermal exploration. World Geothermal Congress, Ankara, Turkey,
2005.
• Lyklema, J. (2001). Fundamentals of Interface and Colloid Science. Volume II Solid-Liquid Interfaces. Academic
Press.
• Meier, L. and Kahr, G. (1999). Determination of the Cation Exchange Capacity (CEC) of Clay Minerals Using
the Complexes of Copper(II) Ion with Triethylenetetramine and Tetraethylenepentamine. Clays and Clay
Minerals 47(3), 386–388.
• Meunier, A. (2013). Les argiles par la pratique. Vuibert
• Pezard, P. A. (1990). Electrical properties of mid-ocean ridge basalt and implications for the structure of the
upper oceanic crust in Hole 504B. Journal of Geophysical Research 95(B6), 9237.
• Vinegar, H. J. and Waxman, M.H. (1984). Induced polarization of shaly sands. Geophysics 49(8), 1267–1287.
• Revil, A., Le Breton, M., Niu, Q., Wallin, E., Haskins, E. and Thomas, D.M. (2016). Induced polarization of
volcanic rocks. I. Surface versus quadrature conductivity. In press.
• Waxman, M. H. and L. J. M. Smits (1968). Electrical conductivities in oil-bearing shaly sands. Soc. Pet. Eng. J.
8, 107–122.
24.11.2016 Léa Lévy - GEORG conference 21
22. Clay content and CEC
24.11.2016 Léa Lévy - GEORG conference 22
y = 92.23x
R² = 0.91
y = 67.86x
R² = 0.98
y = 36.02x
R² = 0.77
y = 9.20x
R² = 0.30
0
5
10
15
20
25
30
35
40
45
50
0% 10% 20% 30% 40% 50%
CECmeq/100g
Clay fraction (assuming the highest has 50% of clay)
CEC and clay fraction – based on the sum of d(001) and
d(002) areas – of whole rock samples
Clay >90% Smectite
MLC with 50-90% smectite
MLC with 20-50% smectite
Chlorite with 0-20% smectite
𝐶𝐸𝐶0 = 110 meq/100g
Editor's Notes
30 sec
I am Léa Lévy, I am doing a PhD in collaboration with these institutions here. In this talk there will be two main things: an overview of the physics linking clay minerals and electrical conduction and then my laboratory results showing to what extent the clay content can be quantified by electrical conductivity measurements.
I decided to include a condensate of knowledge about clay physics because when I started my work on this topic, I couldn‘t find that. I had to go back and forth between physicists and mineralogists to finally understand what is so special about clays in hydrothermal contexts.
and my goal today is to show you some of the physics between clay minerals and electrical conductivity first from a theoretical angle and then from an experimental angle, with laboratory results. Clays are fascinating because they are both geothermometers and electrical media. But when I first tried to understand why, I faced a deep intellectual void. Yes there is a conceptual void when you want to use a unique logic to jump from one scale to another. So I decided to start my presentation today with an overview of what makes clays so special for geothermal exploration. Then I will present laboratory results showing to what extent
50 sec
0) Well for soil scientists, it‘s the fraction below 2 um. But for mineralogists clay means clay minerals, also called phyllosilicates
1) Silicates because the building bricks are silicon tetrahedra and phyllo because the mineral is organized in sheets, actually an alternance of octahedral and tetrahedral sheets.
2) Let‘s look at smectite for example, tetrahedral: pink/yellow and octahedra: green. We see clearly here the TOT sequence, followed by a space filled with cations and water, where fascinating things are happening. And again TOT
3) Then we have chlorite with a different layer between the TOT sequences.
4) And illite with a big green potassium cation between the TOT sequences. Some clays are not organized in TOT but we are not interested in them here.
The main difference between all clays is the degree of substitution in the T and O sheets, which means the replacement of an atom (say Si) by an atom of similar size but lower charge in the crystal lattice. Each replacement creates a negative charge in the crystal.
5) The more substitutions the higher the charge. Depending on the level of the charge you will have or not mobile cations compensating the charge in the interlayer space. In smectite you have mobile cations but in illite the cations are not mobile and in chlorite, we don‘t have cations but a whole octahedral layer with a positive charge. This mobility can actually be quantified, it is what we called the CEC. The cation exchanges can also take place somwhere else than in the interlayer, but these other contributions are minimal so no detail here. A word about the unit: chemists tend to use the meq/100g while physicist use the Coulomb/kg.
