This document provides an introduction to AVO and pre-stack inversion methods. It begins with a brief history of seismic interpretation, from purely structural interpretation to identifying "bright spots" to direct hydrocarbon detection using AVO and pre-stack inversion. It then discusses how AVO response is closely linked to rock physics properties like P-wave velocity, S-wave velocity, and density. The key concepts of AVO modeling and attributes are introduced. Finally, it provides an overview of rock physics and fluid replacement modeling using equations like Biot-Gassmann to model velocity and density changes with fluid saturation.
Avo ppt (Amplitude Variation with Offset)Haseeb Ahmed
AVO/AVA can physically explain presence of hydrocarbon in the reservoirs and the thickness, porosity, density, velocity, lithology and fluid content of the reservoir of the rock can be estimated.
Avo ppt (Amplitude Variation with Offset)Haseeb Ahmed
AVO/AVA can physically explain presence of hydrocarbon in the reservoirs and the thickness, porosity, density, velocity, lithology and fluid content of the reservoir of the rock can be estimated.
3D Facies Modelling project using Petrel software. Msc Geology and Geophysics
Abstract
The Montserrat and Sant Llorenç del Munt fan-delta complexes were developed during the Eocene in the Ebro basin. The depositional stratigraphic record of these fan deltas has been described as a made up by a several transgressive and regressive composite sequences each made up by several fundamental sequences. Each sequence set is in turn composed by five main facies belts: proximal alluvial fan, distal alluvial fan, delta front, carbonates platforms and prodelta.
Using outcrop data from three composite sequences (Sant Vicenç, Vilomara and Manresa), a 3D facies model was built. The key sequential traces of the studied area georeferenced and digitalized on to photorealistic terrain models, were the hard data used as input to reconstruct the main surfaces, which are separating transgressive and regressive stacking patterns. Regarding the facies modelling has been achieved using a geostatistical algorithm in order to define the stacking trend and the interfingerings of adjacent facies belts, and five paleogeographyc maps to reproduce the paleogeometry of the facies belts within each system tract.
The final model has been checked, using a real cross section, and analysed in order to obtain information about the Delta Front facies which are the ones susceptible to be analogous of a reservoir. Attending to the results including eight probability maps of occurrence, the transgressive sequence set of Vilomara is the greatest accumulation of these facies explained by its agradational component.
Seismic attributes are being used more and more often in the reservoir characterization and interpretation processes. The new software and computer’s development allows today to generate a large number of surface and volume attributes. They proved to be very useful for the facies and reservoir properties distribution in the geological models, helping to improve their quality in the areas between the wells and areas without wells. The seismic attributes can help to better understand the stratigraphic and structural features, the sedimentation processes, lithology variations, etc. By improving the static geological models, the dynamic models are also improved, helping to better understand the reservoirs’ behavior during exploitation. As a result, the estimation of the recoverable hydrocarbon volumes becomes more reliable and the development strategies will become more successful.
Why we need a Water Saturation vs. Height function for reservoir modelling.
Definitions: Free-Water-Level, HWC, Net, Swirr
Several case studies showing applications to reservoir modelling.
To determine a field’s hydrocarbon in place, it is necessary to model the distribution of hydrocarbon and water
throughout the reservoir. A water saturation vs. height (SwH) function provides this for the reservoir model. A
good SwH function ensures the three independent sources of fluid distribution data are consistent. These being
the core, formation pressure and electrical log data. The SwH function must be simple to apply, especially in
reservoirs where it is difficult to map permeability or where there appears to be multiple contacts. It must
accurately upscale the log and core derived water saturations to the reservoir model cell sizes.
This presentation clarifies the, often misunderstood, definitions for the free-water-level (FWL), transition zone
and irreducible water saturation. Using capillary pressure theory and the concept of fractals, a convincing SwH
function is derived from first principles. The derivation is simpler than with classical functions as there is no
porosity banding. Several case studies are presented showing the excellent match between the function and
well data. The function makes an accurate prediction of water saturations, even in wells where the resistivity
log was not run, due to well conditions. Logs and core data from eleven fields, with vastly different porosity and
permeability characteristics, depositional environments, and geological age, are compared. These
demonstrates how this SwH function is independent of permeability and litho-facies type and accurately
describes the reservoir fluid distribution.
The function determines the free water level, the hydrocarbon to water contact (HWC), net reservoir cut-off,
the irreducible water saturation, and the shape of the transition zone for the reservoir model. The function
provides a simple way to quality control electrical log and core data and justifies using core plug sized samples
to model water saturations on the reservoir scale. The presentation describes how the function has been used
to predict fluid contacts in wells where they are unclear, or where the contact is below the total depth of the
well. As the function uses the FWL as its base, it explains the apparently varying HWC in some fields and how
low porosity reservoirs can be fully water saturated for hundreds of feet above the FWL.
This simple convincing function calculates water saturation as a function of the height above the free water level
and the bulk volume of water and is independent of the porosity and permeability of the reservoir. It was voted
the best paper at the 1993 SPWLA Symposium in Calgary.
3D Facies Modelling project using Petrel software. Msc Geology and Geophysics
Abstract
The Montserrat and Sant Llorenç del Munt fan-delta complexes were developed during the Eocene in the Ebro basin. The depositional stratigraphic record of these fan deltas has been described as a made up by a several transgressive and regressive composite sequences each made up by several fundamental sequences. Each sequence set is in turn composed by five main facies belts: proximal alluvial fan, distal alluvial fan, delta front, carbonates platforms and prodelta.
Using outcrop data from three composite sequences (Sant Vicenç, Vilomara and Manresa), a 3D facies model was built. The key sequential traces of the studied area georeferenced and digitalized on to photorealistic terrain models, were the hard data used as input to reconstruct the main surfaces, which are separating transgressive and regressive stacking patterns. Regarding the facies modelling has been achieved using a geostatistical algorithm in order to define the stacking trend and the interfingerings of adjacent facies belts, and five paleogeographyc maps to reproduce the paleogeometry of the facies belts within each system tract.
The final model has been checked, using a real cross section, and analysed in order to obtain information about the Delta Front facies which are the ones susceptible to be analogous of a reservoir. Attending to the results including eight probability maps of occurrence, the transgressive sequence set of Vilomara is the greatest accumulation of these facies explained by its agradational component.
