This document discusses using 3D seismic attributes to improve characterization of karst-modified carbonate reservoirs. It describes how karst features like collapse structures, polygonal patterns, and oriented lineaments can impact reservoirs. Multi-trace attributes like coherence, dip/azimuth, and curvature can help identify subtle karst features not evident on standard seismic. A workflow is proposed using attributes, geology, and production data to better understand karst overprints and compartmentalization. The approach is demonstrated on examples from the Central Kansas Uplift and Fort Worth Basin.
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.
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.
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.
Enhancement of geological features in the Fort Worth Basin by the application...Lorenzo Izarra
The main objective of this study is to apply spectral decomposition (SD) and spectral inversion (SI) as seismic attributes to enhance stratigraphic and structural elements on a 3D seismic data located in Fort Worth basin.
By applying these techniques it is possible to improve the vertical resolution of seismic data to better understand the characteristics on this region, and to define geological elements that cannot be seen in conventional seismic data. SD and SI contributed to a more precise interpretation and characterization (mapping, layer thickness determination, and stratigraphic visualization) of reservoirs plays along the stratigraphic column.
Spectral decomposition and spectral inversion contributed to a more precise interpretation and characterization of reservoirs plays along the stratigraphic column.
Spectral decomposition was performed using constrained least-squares spectral analysis (CLSAA), which has better temporal resolution than both the Fourier Transform (FT) and the Continuous Wavelet Transform (CWT).
The spectral inversion was accomplished by inverting the time-frequency analysis for a sparse-layer reflectivity series.
Conclusions
- These methods provided higher resolution images of geological features than conventional seismic data had done, and improved identification and delineation of this features that are important for production of unconventional gas.
- Visualization was improved using RGB overlays of the spectral decomposition data and by the application of coherence attributes to the spectral inversion results.
- Using these high resolution spectral methods, vertical resolution was improved from 115 ft. to 50 ft.
The oxford dictionary defines an attribute as, “a quality ascribed to any person or thing”. We have extended this definition to: “seismic attributes are all the information obtained from seismic data, either by direct measurements or by logical or experience based reasoning
In reflection seismology : aseismic attributes is a quality extracted or derived from seismic data that can be analyzed in order to enhance information that might be more subtle in a traditional seismic image , leading to a better geological or geophysical interpretation of the data
Over the past decades, we have witnessed attribute developments track breakthroughs in reflector acquisition and mapping, fault identification, bright spot identification, frequency loss, thin bed tuning, seismic stratigraphy.
Brief review on Direct hydrocarbon indicators (DHI).
The presentation is a part from Seismic data interpretation course that i teach for undergraduates.
The sources are indicated in the references list.
Contact me via: hatem_refaat95@hotmail.com
This is for student of geophysics who want to know about basic of multi component seismic. For further detail or any query you can drop me mail, my mail id id bprasad461@gmail.com
The analysis of all of the significant processes that formed a basin and deformed its sedimentary fill from basin-scale processes (e.g., plate tectonics)
to centimeter-scale processes (e.g., fracturing)
Unconventional seismic interpretations using seismic attributes workshop usin...mohamed Shihata
This five day Unconventional Seismic Interpretation Course is designed for E&P professionals and aims to provide essential knowledge on visualization, integration, and interpretation techniques that have been recently developed for seismic data. This course assumes an advanced knowledge of seismic interpretation and concentrates on the role of the seismic attributes in the search for oil and gas.
Course Objectives:
By the end of this course delegates will learn about:
• To acquire skills in interpretation of 3-D seismic data using seismic attributes
• Effective using new seismic interpretation techniques (geobodies extraction, multiattributes, hybrid attributes)
• To enhance theoretical knowledge of seismic structural interpretation, stratigraphic interpretation, reservoir identification and evaluation, and horizon and formation attributes
• Be familiar with seismic interpretations software
Skype: self tranning
Facebook: https://www.facebook.com/Initiative.Courses
Mail: selftrainning@gmail.com
Phone: +201120828201 -01201141235
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.