So far this is quite known. But by the way how does the charge of the structure affects the mobility of cations? What do you think: high charge means high CEC or the contrary? Let‘s see.
1 min
What is the link between the degree of substitution and the mobility of cations? The degree of substitution determines the negative charge in the crystal lattice and it‘s the intensity of this charge that will allow or not the mobility of cations. What do you think: if the charge increase (in absolute value) is the CEC lower or higher? Let‘s check that out.
Let‘s imagine an axis
With an increasing absolute charge. Let‘s now see how the different clays are distributed according to their charges
Three groups of charges.
Kaolinite
Hop
Smectite
hope
illite/micas
hop
Chlorite
A first difference between these clays is their affinity for having water between the T sheets. It‘s the natural state of cations to be surrounded by water, but the water mocules, and especially the oxygen, eats a bit of the cation‘s charge. So if the charge to compensate in the clay is high, the water molecules are not welcome, because the whole cation is required to compensate the chagre.
As the charge decreases, the tolerance to water increases in the interlayer.
For example we have here two types of smectite that have different tolerance to water. The invitation of water molecules to the party affects a lot the strength of the bondings between the cations and the sheets.
From H bondings when no cations are involved to VdW bondings when cations are alone and to weak Coulombian attraction when water is present. And what happens if the bondings are weak? The cations are mobile.
So the answer is low charge = weak bondings = increased CEC. Now again, why is that interesting? For two reasons. First it means that an external force (let‘s say electrical) can remove the cations from the clay. Imagine you are a formula driver and you hit an obstacle. It‘s a force. If you have a normal belt, you will stay at your place, but if you have a poorly designed belt, say in paper, it will easily break and you will be ejected. It‘s pretty much how I see cations in clays. The second reason is because weak bondings also means unstability.
Yes the cations are the bolt mainting the whole clay structure. If they can leave the boat like that, the structure is not stable. And that brings us to my last slide about clays.
1 min
Let‘s sum up what‘s going on in smectite
Low substitution level
Low charge in the crystalline structure
Weak bondings between the structure and compensating cations
Mobility of cations and ability to spread an electrical current on one side
On the other side, as I just mentionned, unstability of the whole structure. Why is this instability important?
Pause. Read sentence. Yes the present understanding of chlorite formation in a context of hydrothermal convection is that it‘s a kinetic process, which begins by the formation of smectite. Just to clarify
Kinetic reaction is different from thermodynamic, because it involves time. The formation of chlorite is not triggered immediately when the right species are saturated in water, it will first form an itnermediary product, unstable, the smectite. Smectite is always a first step in chlorite formation but the higher the temperature, the shorter this step. This is also true for permeability: the higher fluid renewal, the shorter this step. That can explain why at high temperature or in highly permeable rock, you will see a chlorite/smectite ratio much higher.
Another key word in this sentence is hydrothermal convection. Because chlorite can also form in a thermal gradient, when heat conduction is the dominating process. In this case, the temperature is much higher but the flux lower and smectite does not seem to be involved. The presence of smectite is therefore a hint for an on-going hydrothermal activity: there must be a hydrothermal fluid not very far away in the time-space around the smectite. It‘s only a hint because smectite can be metastable: in some particular cases it can remain even after the hydrothermal activity is gone
But let‘s close the chain: if you have hydrothermal convection you will see smectite precipitate as a first product, before chlorite precipitates. We see that the low charge of smectite, causing also its high CEC, is actually tightly related to its function in the chlorite formation process.
So to conclude about the clays: we know that the variation of the smectite/chlorite ratio is a useful information about the temperature and permeability of the reservoir, even though it‘s not 100% reliable as such. And we also have a way to distinguish whether a clay is smectite-rich or chlorite-rich.
If I had to summarize the rest of my presententation with one sentence I would say that actually smectite is the only conductor in hydrothermal systems and that the conductivity of rocks linearly increases with the smectite content. Let‘s get there step by step.
30 sec.