Seismic attributes are being used more and more often in the reservoir characterization and interpretation processes. The new software and computer’s development allows today to generate a large number of surface and volume attributes. They proved to be very useful for the facies and reservoir properties distribution in the geological models, helping to improve their quality in the areas between the wells and areas without wells. The seismic attributes can help to better understand the stratigraphic and structural features, the sedimentation processes, lithology variations, etc. By improving the static geological models, the dynamic models are also improved, helping to better understand the reservoirs’ behavior during exploitation. As a result, the estimation of the recoverable hydrocarbon volumes becomes more reliable and the development strategies will become more successful.
Why we need a Water Saturation vs. Height function for reservoir modelling.
Definitions: Free-Water-Level, HWC, Net, Swirr
Several case studies showing applications to reservoir modelling.
To determine a field’s hydrocarbon in place, it is necessary to model the distribution of hydrocarbon and water
throughout the reservoir. A water saturation vs. height (SwH) function provides this for the reservoir model. A
good SwH function ensures the three independent sources of fluid distribution data are consistent. These being
the core, formation pressure and electrical log data. The SwH function must be simple to apply, especially in
reservoirs where it is difficult to map permeability or where there appears to be multiple contacts. It must
accurately upscale the log and core derived water saturations to the reservoir model cell sizes.
This presentation clarifies the, often misunderstood, definitions for the free-water-level (FWL), transition zone
and irreducible water saturation. Using capillary pressure theory and the concept of fractals, a convincing SwH
function is derived from first principles. The derivation is simpler than with classical functions as there is no
porosity banding. Several case studies are presented showing the excellent match between the function and
well data. The function makes an accurate prediction of water saturations, even in wells where the resistivity
log was not run, due to well conditions. Logs and core data from eleven fields, with vastly different porosity and
permeability characteristics, depositional environments, and geological age, are compared. These
demonstrates how this SwH function is independent of permeability and litho-facies type and accurately
describes the reservoir fluid distribution.
The function determines the free water level, the hydrocarbon to water contact (HWC), net reservoir cut-off,
the irreducible water saturation, and the shape of the transition zone for the reservoir model. The function
provides a simple way to quality control electrical log and core data and justifies using core plug sized samples
to model water saturations on the reservoir scale. The presentation describes how the function has been used
to predict fluid contacts in wells where they are unclear, or where the contact is below the total depth of the
well. As the function uses the FWL as its base, it explains the apparently varying HWC in some fields and how
low porosity reservoirs can be fully water saturated for hundreds of feet above the FWL.
This simple convincing function calculates water saturation as a function of the height above the free water level
and the bulk volume of water and is independent of the porosity and permeability of the reservoir. It was voted
the best paper at the 1993 SPWLA Symposium in Calgary.
Advances in Rock Physics Modelling and Improved Estimation of CO2 Saturation, Giorgos Papageorgiou - Geophysical Modelling for CO2 Storage, Leeds, 3 November 2015
Integration of Aeromagntic Data and Landsat Imagery for structural Analysis f...iosrjce
In this study, different digital format data sources including aeromagnetic and remotely sensed
(Landsat 8 and ASTER) images were used for structural and tectonic interpretation of the Mahabubnager
and Gulbarga districts of Telangana and Karnataka states in the Eastern Dharwarcraton. From analysis of
Landsat and ASTER images, the surface morphology and major lineaments trending in the NW–SE, E-W and
NE-SW were identified. Qualitative analysis of IGRF corrected aeromagnetic data were carried out using the
analytical signal, reduction to pole, horizontal & vertical gradient maps, several lineaments trending in three
major directions NE-SW, NW-SE and E-W were delineated. The structural features inferred from image
analysis were corroborated, the zones of intersection of these structural trends which could have acted as
potential sites for kimberlites emplacement were accordingly delineated at 21 locations. Subsequently,
quantitative analysis of magnetic inversion at 21 profiles are carried out utilizing GM-SYS and Geosoft
software, brought out the subsurface configuration of kimberlites. The inferred magnetic models are exhibiting
V-shaped / Oval type structure. Depth of the inferred structures has been revealed by the Euler deconvolution
methods suggest depth varies from 536 to 1640 mts
Learn about going from 3D scans of core samples and other rock types to visualisation, analysis and model generation with Simpleware. Trials available here: http://www.simpleware.com/software/trial/
An Integrated Study of Gravity and Magnetic Data to Determine Subsurface Stru...iosrjce
:The present study wascarried out to delineate the location, extension, trend and depth of subsurface
structures of Alamein area. To achieve this aim, the gravity and aeromagnetic data have been subjected to
different analytical techniques. The Fast Fourier Transform technique was used to separatethe residual
components from the regional ones. The resulted maps showed that the area was affected mainly bytheENE, EW,
WNWand NWtectonic trends. In addition, spectral analysis technique was applied on magnetic anomalies to
estimate the depth to basement surface, which varies from 3.03 in southern part to 7.24 Km in northern part.3DEulerdeconvloution
and tilt angle derivative techniques were carried out to detect the edges of magnetic sources
and to determine their depths.Correlation between them shows acoincidence between Euler solution and zero
lines of tilt angle map. A tentative basement structure map is constructed from the integration of these results
and geological information. This map shows alternative uplifted and downfaulted structure trending in the ENE,
NE and E-W directions. In addition, the NNW to NW strike-slip faults intersected them in later events. Finally,
2-D modeling technique was run on three gravity and magnetic profiles in the same location. Different drilled
wells and the constructed basement structure map support these modeled profiles. Theyshow an acidic basement
rocks. A general decreasing of Conrad discontinuity depths from about 20.5 km at southern part to 17.9 km at
northern part can be noticed. Moreover, the crustal thickness (depth to Moho discontinuity), varies between
31.5 and 28.5 km revealing visibly crustal stretching and thinning northerly
Developments and directions in 3D mapping of mineral systems using geophysicsRichard Lane
(See Geoscience Australia website - https://www.ga.gov.au/products/servlet/controller?event=GEOCAT_DETAILS&catno=70386 ). “Developments and directions in 3D mapping of mineral systems using geophysics” by Richard Lane (Geoscience Australia, richard.lane@ga.gov.au). Presented at “Science at the Surveys” (Melbourne, Victoria, Australia, 22 March 2010). The primary author would like to acknowledge the assistance of many people who have provided material and thoughts for this presentation, with special mention of Richard Chopping, Marina Costelloe, David Hutchinson, Nick Williams, and Lesley Wyborn. This presentation material will be included in a lecture that will be given in various South Pacific locations during 2011 as part of the Society of Exploration Geophysicists “Honorary Lecture Program” sponsored by Shell (http://www.seg.org/).