Enhancement of geological features in the Fort Worth Basin by the application...Lorenzo Izarra
The main objective of this study is to apply spectral decomposition (SD) and spectral inversion (SI) as seismic attributes to enhance stratigraphic and structural elements on a 3D seismic data located in Fort Worth basin.
By applying these techniques it is possible to improve the vertical resolution of seismic data to better understand the characteristics on this region, and to define geological elements that cannot be seen in conventional seismic data. SD and SI contributed to a more precise interpretation and characterization (mapping, layer thickness determination, and stratigraphic visualization) of reservoirs plays along the stratigraphic column.
Spectral decomposition and spectral inversion contributed to a more precise interpretation and characterization of reservoirs plays along the stratigraphic column.
Spectral decomposition was performed using constrained least-squares spectral analysis (CLSAA), which has better temporal resolution than both the Fourier Transform (FT) and the Continuous Wavelet Transform (CWT).
The spectral inversion was accomplished by inverting the time-frequency analysis for a sparse-layer reflectivity series.
Conclusions
- These methods provided higher resolution images of geological features than conventional seismic data had done, and improved identification and delineation of this features that are important for production of unconventional gas.
- Visualization was improved using RGB overlays of the spectral decomposition data and by the application of coherence attributes to the spectral inversion results.
- Using these high resolution spectral methods, vertical resolution was improved from 115 ft. to 50 ft.
The oxford dictionary defines an attribute as, “a quality ascribed to any person or thing”. We have extended this definition to: “seismic attributes are all the information obtained from seismic data, either by direct measurements or by logical or experience based reasoning
In reflection seismology : aseismic attributes is a quality extracted or derived from seismic data that can be analyzed in order to enhance information that might be more subtle in a traditional seismic image , leading to a better geological or geophysical interpretation of the data
Over the past decades, we have witnessed attribute developments track breakthroughs in reflector acquisition and mapping, fault identification, bright spot identification, frequency loss, thin bed tuning, seismic stratigraphy.
Brief review on Direct hydrocarbon indicators (DHI).
The presentation is a part from Seismic data interpretation course that i teach for undergraduates.
The sources are indicated in the references list.
Contact me via: hatem_refaat95@hotmail.com
This is for student of geophysics who want to know about basic of multi component seismic. For further detail or any query you can drop me mail, my mail id id bprasad461@gmail.com
The analysis of all of the significant processes that formed a basin and deformed its sedimentary fill from basin-scale processes (e.g., plate tectonics)
to centimeter-scale processes (e.g., fracturing)
Unconventional seismic interpretations using seismic attributes workshop usin...mohamed Shihata
This five day Unconventional Seismic Interpretation Course is designed for E&P professionals and aims to provide essential knowledge on visualization, integration, and interpretation techniques that have been recently developed for seismic data. This course assumes an advanced knowledge of seismic interpretation and concentrates on the role of the seismic attributes in the search for oil and gas.
Course Objectives:
By the end of this course delegates will learn about:
• To acquire skills in interpretation of 3-D seismic data using seismic attributes
• Effective using new seismic interpretation techniques (geobodies extraction, multiattributes, hybrid attributes)
• To enhance theoretical knowledge of seismic structural interpretation, stratigraphic interpretation, reservoir identification and evaluation, and horizon and formation attributes
• Be familiar with seismic interpretations software
Skype: self tranning
Facebook: https://www.facebook.com/Initiative.Courses
Mail: selftrainning@gmail.com
Phone: +201120828201 -01201141235
GraphRAG is All You need? LLM & Knowledge GraphGuy Korland
Guy Korland, CEO and Co-founder of FalkorDB, will review two articles on the integration of language models with knowledge graphs.