I am working with core samples from four boreholes in Krafla, with different alteration stages and temperature. The maximujm depth is 700 m. Here we can see low temperature alteration in KH1, which is observed in the whole borehole.
KH3 has high temperature alteration but shows a maximum temperature of 30°C
KH5 has very high temperature alteration but maximum temperature of 150°C and overprinting of epidote by laumontite is observed. This section of the reservoir is likely colder now than in the past
KH6 is only 2km from KH5 but has the ivnerse trend: the temperature seems to be increasing. A gradient Smectite to MLC is clearly seen, as well as a gradient zeolite to wiarakite.
The rest of the presentation consists in laboratory measurements on these cores: conductivity, cation exchange capacity, quantitative Xray diffraction and also thin section observations.
All samples I am going to talk about are altered, at different degree. None of them are fresh.
2 min
The first results I am going to talk about is the straight relationship between the CEC and the clay content, and more aprticularly the role of smectite.
First let‘s consider all samples. They all have clay, as we can see on the XRD scans. Let‘s assume that the maximum clay fraction is 50%, which is a qualitative estimation, to start witth. Some of the samples have almost no smectite and some have 100% smecite in the clay. We can observe some trend here but it is a bit fuzzy. Actually if you look behind the main trend you can see different sub-trends.
Two independant and simple measurements: CEC and XRD on whole rock.
Separation between smectite ~100% vs contains some chlorite layers is straight forward (red/blue XRD curves).
CEC measurements very uncertain below 2 meq/100g and uncertainty being dealt with for high values: importance of thermodynamic factor + heterogeneity. That‘s why the trend at high clay content is not so good.
The clay fraction can be greatly improved with better quantification, so this is just preliminary but I decided to present it here to show that the relation is quite straight forward with simple manipulation.
Relative values: would need a reference sample to be absolute. Planned: use a sample that contain a lot of smectite and no zeolite and measure the weight loss during dehydration.
Proper XRD Quantitative with standards is given in weight ratio. Here it‘s unclear.
Of course when I say more than 50% smectite I don‘t know if it is in the mix-layer clay itself or if it is in the mixture of clays.
Beware: low-smectite content can mean very crystalline rock, not much altered (then we have a low clay fraction, can be seen with XRD of course) or a lot of chlorite and a high level of alteration. So again my work focuses on how to quantify the smectite content. Then how to interprete the smectite content is another question.
2 min
The first results I am going to talk about is the straight relationship between the CEC and the clay content, and more aprticularly the role of smectite.
First let‘s consider all samples. They all have clay, as we can see on the XRD scans. Let‘s assume that the maximum clay fraction is 50%, which is a qualitative estimation, to start witth. Some of the samples have almost no smectite and some have 100% smecite in the clay. We can observe some trend here but it is a bit fuzzy. Actually if you look behind the main trend you can see different sub-trends.
First two trends with samples containing mainly smectite, 100% in orange and about 75% in blue. If we assume that only one mineral phase gives the CEC signal (it has to be the smectite), we can deduce an average CEC for our smectite here from the orange curve. We obtain 110 meq/100g, which is in agreement with the litterature and strengthen our first hypothesis of a maximum of 50% of clay. Based on this value we can compute a smectite fraction in the whole rock, by comparing the CEC of whole rock to this index CEC. And then we can estimate the smectite fraction in the clay.
Methods?
Two independant and simple measurements: CEC and XRD on whole rock.
Separation between smectite ~100% vs contains some chlorite layers is straight forward (red/blue XRD curves).
CEC measurements very uncertain below 2 meq/100g and uncertainty being dealt with for high values: importance of thermodynamic factor + heterogeneity. That‘s why the trend at high clay content is not so good.
The clay fraction can be greatly improved with better quantification, so this is just preliminary but I decided to present it here to show that the relation is quite straight forward with simple manipulation.
Relative values: would need a reference sample to be absolute. Planned: use a sample that contain a lot of smectite and no zeolite and measure the weight loss during dehydration.
Proper XRD Quantitative with standards is given in weight ratio. Here it‘s unclear.
Of course when I say more than 50% smectite I don‘t know if it is in the mix-layer clay itself or if it is in the mixture of clays.