full cv Senior geophysicist ,international instructor, technical advisormohamed Shihata
I'm honored to apply for geosciences and business development jobs seeking to create innovative workflow for solve unconventional geosciences problems, reliable and ambitious geophysicist, Enjoys learning new skills, confident and experienced working in different cultures and countries, good computers skills (Kingdome and FFA, Jewel_Suite,Opendetect , Hampson-Russell).
Total experiences year 8 years divided to 3 years extensive experiences technical support experience with kingdom suit interesting in seismic attributes analysis and have good experience in seismic interpretation, 2Support business development in key accounts and attract new clients within his / her area of focus, 3years international instructor for different companies and academic centers
I send my CV which might be the way to join your staff, I would appreciate meeting with you at your convenient time, so that we may discuss my qualifications in relation to your needs
A study on multple time lapse seismic avo inversionzhenhuarui
The seismic responses caused by different reservoir parameter variations are numerically simulated,
and then the feasibility of discriminating different reservoir parameters and realizing quantitative interpretation
using time-lapse seismic AVO technique is ensured. Based on Aki and Richards’ simplified AVO equation, the
formula of P-P wave and P-S wave for time-lapse seismic AVO was derived in details. According to the rock
physical model of S oil field and the formula acquired, the multiple time-lapse seismic AVO inversion equations
are achieved to discriminate the changes of oil saturation and effective pressure. It is shown by simulated data
experiment that the time-lapse seismic AVO inversion is feasible, and the formula derived in this paper is effective
to discriminate the changes of oil saturation and effective pressure, and to improve the precision of time-lapse
seismic interpretation.
The Effect of Bottom Sediment Transport on Wave Set-Upijceronline
In this paper we augment the wave-averaged mean field equations commonly used to describe wave set-up and wave-induced mean currents in the near-shore zone, with an empirical sediment flux law depending only on the wave-induced mean current and mean total depth. This model allows the bottom to evolve slowly in time, and is used to examine how sediment transport affects wave set-up in the surf zone. We show that the mean bottom depth in the surf zone evolves according to a simple wave equation, whose solution predicts that the mean bottom depth decreases and the beach is replenished. Further, we show that if the sediment flux law also allows for a diffusive dependence on the beach slope then the simple wave equation is replaced by a nonlinear diffusion equation which allows a steady-state solution, the equilibrium beach profile
Seismic data Interpretation On Dhodak field PakistanJamal Ahmad
I (Jamal Ahmad) presented this on 21 Feb, 2009 to defend my M.Phil dissertation in Geophysics at QAU, Islamabad, Pakistan. For more information about this, you may contact me directly at jamal.qau@gmail.com.
Analysis of the Interaction between A Fluid and A Circular Pile Using the Fra...IJERA Editor
The purpose of this research is to study the interaction between a fluid and a circular pile, located downstream
from a fan-shaped dam, through the fractional Navier-Stokes equations, and in particular, its approximation to
the boundary layer. The flow region is divided into zones according to the vorticity transport theory of
turbulence. First, we consider the limit of the spatial occupancy index close to 1. Then, a stream function is
introduced, and for the potential zone, we consider a complex potential, using the inverse distances on a circle.
In the other limit, when the spatial occupation index approaches 0, we consider the equations of the boundary
layer in the limit of fully developed turbulence. Next, for the last approaches, a new stream function and
velocities in their radial and polar components are obtained. We also find the asymmetry of the pressure
distribution around the pile, based on the viscosity and considering that the pressure drag force and the friction
coefficients are proportional to the inverse of the Reynolds number. We conclude that D'Alembert's paradox and
Thomson's theorem has been resolved. For applications, in the case of the turbulent wake, we are interested both
in the orientation given by the pile symmetry axis and its extension. The criterion that should be satisfied is: the
diameter of the pile, on the border of inequality, must be located as proportional average between the length of
the turbulent wake and twice the characteristic length associated with the dam, whose aspect ratio, in turn, to the
pile diameter, determines the contraction factor.
Wavelet estimation for a multidimensional acoustic or elastic earthArthur Weglein
A new and general wave theoretical wavelet estimation
method is derived. Knowing the seismic wavelet
is important both for processing seismic data and for
modeling the seismic response. To obtain the wavelet,
both statistical (e.g., Wiener-Levinson) and deterministic
(matching surface seismic to well-log data) methods
are generally used. In the marine case, a far-field
signature is often obtained with a deep-towed hydrophone.
The statistical methods do not allow obtaining
the phase of the wavelet, whereas the deterministic
method obviously requires data from a well. The
deep-towed hydrophone requires that the water be
deep enough for the hydrophone to be in the far field
and in addition that the reflections from the water
bottom and structure do not corrupt the measured
wavelet. None of the methods address the source
array pattern, which is important for amplitude-versus-
offset (AVO) studies.
Wavelet estimation for a multidimensional acoustic or elastic earth- Arthur W...Arthur Weglein
A new and general wave theoretical wavelet estimation
method is derived. Knowing the seismic wavelet
is important both for processing seismic data and for
modeling the seismic response. To obtain the wavelet,
both statistical (e.g., Wiener-Levinson) and deterministic
(matching surface seismic to well-log data) methods
are generally used. In the marine case, a far-field
signature is often obtained with a deep-towed hydrophone.
The statistical methods do not allow obtaining
the phase of the wavelet, whereas the deterministic
method obviously requires data from a well. The
deep-towed hydrophone requires that the water be
deep enough for the hydrophone to be in the far field
and in addition that the reflections from the water
bottom and structure do not corrupt the measured
wavelet. None of the methods address the source
array pattern, which is important for amplitude-versus-
offset (AVO) studies
Obtaining three-dimensional velocity information directly from reflection sei...Arthur Weglein
This paper present a formalism for obtaining the subsurface
velocity configuration directly from reflection seismic data.