1. Unifying Large Language Models and Knowledge Graphs: A Roadmap.
https://arxiv.org/abs/2306.08302
2. Microsoft Research's GraphRAG paper and a review paper on various uses of knowledge graphs:
https://www.microsoft.com/en-us/research/blog/graphrag-unlocking-llm-discovery-on-narrative-private-data/
State of ICS and IoT Cyber Threat Landscape Report 2024 previewPrayukth K V
The IoT and OT threat landscape report has been prepared by the Threat Research Team at Sectrio using data from Sectrio, cyber threat intelligence farming facilities spread across over 85 cities around the world. In addition, Sectrio also runs AI-based advanced threat and payload engagement facilities that serve as sinks to attract and engage sophisticated threat actors, and newer malware including new variants and latent threats that are at an earlier stage of development.
The latest edition of the OT/ICS and IoT security Threat Landscape Report 2024 also covers:
State of global ICS asset and network exposure
Sectoral targets and attacks as well as the cost of ransom
Global APT activity, AI usage, actor and tactic profiles, and implications
Rise in volumes of AI-powered cyberattacks
Major cyber events in 2024
Malware and malicious payload trends
Cyberattack types and targets
Vulnerability exploit attempts on CVEs
Attacks on counties – USA
Expansion of bot farms – how, where, and why
In-depth analysis of the cyber threat landscape across North America, South America, Europe, APAC, and the Middle East
Why are attacks on smart factories rising?
Cyber risk predictions
Axis of attacks – Europe
Systemic attacks in the Middle East
Download the full report from here:
https://sectrio.com/resources/ot-threat-landscape-reports/sectrio-releases-ot-ics-and-iot-security-threat-landscape-report-2024/
Accelerate your Kubernetes clusters with Varnish CachingThijs Feryn
A presentation about the usage and availability of Varnish on Kubernetes. This talk explores the capabilities of Varnish caching and shows how to use the Varnish Helm chart to deploy it to Kubernetes.
This presentation was delivered at K8SUG Singapore. See https://feryn.eu/presentations/accelerate-your-kubernetes-clusters-with-varnish-caching-k8sug-singapore-28-2024 for more details.
Key Trends Shaping the Future of Infrastructure.pdfCheryl Hung
Keynote at DIGIT West Expo, Glasgow on 29 May 2024.
Cheryl Hung, ochery.com
Sr Director, Infrastructure Ecosystem, Arm.
The key trends across hardware, cloud and open-source; exploring how these areas are likely to mature and develop over the short and long-term, and then considering how organisations can position themselves to adapt and thrive.
Neuro-symbolic is not enough, we need neuro-*semantic*Frank van Harmelen
Neuro-symbolic (NeSy) AI is on the rise. However, simply machine learning on just any symbolic structure is not sufficient to really harvest the gains of NeSy. These will only be gained when the symbolic structures have an actual semantics. I give an operational definition of semantics as “predictable inference”.
All of this illustrated with link prediction over knowledge graphs, but the argument is general.
UiPath Test Automation using UiPath Test Suite series, part 4DianaGray10
Welcome to UiPath Test Automation using UiPath Test Suite series part 4. In this session, we will cover Test Manager overview along with SAP heatmap.
The UiPath Test Manager overview with SAP heatmap webinar offers a concise yet comprehensive exploration of the role of a Test Manager within SAP environments, coupled with the utilization of heatmaps for effective testing strategies.
Participants will gain insights into the responsibilities, challenges, and best practices associated with test management in SAP projects. Additionally, the webinar delves into the significance of heatmaps as a visual aid for identifying testing priorities, areas of risk, and resource allocation within SAP landscapes. Through this session, attendees can expect to enhance their understanding of test management principles while learning practical approaches to optimize testing processes in SAP environments using heatmap visualization techniques
What will you get from this session?
1. Insights into SAP testing best practices
2. Heatmap utilization for testing
3. Optimization of testing processes
4. Demo
Topics covered:
Execution from the test manager
Orchestrator execution result
Defect reporting
SAP heatmap example with demo
Speaker:
Deepak Rai, Automation Practice Lead, Boundaryless Group and UiPath MVP
Software Delivery At the Speed of AI: Inflectra Invests In AI-Powered QualityInflectra
In this insightful webinar, Inflectra explores how artificial intelligence (AI) is transforming software development and testing. Discover how AI-powered tools are revolutionizing every stage of the software development lifecycle (SDLC), from design and prototyping to testing, deployment, and monitoring.