Beware: low-smectite content can mean very crystalline rock, not much altered (then we have a low clay fraction, can be seen with XRD of course) or a lot of chlorite and a high level of alteration. So again my work focuses on how to quantify the smectite content. Then how to interprete the smectite content is another question.
2 min
The first results I am going to talk about is the straight relationship between the CEC and the clay content, and more aprticularly the role of smectite.
First let‘s consider all samples. They all have clay, as we can see on the XRD scans. Let‘s assume that the maximum clay fraction is 50%, which is a qualitative estimation, to start witth. Some of the samples have almost no smectite and some have 100% smecite in the clay. We can observe some trend here but it is a bit fuzzy. Actually if you look behind the main trend you can see different sub-trends.
First two trends with samples containing mainly smectite, 100% in orange and about 75% in blue. If we assume that only one mineral phase gives the CEC signal (it has to be the smectite), we can deduce an average CEC for our smectite here from the orange curve. We obtain 110 meq/100g, which is in agreement with the litterature and strengthen our first hypothesis of a maximum of 50% of clay.
Then we start to observe MLC in thin sections, as well as some charcteristic peaks in XRD. MLC has smectite and chlorite layers with different propotions. Here we look at the global balance in the clay: how many layers of smectite, how many of chlorite, regardless whether they are in discrete smec/chl or in MLC minerals. A category with 60% smectite in the total clay can be seen.
Methods?
Two independant and simple measurements: CEC and XRD on whole rock.
Separation between smectite ~100% vs contains some chlorite layers is straight forward (red/blue XRD curves).
CEC measurements very uncertain below 2 meq/100g and uncertainty being dealt with for high values: importance of thermodynamic factor + heterogeneity. That‘s why the trend at high clay content is not so good.
The clay fraction can be greatly improved with better quantification, so this is just preliminary but I decided to present it here to show that the relation is quite straight forward with simple manipulation.
Relative values: would need a reference sample to be absolute. Planned: use a sample that contain a lot of smectite and no zeolite and measure the weight loss during dehydration.
Proper XRD Quantitative with standards is given in weight ratio. Here it‘s unclear.
Of course when I say more than 50% smectite I don‘t know if it is in the mix-layer clay itself or if it is in the mixture of clays.
Beware: low-smectite content can mean very crystalline rock, not much altered (then we have a low clay fraction, can be seen with XRD of course) or a lot of chlorite and a high level of alteration. So again my work focuses on how to quantify the smectite content. Then how to interprete the smectite content is another question.
2 min
The first results I am going to talk about is the straight relationship between the CEC and the clay content, and more aprticularly the role of smectite.
First let‘s consider all samples. They all have clay, as we can see on the XRD scans. Let‘s assume that the maximum clay fraction is 50%, which is a qualitative estimation, to start witth. Some of the samples have almost no smectite and some have 100% smecite in the clay. We can observe some trend here but it is a bit fuzzy. Actually if you look behind the main trend you can see different sub-trends.
First two trends with samples containing mainly smectite, 100% in orange and about 75% in blue. If we assume that only one mineral phase gives the CEC signal (it has to be the smectite), we can deduce an average CEC for our smectite here from the orange curve. We obtain 110 meq/100g, which is in agreement with the litterature and strengthen our first hypothesis of a maximum of 50% of clay.
Then we start to observe MLC in thin sections, as well as some charcteristic peaks in XRD. MLC has smectite and chlorite layers with different propotions. Here we look at the global balance in the clay: how many layers of smectite, how many of chlorite, regardless whether they are in discrete smec/chl or in MLC minerals. A category with 60% smectite in the total clay can be seen.
Then we jump to clay phases that are dominated by chlorite, but where smectite layers are still present and participating to the signal.
Methods?
Two independant and simple measurements: CEC and XRD on whole rock.
Separation between smectite ~100% vs contains some chlorite layers is straight forward (red/blue XRD curves).
CEC measurements very uncertain below 2 meq/100g and uncertainty being dealt with for high values: importance of thermodynamic factor + heterogeneity. That‘s why the trend at high clay content is not so good.
The clay fraction can be greatly improved with better quantification, so this is just preliminary but I decided to present it here to show that the relation is quite straight forward with simple manipulation.