Our approach is to apply the results obtained for inverse
problems in quantum scattering theory to the reflection
seismic problem. In particular, we extend the results of
Moses (1956) for inverse quantum scattering and Razavy
(1975) for the one-dimensional (1-D) identification of the
acoustic wave equation to the problem of identifying the
velocity in the three-dimensional (3-D) acoustic wave equation
from boundary value measurements. No a priori knowledge
of the subsurface velocity is assumed and all refraction,
diffraction, and multiple reflection phenomena are
taken into account. In addition, we explain how the idea of
slant stack in processing seismic data is an important part
of the proposed 3-D inverse scattering formalism.
SUBMERGED HORIZONTAL PLATE FOR COASTAL RETREATING CONTROL: THE CASE OF POLIGN...marmar83
Many sites along the Apulian coast (SE Italy) are composed of weathered and fractured carbonate rocks, affected by intense erosion and frequent sliding. A detailed research of the University of Bari (Andriani and Walsh, 2007) highlighted that from 1997 through 2003, the cliff retreat rate varied from 0.01 to 0.1 myr-1, mostly as a consequence of wave action. In the case of Polignano a Mare, a small town 30 km far from Bari, the erosive process seems to be seriously affecting the stability of buildings. Here, because of the bathymetry, the traditional rubble mound breakwaters are not suited. As an alternative, a rigid horizontal submerged plate on piles is here considered. Since there is no universally accepted theory nor formula to calculate the hydraulic performance of such kind of structure physical models have been constructed at HR Wallingford and subjected to random wave attacks. This paper discusses results of those tests.
Mechanical wave descriptions for planets and asteroid fields: kinematic model...Premier Publishers
Models with wave dynamics and oscillations in the solar system are presented. A solitonial solution (Korteweg-de Vries), for a density field, is related to the formations of planets. A new nonlinear equation for a solitonial, will be derived, and denoted ‘J-T equation’. The linearized version has solutions, which are small vibrations with eigen frequency proportional to the parameters describing the solitonial wave, around a constant level, which is 2/3 of the maximum solitonial density. The location and orbital motion of Mercury and Venus are compared with wave dynamics. The tidal effect for Earth is analysed in terms of dynamics. Related phenomena for other planetary objects are discussed in conjunction with assuming a Roche limit.
Gravimetri Dersi için aşağıda ki videoları izleyebilirsiniz.
Link 01: https://www.youtube.com/watch?v=HTyjVaVGx0k
Link 02: https://www.youtube.com/watch?v=fUkfgI8XaOE
Geopsy yaygın olarak kullanılan profesyonel bir program. Özellikle, profesyonel program deneyimi yeni mezunlarda çok aranan bir özellik. Bir öğrencim çalışmasında kullanmayı planlıyor.
The Indian economy is classified into different sectors to simplify the analysis and understanding of economic activities. For Class 10, it's essential to grasp the sectors of the Indian economy, understand their characteristics, and recognize their importance. This guide will provide detailed notes on the Sectors of the Indian Economy Class 10, using specific long-tail keywords to enhance comprehension.
For more information, visit-www.vavaclasses.com
Synthetic Fiber Construction in lab .pptxPavel ( NSTU)
Synthetic fiber production is a fascinating and complex field that blends chemistry, engineering, and environmental science. By understanding these aspects, students can gain a comprehensive view of synthetic fiber production, its impact on society and the environment, and the potential for future innovations. Synthetic fibers play a crucial role in modern society, impacting various aspects of daily life, industry, and the environment. ynthetic fibers are integral to modern life, offering a range of benefits from cost-effectiveness and versatility to innovative applications and performance characteristics. While they pose environmental challenges, ongoing research and development aim to create more sustainable and eco-friendly alternatives. Understanding the importance of synthetic fibers helps in appreciating their role in the economy, industry, and daily life, while also emphasizing the need for sustainable practices and innovation.
How to Create Map Views in the Odoo 17 ERPCeline George
The map views are useful for providing a geographical representation of data. They allow users to visualize and analyze the data in a more intuitive manner.
Students, digital devices and success - Andreas Schleicher - 27 May 2024..pptxEduSkills OECD
Andreas Schleicher presents at the OECD webinar ‘Digital devices in schools: detrimental distraction or secret to success?’ on 27 May 2024. The presentation was based on findings from PISA 2022 results and the webinar helped launch the PISA in Focus ‘Managing screen time: How to protect and equip students against distraction’ https://www.oecd-ilibrary.org/education/managing-screen-time_7c225af4-en and the OECD Education Policy Perspective ‘Students, digital devices and success’ can be found here - https://oe.cd/il/5yV
How to Split Bills in the Odoo 17 POS ModuleCeline George
Bills have a main role in point of sale procedure. It will help to track sales, handling payments and giving receipts to customers. Bill splitting also has an important role in POS. For example, If some friends come together for dinner and if they want to divide the bill then it is possible by POS bill splitting. This slide will show how to split bills in odoo 17 POS.
Operation “Blue Star” is the only event in the history of Independent India where the state went into war with its own people. Even after about 40 years it is not clear if it was culmination of states anger over people of the region, a political game of power or start of dictatorial chapter in the democratic setup.
The people of Punjab felt alienated from main stream due to denial of their just demands during a long democratic struggle since independence. As it happen all over the word, it led to militant struggle with great loss of lives of military, police and civilian personnel. Killing of Indira Gandhi and massacre of innocent Sikhs in Delhi and other India cities was also associated with this movement.
2024.06.01 Introducing a competency framework for languag learning materials ...Sandy Millin
http://sandymillin.wordpress.com/iateflwebinar2024
Published classroom materials form the basis of syllabuses, drive teacher professional development, and have a potentially huge influence on learners, teachers and education systems. All teachers also create their own materials, whether a few sentences on a blackboard, a highly-structured fully-realised online course, or anything in between. Despite this, the knowledge and skills needed to create effective language learning materials are rarely part of teacher training, and are mostly learnt by trial and error.