Learn about:
• The Future of Testing: How AI is shifting testing towards verification, analysis, and higher-level skills, while reducing repetitive tasks.
• Test Automation: How AI-powered test case generation, optimization, and self-healing tests are making testing more efficient and effective.
• Visual Testing: Explore the emerging capabilities of AI in visual testing and how it's set to revolutionize UI verification.
• Inflectra's AI Solutions: See demonstrations of Inflectra's cutting-edge AI tools like the ChatGPT plugin and Azure Open AI platform, designed to streamline your testing process.
Whether you're a developer, tester, or QA professional, this webinar will give you valuable insights into how AI is shaping the future of software delivery.
Let's dive deeper into the world of ODC! Ricardo Alves (OutSystems) will join us to tell all about the new Data Fabric. After that, Sezen de Bruijn (OutSystems) will get into the details on how to best design a sturdy architecture within ODC.
1. Improving Reservoir Characterization
of Karst-Modified Reservoirs
with 3-D Geometric Seismic Attributes
Susan E. Nissen1, E. Charlotte Sullivan2,
Kurt J. Marfurt3, and Timothy R. Carr4
1
Consultant, McLouth, KS
Pacific Northwest National Labs, Richland, WA
2
College of Earth and Energy, University of Oklahoma, Norman, OK
3
4
Department of Geology and Geography, West Virginia University,
Morgantown, WV
2. Outline
• Characteristics of karst-modified reservoirs
• Multi-trace geometric seismic attributes
• Seismic-based examples of
• Collapse structures
• Polygonal features
• Oriented lineaments
• Interpretation workflow for karst-modified
reservoirs
• Conclusions
3. Karst Modified Reservoirs
• Carbonate reservoirs
• Rocks modified by dissolution during
subaerial exposure
• May also have hydrothermal and tectonic
overprints
4. Examples of karst features that can affect
reservoir performance
Collapse features Residual Solution-enlarged
• Compartmentalize paleo-highs fractures
reservoir • May be hydro- • Fluid conduits (if
• Affect deposition carbon traps open) or barriers
of overlying strata (if filled)
Loess-filled fractures, Missouri
Cockpit karst, Jamaica
Cave collapse facies in image log www.cockpitcountry.com
Ft. Worth Basin, Texas
5. Interpretation of Karst Features
• Well data alone is insufficient for identifying the
spatial extent and distribution of local karst features.
• Karst features with substantial vertical relief can be
readily identified using 3-D seismic.
• Critical features relating to reservoir character are
often subtle and not readily detected using standard
3-D seismic interpretation methods.
• Multi-trace geometric seismic attributes can help!
6. Multi-Trace Geometric Seismic Attributes
• Calculated using multiple input seismic traces
and a small vertical analysis window
• The analysis "box" moves throughout the entire
data volume => attributes can be output as a 3-
D volume
• Provide quantitative information about lateral
variations in the seismic data
7. Multi-Trace Geometric Seismic Attributes
• Coherence - A measure of the trace-to-trace similarity of
the seismic waveform
Reference Trace
• Dip/azimuth - Numerical
estimation of the Instantaneous dip =
Dip with highest
instantaneous dip and coherence
azimuth of reflectors
Dips
tested
• Curvature – A measure of the Positive
Curvature
bending of a surface (~2nd Cu Zer
rv o
atu
Zero
Curvature
derivative of the surface)
re
Negative
Anticline Curvature
Di
p
X Pl pin R Flat
an g
e
Syncline
Z Curvature (k)=1/R After Roberts, 2001
8. Mid Continent examples
Central Kansas Uplift
Ord. Arbuckle
- Collapse structures
Mississippian - Polygonal features
- Oriented lineaments
Ft. Worth Basin
Ord. Ellenburger
9. Collapse Features – Fort Worth Basin
vertical seismic section