Relative values: would need a reference sample to be absolute. Planned: use a sample that contain a lot of smectite and no zeolite and measure the weight loss during dehydration.
Proper XRD Quantitative with standards is given in weight ratio. Here it‘s unclear.
Of course when I say more than 50% smectite I don‘t know if it is in the mix-layer clay itself or if it is in the mixture of clays.
Beware: low-smectite content can mean very crystalline rock, not much altered (then we have a low clay fraction, can be seen with XRD of course) or a lot of chlorite and a high level of alteration. So again my work focuses on how to quantify the smectite content. Then how to interprete the smectite content is another question.
2 mn
The first results I am going to talk about is the straight relationship between the CEC and the clay content, and more aprticularly the role of smectite.
First let‘s consider all samples. They all have clay, as we can see on the XRD scans. Let‘s assume that the maximum clay fraction is 50%, which is a qualitative estimation, to start witth. Some of the samples have almost no smectite and some have 100% smecite in the clay. We can observe some trend here but it is a bit fuzzy. Actually if you look behind the main trend you can see different sub-trends.
First two trends with samples containing mainly smectite, 100% in orange and about 75% in blue. If we assume that only one mineral phase gives the CEC signal (it has to be the smectite), we can deduce an average CEC for our smectite here from the orange curve. We obtain 110 meq/100g, which is in agreement with the litterature and strengthen our first hypothesis of a maximum of 50% of clay.
Then we start to observe MLC in thin sections, as well as some charcteristic peaks in XRD. MLC has smectite and chlorite layers with different propotions. Here we look at the global balance in the clay: how many layers of smectite, how many of chlorite, regardless whether they are in discrete smec/chl or in MLC minerals. A category with 60% smectite in the total clay can be seen.
Then we jump to clay phases that are dominated by chlorite, but where smectite layers are still present and participating to the signal.
We have a final category of samples with about 10% smec in the clay and the rest is not classified. Here the red trend is not very satisfying. There is little smectite that the uncertainty of these low CEC values plays a big role.
What is aprticvularly interesting is the consistent behavior of the five first groups: they have an average smectite content in the clay and an average CEC, regardless whther they have a lot of lay or not. Let‘s now see how that can be translated in terms of electrical conductivity.
Relative values: would need a reference sample to be absolute. Planned: use a sample that contain a lot of smectite and no zeolite and measure the weight loss during dehydration.
Beware: low-smectite content can mean very crystalline rock, not much altered (then we have a low clay fraction, can be seen with XRD of course) or a lot of chlorite and a high level of alteration. So again my work focuses on how to quantify the smectite content. Then how to interprete the smectite content is another question.
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1) Standard equation for cond
1 was measured in laboratory
F was deduced from the slope here
Cs was taken as the lowest value
CEC measured in the laboratory,s ame values as we have shown before.
In Krafla the salinity is below 0,1 S/m so we are in the flat part of the graph and the value at 0,02 S/m is a rather good estimate of what we would measure in the field.
Classic method, just done with a lot of Icelandic samples here (new).
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It‘s actually the same data as the cond/CEC, but using the assumtpion that only smec gives the CEC, we translate that into smec content
The blue part of the graph regroups the samples which have a meaningful smectite content, more than 1% in the whole rock. The samples that are not on the blue part have between 0 and 1% of smectite, according to the CEC. The variations are thus subject to high uncertainty and they have been separated from the graph, to focus on the blue part. If we take all the blue samples, the comparison cond/smec content yields a very good correlation.
Let‘s look at the red part, where the clay contains less than 20% smectite, meaning at least 80% chlorite.
So we have a nice trend for samples contasining at least one percent smectite, which means more or less that the CEC is more than 1 meq/100g. But what‘s happening in the rest of the samples? Do they have little smectite because they have a lot of chlorite instead or because they don‘t have a lot of clay in general? We cannot know that based only on this plot. We just see in red samples with a low smectite/chlorite ratio and in blue samples with lot of smectite in the whole rock. There is actually an overlap: 5 samples have up to 2% of smectite in the whole rock but this 1-2% represents less then 20% of the clay so they have up to 18% chlorite in the whole rock.