Knowledge and skills frameworks, generally called competency frameworks, for ELT teachers, trainers and managers have existed for a few years now. However, until I created one for my MA dissertation, there wasn’t one drawing together what we need to know and do to be able to effectively produce language learning materials.
This webinar will introduce you to my framework, highlighting the key competencies I identified from my research. It will also show how anybody involved in language teaching (any language, not just English!), teacher training, managing schools or developing language learning materials can benefit from using the framework.
Instructions for Submissions thorugh G- Classroom.pptxJheel Barad
This presentation provides a briefing on how to upload submissions and documents in Google Classroom. It was prepared as part of an orientation for new Sainik School in-service teacher trainees. As a training officer, my goal is to ensure that you are comfortable and proficient with this essential tool for managing assignments and fostering student engagement.
Instructions for Submissions thorugh G- Classroom.pptx
Reservoir Geophysics : Brian Russell Lecture 1
1. AVO and Inversion - Part 1
Introduction and Rock Physics
Dr. Brian Russell
2. Overview of AVO and Inversion
This tutorial is a brief introduction to the Amplitude
Variations with Offset, or Amplitude Versus Offset
(AVO), and pre-stack inversion methods.
I will briefly review how the interpretation of seismic
data has changed through the years.
I will then look at why AVO and pre-stack inversion
was an important step forward for the interpretation
of hydrocarbon anomalies.
Finally, I will show why the AVO and pre-stack
inversion responses are closely linked to the rock
physics of the reservoir.
2
3. A Seismic Section
The figure above shows a stacked seismic section recorded over the shallow
Cretaceous in Alberta. How would you interpret this section?
3
4. Structural Interpretation
Your eye may first go to an anticlinal seismic event between 630 and 640 ms. Here, it
has been picked and called H1. A seismic interpreter prior to 1970 would have looked
only at structure and perhaps have located a well at CDP 330.
4
5. Gas Well Location
And, in this case, he or she would have been right! A successful gas well was drilled
at that location. The figure above shows the sonic log, integrated to time, spliced on
the section. The gas sand top and base are shown as black lines on the log.
5
6. “Bright Spots”
But this would have been a lucky guess, since structure alone does not tell you that a
gas sand is present. A geophysicist in the 1970’s would have based the well on the
fact that there is a “bright spot” visible on the seismic section, as indicated above.
6
7. What is a “Bright Spot”?
To understand “bright spots”, recall the definition of the zero-offset reflection
coefficient, shown in the figure above. R0 , the reflection coefficient, is the amplitude
of the seismic trough shown. Note also that the product of density, r, and P-wave
velocity, V, is called acoustic impedance.
1122
1122
0
VV
VV
R
rr
rr
Seismic
raypath
Interface at
depth = d
r1 V1
r2 V2
Reflection at time
t = 2d/V1
Geology Seismic
Surface
Seismic
Wavelet
Shale
Gas Sand
7
8. This figure, from
Gardner et al. (1974),
shows a big difference
between shale and gas
sand velocity at
shallow depths in the
Gulf of Mexico. The
paper also derived the
“Gardner” equation,
which states that
density and velocity are
related by the equation
r = 0.23 V 0.25
Thus, we would expect
a large reflection
coefficient, or “bright
spot”, for shallow gas
sands.
Difference between shale and gas
sand velocity at shallow depth.
Gardner’s results for GOM
8
9. The AVO Method
“Bright spots” can
be caused by
lithologic variations
as well as gas
sands.
Geophysicists in
the 1980’s looked at
pre-stack seismic
data and found that
amplitude change
with offset could be
used to explain gas
sands (Ostrander,
1984). This example
is a Class 3 gas
sand, which we will
discuss later.
9
10. What causes the AVO Effect?
The traces in a seismic gather reflect from the subsurface at increasing
angles of incidence q. The first order approximation to the reflection
coefficients as a function of angle is given by adding a second term to the
zero-offset reflection coefficient:
qq 2
0 sin)( BRR
q1q2q3
Surface
Reflectorr1 VP1 VS1
r2 VP2 VS2
B is a gradient term which produces the AVO effect. It is dependent on
changes in density, r, P-wave velocity, VP, and S-wave velocity, VS.
10
11. This diagram shows a schematic diagram of (a) P, or compressional, waves,
(b) SH, or horizontal shear-waves, and (c) SV, or vertical shear-waves, where
the S-waves have been generated using a shear wave source (Ensley, 1984).
(a) (b) (c)
P and S-Waves
11
Note that we can also record S wave information.
12. Why is S-wave Velocity Important?
12
The plot on the left
shows P and S-wave
velocity plot as a
function of gas
saturation (100% gas
saturation = 0% Water
Saturation), computed
with the Biot-
Gassmann equations.
Note that P-wave
velocity drops
dramatically, but S-
wave velocity only
increases slightly
(why?). This will be
discussed in the next
section.
13. AVO Modeling
Based on AVO theory and the rock physics of the reservoir, we can perform AVO
modeling, as shown above. Note that the model result is a fairly good match to the
offset stack. Poisson’s ratio is a function of Vp/Vs ratio and will be discussed in the
next chapter.
P-wave Density S-wave
Poisson’s
ratio
Synthetic Offset Stack
13
15. Cross-Plotting of Attributes
One of the AVO methods that we will be
discussing later in the course involves
cross-plotting the zero-offset reflection
coefficient (R0, usually called A), versus the
gradient (B), as shown on the left.
As seen in the figure below, the highlighted
zones correspond to the top of gas sand
(pink), base of gas sand (yellow), and a hard
streak below the gas sand (blue).
Gradient (B)
Intercept (A)
15
16. AVO Inversion
A new tool combines
inversion with AVO
Analysis to enhance the
reservoir discrimination.
Here, we have inverted for
P-impedance and Vp/Vs
ratio, cross-plotted and
identified a gas sand.
16
Gas
Sand
18. Conclusions
Seismic interpretation has evolved over the years,
from strictly structural interpretation, through “bright
spot” identification, to direct hydrocarbon detection
using AVO and pre-stack inversion.
In this short course I will elaborate on the ideas that
have been presented in this short introduction.
As a starting point, the next section I will discuss the
principles of rock physics in more detail.