Pennsylvanian Caddo • Collapse features
are visible as
depressions on the
~2600 ft 3-D seismic profile
Collapse features
• Collapse features
extend from the
Ellenburger through
Pennsylvanian
strata
Ordovician Ellenburger
10. Attribute time slices near the Ellenburger
Amplitude Coherence
fault
N
Dip/Azimuth Most Negative Curvature
W E
Collapse
S
features
3 mi
11. Collapse features line up at the intersections
of negative curvature lineaments
Coherence Most Negative Curvature
Time = 1.2 s
1 mi
12. Polygonal Features
Ordovician Arbuckle Ordovician Ellenburger
Kansas Fort Worth Basin
1 mi 1 mi
1 mi
1.6 km 1.6 km
1.6 km
Diameters ~700-900 ft Diameters ~1400-1600 ft Diameters ~1200 -3500 ft
Vertical relief generally 2 ms (~15 ft) or less
13. Cockpit
Cockpits
karst Arbuckle Polygonal Karst
-- Cockpit Karst
(After Cansler and Carr, 2001)
doline
cone
1 m i
1 .6 k m
Morphological map Arbuckle structure overlain
Arbuckle time structure with paleotopographic
of karst area in New
overlain by most positive divides in Barton Co., KS
Guinea (Williams,
curvature (Cansler, 2000)
1972)
14. Ellenburger polygonal karst
- tectonic collapse structures
Collapse feature Faults
at topographic high
Collapse Features Coincide with
Deep Basement Faults
N
Ellenburger
Basement
15. Oriented lineaments -- Kansas Mississippian
Lineament trend vs.
oil/water production
14 100
90
12
5 year water production (x104 Bbl)
5 year oil production (x104 Bbl)
80
10
70
60
8
50
6
40
30
4
20
2
10
0 0
0 100 200 300 400 500 600 700 800 0 100 200 300 400 500 600 700 800
distance to NE lineament (ft) distance to NE lineament (ft)
14 100
90
12
5 year water production (x10 Bbl)
5 year oil production (x104 Bbl)
80
4
10
70
60
8
50
6
40
4 30
20
2
10
0 0
0 100 200 300 400 500 600 700 800 0 100 200 300 400 500 600 700 800
0.5 mile distance to NW lineament (ft) distance to NW lineament (ft)
16. Workflow for Identification of Karst Overprints
Using Multi-Trace Attributes
Interpret features relating to
Extract attributes structure, geomorphology,
Volumetric
along horizon and reservoir architecture
attributes
or time slice on attribute slices
Identify dominant karst
Predict general production
Horizon geomorphology (e.g., polygonal
performance based on
picks karst vs. groundwater-sapped
type of karst overprint
plateaus)
Core and Separate subaerial karst Identify areas of
log data from tectonic overprint enhanced or occluded
porosity/permeability
Measure distance from
oriented lineaments.
Outline potential reservoir
Production Identify preferred orientations compartment boundaries
data of fluid conduits vs. barriers (fluid barriers)
17. Conclusions
• Coherence, dip/azimuth, and curvature
extractions are valuable for establishing seismic
geomorphology
• Different attributes reveal different details about
karst features
• A workflow utilizing multi-trace attributes, along
with geologic and production information, can
improve characterization of karst-modified
carbonate reservoirs
18. Acknowledgements
Devon Energy
Grand Mesa Operating Company
John O. Farmer, Inc.
Murfin Drilling Company
IHS - geoPLUS Corporation
Seismic Micro-Technology, Inc.
U. S. Department of Energy
Petroleum Research Fund
State of Texas ATP
Kansas Geological Survey, University of Kansas
University of Houston
Editor's Notes
We will look at examples of the application of volumetric seismic attributes to three areas An Ordovician Ellenburger aquifer in the Fort Worth Basin, north Texas . An Ordovician Arbuckle reservoir in Kansas And a Mississippian reservoir in Kansas
Vertical cross section from a 3-D survey in the Fort Worth Basin of north Texas. Here, collapse features extend from the Ordovician Ellenburger carbonates through Mississippian and Pennsylvanian shales, siltstones, and limestones- a vertical distance of about 2600 ft.