My assumption was that smectite was only conducting mineral, how can I know if it is true? I would need to see the evolution of the conductivity for samples with a relatively constant smectite content and an increasing chlorite content. Let‘s do that.
Here we use a different dataset: the clay content comes from XRD. The red samples are the same red samples as in the other plot: the clay contains at least 80% chlorite. What does it tell us? Well those samples, as we see on the left graph have a relatively constant smectite content in the whole rock, less than 2%, but a chlorite content that varies between 5 and 18%. The conductivity does not seem to be correlated to this evolution. Therefore we conclude that the assumption of smectite being the only conductor is relevant.
It means that the normalized conductivity is a direct emasurement of the smectite content and that we can track the smectite content in the reservoir. But it‘s a bit difficult to measure F or even the porosity from the surface. How do we do then?
I am just going to mention here a possibility on how to proceed. The measurements are still going-on so results were still very preliminary, but the main idea is that you can constrain your itnerpretation by looking at the impedance signal as a whole, instead of only the amplitude ratio. Yes because in the field or in the lab you measure both an amplitude ratio and a phase, which is the definition of a complex number.And wWhen you look separately at the real and imaginary part of this complex number you have two values, which are pretty much dependant on the same variables and can help reseolve the ambiguity mentioned here: F, porosity, smectite-content. That‘s waht I am working on at the moment.
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One big idea that I want people to leave with?
Have good closing.
Stress the novelty of the work and why the results are important.
Stress the take-home message.
The so-called normalized interface conductivity is directly proportional to the smectite content, with a constant baseline for samples with almost no smectite. The comparison of smectite and chlorite electrical behavior, based on three different types of laboratory quantification, that is conductivity, CEC & XRD, is completely new. It is shown here in the particular case of Icelandic altered basalt.
According to my results I conclude that if you see a CEC signal in the chlorite zone it is likely due to the presence of a small fraction of smectite, and not to the CEC of chlorite. Which emphasizes the fact that smectite is the key in that whole problem, through the weak bondings between cations and crystal structure
The weak bondings relate the role of smectite in chlorite precipitation, through its unstability and the electrical conduction by cation exchange. And before I end this talk I would like to raise an open question.
We have seen that the presence of smectite itself can be misleading, in the case smectite is metastable. But could we use the evolution of the smectite content to locate the transition?
Thanks for your attention !
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Interest in the delay time of current carriage, due to polarization, i.e. charges storage because it is both tightly related and complementary to electrical conductivity. Interpretation of conductivity alone is ambiguous, whether it is CEC or porosity. But the imaginary part has the potential to clear the ambiguity because it brings a second equation on CEC/porosity/F.
Cs‘‘=f(freq): various phenomena visible.
Cs‘‘ = f (CEC) Trend less robust? A new parameter is taken into account: the pyrite (removed from the graph).
Done on sedimentary rock, very new on volcanic rock (Revil). Comparison with Revil trend: no chlorite in his samples, one with zeolites – but this is a non CEC zeolite (natrolite). All the rest is smectite with sometimes illite. This is the first study of complex conductivity vs CEC for volcanic rocks with alteration ranging in smectite-chlorite.
Depth uncertainty on cuttings
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Methods?
Two independant and simple measurements: CEC and XRD on whole rock.
Separation between smectite ~100% vs contains some chlorite layers is straight forward (red/blue XRD curves).
CEC measurements very uncertain below 2 meq/100g and uncertainty being dealt with for high values: importance of thermodynamic factor + heterogeneity. That‘s why the trend at high clay content is not so good.
The clay fraction can be greatly improved with better quantification, so this is just preliminary but I decided to present it here to show that the relation is quite straight forward with simple manipulation.
Relative values: would need a reference sample to be absolute. Planned: use a sample that contain a lot of smectite and no zeolite and measure the weight loss during dehydration.
Proper XRD Quantitative with standards is given in weight ratio. Here it‘s unclear.
Of course when I say more than 50% smectite I don‘t know if it is in the mix-layer clay itself or if it is in the mixture of clays.
Beware: low-smectite content can mean very crystalline rock, not much altered (then we have a low clay fraction, can be seen with XRD of course) or a lot of chlorite and a high level of alteration. So again my work focuses on how to quantify the smectite content. Then how to interprete the smectite content is another question.