I will then move to AVO modeling and analysis.
Finally, I will look at AVO and pre-stack inversion
analysis on real seismic data.
18
20. Pores / FluidRock Matrix
The AVO response is dependent on the properties of P-wave velocity (VP),
S-wave velocity (VS), and density (r) in a porous reservoir rock. As shown
below, this involves the matrix material, the porosity, and the fluids filling
the pores:
Basic Rock Physics
20
21. )1()1( whcwwmsat SρSρρρ
.subscriptswatern,hydrocarbo
matrix,saturated,,
,saturationwater
porosity,
density,:where
wsat,m,hc
wS
ρ
This is illustrated in the next graph.
Density effects can be modeled with the following equation:
Density
21
22. Density versus Water Saturation
Density vs Water Saturation
Sandstone with Porosity = 33%
Densities (g/cc): Matrix = 2.65, Water = 1.0,
Oil = 0.8, Gas = 0.001
1.6
1.7
1.8
1.9
2
2.1
2.2
0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1
Water Saturation
Density
Oil Gas
Here is a plot of density
vs water saturation for a
porous sand with the
parameters shown,
where we have filled the
pores with either oil or
gas.
In the section on AVO
we will model both the
wet sand and the 50%
saturated gas sand.
Note that these density
values can be read off
the plot and are:
rwet = 2.11 g/cc
rgas = 1.95 g/cc
22
23. P and S-Wave Velocities
Unlike density, seismic velocity involves the deformation of a rock as a
function of time. As shown below, a cube of rock can be compressed, which
changes its volume and shape or sheared, which changes its shape but not
its volume.
23
24. P-waves S-waves
The leads to two different types of velocities:
P-wave, or compressional wave velocity, in which the direction of
particle motion is in the same direction as the wave movement.
S-wave, or shear wave velocity, in which the direction of particle
motion is at right angles to the wave movement.
P and S-Wave Velocities
24
25. r
2
PV
r
SV
where: = the first Lamé constant,
= the second Lamé constant,
and r = density.
The simplest forms of the P and S-wave velocities are derived for
non-porous, isotropic rocks. Here are the equations for velocity
written using the Lamé coefficients:
Velocity Equations using and
25
26. r
3
4
K
VP r
SV
where: K = the bulk modulus, or the reciprocal of compressibility.
= + 2/3
= the shear modulus, or the second Lamé constant,
and r = density.
Another common way of writing the velocity equations is with
bulk and shear modulus:
Velocity Equations using K and
26
27. Poisson’s Ratio from strains
The Poisson’s ratio, , is defined as the negative of the ratio
between the transverse and longitudinal strains:
If we apply a compressional
force to a cylindrical piece of
rock, as shown on the right, we
change its shape.
)//()/( LLRR
R
R+R
L+L L
F (Force)
F
The longitudindal strain is given
by L/L and the transverse strain
is given by R/R.
(In the typical case shown above, L is negative, so is positive)
27
28. 22
2
2
2
S
P
V
V
:where
This formula is more useful in our calculations than the formula given
by the ratio of the strains. The inverse to the above formula, allowing
us to derive VP or VS from , is given by:
12
222
A second way of looking at Poisson’s ratio is to use the ratio of VP to VS,
and this definition is given by:
Poisson’s Ratio from velocity
28
29. Vp/Vs vs Poisson's Ratio
-0.2
-0.1
0
0.1
0.2
0.3
0.4
0.5
0 1 2 3 4 5 6 7 8 9 10
Vp/Vs
Poisson'sRatio
Gas Case Wet Case
Poisson’s Ratio vs VP/VS ratio
29
30. If VP/VS = 2, then = 0
If VP/VS = 1.5, then = 0.1 (Gas Case)
If VP/VS = 2, then = 1/3 (Wet Case)
If VP/VS = , then = 0.5 (VS = 0)
Poisson’s Ratio
From the previous figure, note that there are several values of
Poisson’s ratio and VP/VS ratio that are important to remember.
30
Note also from the previous figure that Poisson’s ratio can
theoretically be negative, but this has only been observed for
materials created in the lab (e.g. Goretex and polymer foams).
31. A plot of velocity versus
water saturation using
the above equation. We
used a porous sand with
the parameters shown
and have filled the pores
with either oil or gas.
This equation does not
hold for gas sands, and
this lead to the
development of the Biot-
Gassmann equations.
Velocity vs Water Saturation
Wyllie's Equation
Porosity = 33%
Vmatrix = 5700 m/s, Vw = 1600 m/s,
Voil = 1300 m/s, Vgas = 300 m/s.
500
1000
1500
2000
2500
3000
3500
0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1
Water Saturation
Velocity(m/sec)
Oil Gas
Velocity in Porous Rocks
Velocity effects can be modeled by the volume average equation:
V/t,)S(tSt)(tt whcwwmsat 1where11
31
32. sat
satsat
satP
K
V
r
3
4
_
sat
sat
satSV
r
_
Note that rsat is found using the volume average equation:
The volume average equation gives incorrect results for gas sands.
Independently, Biot (1941) and Gassmann (1951), developed a more
correct theory of wave propagation in fluid saturated rocks, especially gas
sands, by deriving expressions for the saturated bulk and shear moduli
and substituting into the regular equations for P and S-wave velocity:
The Biot-Gassmann Equations
)1()1( whcwwmsat SρSρρρ
32
drysat
In the Biot-Gassmann equations, the shear modulus does not change for
varying saturation at constant porosity. In equations:
33. The Biot-Gassmann Equations
To understand the Biot-Gassmann equations, let us update the figure we
saw earlier to include the concepts of the “saturated rock” (which includes
the in-situ fluid) and the “dry rock” (in which the fluid has been drained.)
Rock Matrix Pores and fluid
Dry rock
frame, or
skeleton
(pores
empty)
Saturated
Rock
(pores full)
33
34. 2
2
1
1
m
dry
mfl
m
dry
drysat
K
K
KK
K
K
KK
Mavko et al, in The Rock Physics Handbook, re-arranged the above
equation to give a more intuitive form:
)( flm
fl
drym
dry
satm
sat
KK
K
KK
K
KK
K
where sat = saturated rock, dry = dry frame, m = mineral, fl = fluid,
and = porosity.