Different attributes show different information about the collapse features Coherence better at showing features than conventional amplitude slice Dip/azimuth shows that they are depressions, sense of motion on faults Volumetric curvature shows more detailed, somewhat polygonal features not evident on the other attributes
Comparison of polygonal features in Kansas Arbuckle and Fort Worth Basin Ellenburger.
A horizon structure map of the Arbuckle surface from a 3D seismic survey in Kansas shows approximately 100 ft (30 m) of local relief, with northwest to southeast-trending ridges. Individual cones and dolines can be seen, some with diameters <1000 ft (300 m). Most Positive curvature extracted along the Arbuckle horizon shows a network of polygonal features with average diameters of approximately 750 ft (230 m). Most of these features have no apparent relief on the seismic structure map. This seismic geomorphic landscape is reminiscent of polygonal or cockpit karst, as described by Williams (1972). Polygonal karst forms in uplifted low-relief strata that have been fissured by a system of joints. Stream sinks are initiated at locations of maximum fracturing. Scattered small depressions expand and capture smaller neighbors until the entire surface is occupied by adjoining polygonal depressions. Polygonal karst has been identified by Cansler and Carr (2001) on the Arbuckle erosional surface elsewhere in Kansas using well data. In their study area, dolines are up to 250 ft (75 m) deep and are localized in areas as wide as 1 mile (1.6 km). Typically, they are 10-60 ft deep (3-20 m) with diameters of 1000-2000 ft (300-600 m). Cansler and Carr (2001) concluded that it is likely that the surface is pitted with a large number of smaller dolines that are too small in area to delineate with well spacing or < 10 ft (3 m) in depth. We appear to be imaging just such features with our seismic curvature map.
Polygonal geomorphology, similar to the cockpit karst identified in the Kansas Arbuckle, is also seen on the surface of the Ordovician Ellenburger horizon in the Fort Worth Basin. Most negative curvature time slices near the Ellenburger show polygonal geometry and corresponding coherence slices show circular collapse features that line up at the intersection of curvature lineaments. However, when we examine the 3D visualization of coherence extracted along the top of the Ellenburger, we see that the collapse features occur near the tops of topographic highs, as well as at valley heads and that the rims of the “cockpits” are rather wide. Although the presence of subaerial karst is well established in the Ellenburger by the presence of cavern collapse facies in conventional cores, this karst forms a pervasive background and is not limited to areas of the large collapse features. Many of the collapse features coincide with deep basement faults, or occur along Pennsylvanian age fractures and small faults. In addition, dolomite and native copper cements in fracture fill indicate flow of burial fluids. These lines of evidence indicate that the polygonal geomorphology and extensive collapse features in the Fort Worth basin data set are more likely controlled by tectonic processes than subaerial weathering. Implications from these studies are that tectonic and subaerial karst processes may be linked, with subaerial karst forming at intersections of tectonic joints. Reactivation of zones of weakness allows migration of fluids (meteoric and hydrothermal) along the same vertical pathways through time.
In a Mississippian reservoir in central Kansas that is subjacent to a pre-Pennsylvanian unconformity and karst surface, lineaments in the long wavelength Most Negative curvature volume, extracted along a horizon corresponding to the base of the aquifer supporting the reservoir, are correlated with fluid production in the reservoir. These lineaments are dominated by two orthogonal directions (northeast and northwest), which line up with regional structural trends. Wells situated near northeasterly oriented lineaments have lower oil production and a thicker basal conglomerate above the unconformity surface than do wells more distant from the northeasterly trending lineaments. The presence of rotated blocks of dolomite and green shale in cores is suggestive of low permeability debris fill. The northeasterly trending lineaments may relate to a high concentration of shale-filled fractures that either degrade the quality of the limestone reservoir or serve as compartment boundaries. Proximity to northwesterly trending lineaments correlates with higher water production, but has no relationship with oil production, suggesting that northwesterly trending lineaments correspond to open fractures that connect directly to the underlying aquifer.