(1)
(2)
The Biot-Gassmann bulk modulus equation is as follows:
Biot-Gassmann – Saturated Bulk Modulus
34
35. Biot’s Formulation
Biot defines b (the Biot coefficient) and M (the fluid modulus) as:
,
1
and,1
mflm
dry
KKMK
K b
b
Equation (1) then can be written as: MKK drysat
2
b
If b = 0 (or Kdry = Km) this equation simplifies to: drysat KK
If b = 1 (or Kdry= 0), this equation simplifies to:
mflsat KKK
11
Physically, b = 0 implies we have a non-porous rock, and b = 1 implies we
have particles in suspension (and the formula given is called Wood’s
formula). These are the two end members of a porous rock.
35
36. Ksandstone = 40 GPa,
Klimestone = 60 GPa.
We will now look at how to get estimates of the various bulk modulus
terms in the Biot-Gassmann equations, starting with the bulk modulus of
the solid rock matrix. Values will be given in gigaPascals (GPa), which
are equivalent to 1010 dynes/cm2.
The bulk modulus of the solid rock matrix, Km is usually taken from
published data that involved measurements on drill core samples.
Typical values are:
The Rock Matrix Bulk Modulus
36
37. hc
w
w
w
fl K
S
K
S
K
11
Equations for estimating the values of brine, gas, and oil bulk modulii are
given in Batzle and Wang, 1992, Seismic Properties of Pore Fluids,
Geophysics, 57, 1396-1408. Typical values are:
Kgas = 0.021 GPa, Koil = 0.79 GPa, Kw = 2.38 GPa
fl
w
hc
where the bulk modulus of the fluid,
the bulk modulus of the water,
and the bulk modulus of the hydrocarbon.
K
K
K
The fluid bulk modulus can be modeled using the following equation:
The Fluid Bulk Modulus
37
38. The key step in FRM is calculating a value of Kdry. This can be done in
several ways:
(1) For known VS and VP, Kdry can be calculated by first calculating Ksat
and then using Mavko’s equation (equation (2)), given earlier.
(2) For known VP, but unknown VS, Kdry can be estimated by:
(a) Assuming a known dry rock Poisson’s ratio dry. Equation (1) can
then be rewritten as a quadratic equation in which we solve for Kdry.
(b) Using the Greenberg-Castagna method, described later.
Estimating Kdry
38
39. In the next few slides, we will look at the computed responses for
both a gas-saturated sand and an oil-saturated sand using the
Biot-Gassmann equation.
We will look at the effect of saturation on both velocity (VP and VS)
and Poisson’s Ratio.
Keep in mind that this model assumes that the gas is uniformly
distributed in the fluid. Patchy saturation provides a different
function. (See Mavko et al: The Rock Physics Handbook.)
Data Examples
39
40. Velocity vs Saturation of Gas
Velocity vs Water Saturation - Gas Case
Sandstone with Phi = 33%, Density as previous figure for gas,
Kmatrix = 40 Gpa, Kdry = 3.25 GPa, Kw = 2.38 Gpa,
Kgas = 0.021 Gpa, Shear Modulus = 3.3. Gpa.
1000
1200
1400
1600
1800
2000
2200
2400
2600
0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1
Sw
Velocity(m/s)
Vp Vs
A plot of velocity vs water
saturation for a porous gas
sand using the Biot-Gassmann
equations with the parameters
shown.
In the section on AVO we will
model both the wet sand and
the 50% saturated gas sand.
Note that the velocity values
can be read off the plot and
are:
VPwet = 2500 m/s
VPgas = 2000 m/s
VSwet = 1250 m/s
VSgas = 1305 m/s
40
41. Poisson’s Ratio vs Saturation of Gas
Poisson's Ratio vs Water Saturation - Gas Case
Sandstone with Phi = 33%, Density as previous figure for gas,
Kmatrix = 40 Gpa, Kdry = 3.25 GPa, Kw = 2.38 Gpa,
Kgas = 0.021 Gpa, Shear Modulus = 3.3. Gpa.
0
0.1
0.2
0.3
0.4
0.5
0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1
Sw
Poisson'sRatio
A plot of Poisson’s ratio vs
water saturation for a porous
gas sand using the Biot-
Gassmann equations with the
parameters shown.
In the section on AVO we will
model both the wet sand and
the 50% saturated gas sand.
Note that the Poisson’s ratio
values can be read off the plot
and are:
wet = 0.33
gas = 0.12
41
42. Velocity vs Saturation of Oil
Velocity vs Water Saturation - Oil Case
Sandstone with Phi = 33%, Density as previous figure for oil,
Kmatrix = 40 Gpa, Kdry = 3.25 GPa, Kw = 2.38 Gpa,
Koil = 1.0 Gpa, Shear Modulus = 3.3. Gpa.
1000
1200
1400
1600
1800
2000
2200
2400
2600
0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1
Sw
Velocity(m/s)
Vp Vs
A plot of velocity vs water
saturation for a porous oil
sand using the Biot-
Gassmann equations with
the parameters shown.
Note that there is not much
of a velocity change.
However, this is for “dead”
oil, with no dissolved gas
bubbles, and most oil
reservoirs have some
percentage of dissolved
gas.
42
43. Poisson’s Ratio vs Saturation of Oil
Poisson's Ratio vs Water Saturation - Oil Case
Sandstone with Phi = 33%, Density as previous figure for oil,
Kmatrix = 40 Gpa, Kdry = 3.25 GPa, Kw = 2.38 Gpa,
Koil = 1.0 Gpa, Shear Modulus = 3.3. Gpa.
0
0.1
0.2
0.3
0.4
0.5
0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1
Sw
Poisson'sRatio
A plot of Poisson’s ratio vs
water saturation for a porous
oil sand using the Biot-
Gassmann equations with the
parameters shown.
Note that there is not much of
a Poisson’s ratio change.
However, again this is for
“dead” oil, with no dissolved
gas bubbles, and most oil
reservoirs have some
percentage of dissolved gas.
43
44. Fluid substitution in carbonates
In general carbonates are thought to have a smaller fluid sensitivity than
clastics. This is a consequence of the fact that they are typically stiffer (i.e.
have larger values of Km and Kdry ) implying a smaller Biot coefficient b and
hence fluid response.
This general observation is complicated by the fact that carbonates often
contain irregular pore shapes and geometries.
High aspect ratio pores make the rock more compliant and thus more
sensitive to fluid changes.
Aligned cracks require the use of the anisotropic Gassmann equation,
resulting in the saturated bulk modulus being directionally dependent.
Gassmann assumed that pore pressure remains constant during wave
propagation. If the geometry of the pores and cracks restrict the fluid
flow at seismic frequencies then the rock will appear stiffer.
All these factors make the application of the Biot-Gassmann fluid
substitution in carbonates more complex.
44
45. Kuster-Toksöz model
The Kuster-Toksöz model allows to estimate properties of the
rocks with ellipsoidal pores, filled up with any kind of fluid.
• The Kuster-Toksöz model was developed in 1974
• Based on ellipsoidal pore shape (Eshelby, 1957)
• Pore space described as a collection of pores of
different aspect ratios
a
b
Aspect Ratio α= b/a
Courtesy of A. Cheng(2009)
In the appendix, we show how to compute the Kuster-Toksöz
model values Tiijj and F.
48. 48
The Keys-Xu method
Keys and Xu (2002) give a method for computing the dry
rock moduli as a function of porosity, mineral moduli and
pore aspect ratio.
The equations are as follows, where p and q are functions
of the scalars given by Kuster and Toksöz (1974):
mineral.ofratioaspectandclay,ofratioaspect
before,as,
1
1
,
1
),(
5
1
,)(
3
1
where,)1(and)1(
21
21
2
1
2
1
aa
aa
clayclay
k
kk
k
kiijjk
q
m
p
mdry
V
f
V
f
FfqTfp
KK
49. 49
The Keys-Xu method
Here is a plot of the
results of the Keys
and Xu (2002)
method for the dry
rock bulk modulus:
50. When multiple pore fluids are present, Kfl is usually calculated by a Reuss
averaging technique (see Appendix 2):
Kfl vs Sw and Sg
0
0.5
1
1.5
2
2.5
3
0 0.25 0.5 0.75 1
Water saturation (fraction)
Bulkmodulus(Gpa)
This averaging
technique assumes
uniform fluid
distribution!
-Gas and liquid must
be evenly distributed
in every pore.
This method heavily biases compressibility of the combined fluid to
the most compressible phase.
g
g
o
o
w
w
fl K
S
K
S
K
S
K
1
Patchy Saturation
50
51. When patch sizes are large with respect to the seismic wavelength, Voigt
averaging (see Appendix 2) gives the best estimate of Kfl (Domenico, 1976):
When patch sizes are of intermediate size, Gassmann substitution should
be performed for each patch area and a volume average should be made.
This can be approximated by using a power-law averaging technique,
which we will not discuss here.
ggoowwfl KSKSKSK
When fluids are not uniformly mixed, effective modulus values cannot be
estimated from Reuss averaging. Uniform averaging of fluids does not
apply.
Patchy Saturation
51
53. SP VV
12
22
This will be illustrated in the next few slides.
Note that for a constant Poisson’s ratio, the intercept is zero:
smVV SP /136016.1
The mudrock line is a linear relationship between VP and VS
derived by Castagna et al (1985):
The Mudrock Line
53
58. Using the regression coefficients given above, Greenberg and Castagna
(1992) first propose that the shear-wave velocity for a brine-saturated rock
with mixed mineral components can be given as a Voigt-Reuss-Hill
average of the volume components of each mineral.
PS
PS
PPS
PS
VskmV
VskmV
VVskmV
VskmV
770.0/867.0:Shale
583.0/078.0:Dolomite
055.0017.1/031.1:Limestone
804.0/856.0:Sandstone
2
Greenberg and Castagna (1992) extended the previous mud-rock
line to different mineralogies as follows, where we have now
inverted the equation for VS as a function of VP:
The Greenberg-Castagna method
58
59. The rock physics template (RPT)
Ødegaard and Avseth
(2003) proposed a
technique they called the
rock physics template
(RPT), in which the fluid
and mineralogical
content of a reservoir
could be estimated on a
crossplot of Vp/Vs ratio
against acoustic
impedance, as shown
here.
from Ødegaard and Avseth (2003)
59
60. Ødegaard and Avseth (2003) compute Kdry and dry as a
function of porosity using Hertz-Mindlin (HM) contact
theory and the lower Hashin-Shtrikman bound.
Hertz-Mindlin contact theory assumes that the porous rock
can be modeled as a packing of identical spheres, and the
effective bulk and shear moduli are computed from:
member.-endporosityhighand
ratio,sPoisson'mineralgrain,percontacts
,modulusshearmineral,pressureconfining:where
,
)1(2
)1(3
)2(5
44
,
)1(18
)1( 3
1
22
2223
1
22
222
c
m
m
m
mc
m
m
eff
m
mc
eff
n
P
P
n
P
n
K
The rock physics template (RPT)
60
61. The lower Hashin-Shtrikman bound is then used to compute
the dry rock bulk and shear moduli as a function of porosity
with the following equations:
modulus.bulkmineraland
2
89
6
:where,
3
4/1/
3
4
)3/4(
/1
)3/4(
/
1
1
m
effeff
effeffeff
m
c
eff
c
dry
eff
effm
c
effeff
c
dry
K
K
K
z
z
zz
KK
K
Standard Gassmann theory is then used for the fluid
replacement process.
The rock physics template (RPT)
61
62. Here is the RPT for a range of porosities and water saturations, in a
clean sand case. We will build this template in the next exercise.
The rock physics template (RPT)
62
63. An understanding of rock physics is crucial for the
interpretation of AVO anomalies.
The volume average equation can be used to model
density in a water sand, but this equation does not
match observations for velocities in a gas sand.
The Biot-Gassmann equations match observations well
for unconsolidated gas sands.
When dealing with more complex porous media with
patchy saturation, or fracture type porosity (e.g.
carbonates), the Biot-Gassmann equations do not hold,
and we move to the Kuster-Toksöz approach.
The ARCO mudrock line is a good empirical tool for the
wet sands and shales.
Conclusions
63