Integrated Reservoir Modeling
|Prof. Dr Michael Poppelreiter (University Technology Petronas, Perak, Malaysia)|
|Geophysics – Integrated Geophysics|
|15 CPD points|
3D CARBONATES CORRELATION GEOSTATISTICS INTEGRATION RESERVOIR CHARACTERIZATION WELL LOG
This outcrop-based course provides participants with an overview of the integrated reservoir modeling process, tools and tasks. The data set is from a Tertiary carbonate reservoir. It exposes participants to hands-on integrated reservoir modeling.
A conceptual reservoir model and a digital reservoir model are constructed on paper and digitally. Common sedimentological techniques such as section logging, gamma ray measurements and interpretation of aspect ratios from photo panels and maps will be demonstrated and practiced.
All data required to build models are actual industry data. The uncertainty of all data sets is assessed. Alternative models are constructed.
QC of data versus interpretation is an integral part of the course. A strong emphasis is put on stratigraphic correlation framework and structural model building. Property modeling and volumetrics are carried out interactively as a team exercise. Team interaction is a fundamental component of this course.
Upon completion of the course, participants will be familiar with:
- Reservoir modeling workflow;
- Structural model building;
- Construction of a stratigraphic framework;
- Acquisition and modeling of reservoir body dimensions on a regional and local scale;
- Acquisition, measurement and application of petrophysical properties;
- Integration of data at different scales: thin sections, cores, outcrop panels, petrophysical data and regional geological information depositional system of Tertiary age;
- Well exposed and exceptionally well-studied on a local and a regional scale.
- Review of statistical analysis and probability
- Part 1: Sources of uncertainty in geophysics and reservoir modeling
- Part 2: Modeling uncertainty in seismic reservoir characterization
- Part 3: Geostatistics and spatial uncertainty
- Part 4: Uncertainty and data integration
- Part 5: Structural uncertainty
- Part 6: Uncertainty in reservoir dynamic modeling
- Part 7: Visualizing uncertainty
- Part 8: Value of Information and decision making
The course is designed for geologists, geophysicists, engineers, petrophysicists or others involved in reservoir modeling.
Participants should have knowledge of geology and petrophysics. Students are expected to have a clear understanding of how to use Petrel software as well as some comprehension of the principles of geology and log analysis.
About the instructor
Prof. Dr Michael C. Poppelreiter, Director of the South East Asian Carbonate Research Lab (SEACaRL), Shell Chair in Petroleum Geology at the Department of Geosciences, Universiti Teknologi PETRONAS (UTP).
Area of expertise: Shell Subject Matter Expert for carbonate geology, Outcrop and Regional Geological Studies (focus Middle East), Conceptual Modelling, Reservoir Modelling and 3D Digital Modelling, Project management, CO2 in carbonate, Technical Assurance & Capability (TA-2), 25 publications and 2 books on borehole image logs and reservoir geology.
Participants are recommended to read before attending the course Kerans and Tinker (1997), SEPM Short Course Note 40.
Explore other courses under this discipline:
Instructor: Dr Kurt Marfurt (University of Oklahoma)
Seismic data are incredibly rich in information, including amplitude, frequency, and the configuration or morphology of reflection events. Seismic attributes, including volumetric estimates of coherence, dip/azimuth, curvature, amplitude texture, and spectral decomposition, can greatly accelerate the interpretation of newly acquired 3D surveys as well as provide new insight into old 3D surveys.
Instructor: Dr Leo Eisner (Seismik)
The goal of this class is to explain principles of microseismic monitoring ranging from single monitoring borehole to surface and near surface networks. This class focuses on understanding the measurements made in passive seismic, their use and their uncertainties. Attendees should be able to decide on the best type of microseismic monitoring, design it, and know what kind of processing is needed to achieve their goals. They will also understand the uncertainties in the microseismicity. They will be able to avoid interpretation of uncertain observations. No requirement on prior class is needed, although knowledge of hydraulic fracturing and seismology helps. The course will also discuss the latest developments in microseismicity from source mechanisms, through tomography and anisotropy to reservoir simulations, including pore pressure analysis. The course discusses also social and scientific aspects of (induced) seismicity related to oil and gas reservoir.
Instructor: Dr Enru Liu (ExxonMobil)
The ability to identify fracture clusters and corridors and their prevalent directions within many carbonates and unconventional resources (shale gas, tight gas and tight oil reservoirs) can have a significant impact on field development planning as well as on the placement of individual wells. The characterization of natural fractures is difficult and cannot be achieved by any single discipline or single measurement. Geophysics can identify spatial distributions of fractures and fracture corridors between wells and seismically-derived fracture information to complement (not compete with) other measurements, such as outcrops, core, FMI, cross-dipole and other fracture information. This course is an introduction to the fundamental concepts of seismic fracture characterization by introducing seismic anisotropy, equivalent-medium representation theories of fractured rock and methodologies for extracting fracture parameters from seismic data. With a focus on practical applications, three case studies are presented to demonstrate the applicability, workflow and limitations of this technology: a physical laboratory 3D experiment where fracture distributions are known, a Middle East fractured carbonate reservoir and a fractured tight gas reservoir.
Instructor: Dr Sagar Ronghe (DownUnder GeoSolutions)
The course discusses reservoir characterisation through the integration of wireline and seismic data as applicable to all stages of oil and gas field activity: from reconnaissance, through exploration and appraisal, to focused reservoir characterisation during field development. Techniques presented include amplitude and AVA interpretations, stack rotations, deterministic and stochastic inversion, probabilistic interpretations of lithology and fluid distributions, and quantification of reservoir properties including prediction uncertainty. The importance of petrophysics and rock physics calibration as a foundation to all of these methods is highlighted. The course also discusses the calibration of seismic velocities to well data for accurate time-to-depth conversion.
Instructor: Mr Olav Inge Barkved (Petoro)
Time-lapse seismic surveys or 4D seismic provide snapshots of a producing hydrocarbon reservoir and its surroundings. The benefit of the technology in monitoring fluid and pressure changes and to point out bypassed oil or un-drained compartments has been well documented over the last 10–15 years. Still the technology is undergoing rapid development. This course will provide some context on what is driving the dynamic changes linked to producing a hydrocarbon reservoir and what we should expect to observe using seismic technologies in a varied geological setting. It will address key issues that impact the feasibility of time-lapse seismic and evaluate established methods. However, the focus will be on ‘new’ technologies, use of a permanent array, frequent seismic surveying and integration of the data. Examples from the Valhall field will be used extensively to illustrate the potential of seismic data and to articulate issues related to interpretation and integration. This will include data examples from marine towed 4D, frequent surveying using permanently installed sensors, in-well recordings and analysis of passive data, including micro seismicity. Use of seismic surveillance information to support reservoir management, new well delivery and base management will be a central part of the presentation.
Instructor: Dr Anthony Fogg (Arun Geoscience)
AVO (Amplitude Versus Offset) analysis has been a key technology for derisking drill targets as it can potentially distinguish different fluids and lithotypes. Over time the application of the AVO technique has evolved and merged with seismic inversion methods so that today the traditional AVO analysis techniques have been superseded by the analysis of rock property volumes on the interpreter's work station. However, in order to derive these rock properties we still rely on the fundamental principles of AVO. This course covers the basics of AVO theory and how it is used to create attributes or inversion volumes from seismic reflection data that reveal the rock and fluid characteristics of the sub-surface. The course is not mathematical, but does review some simple equations that help the student understand how AVO is applied to create quantitative measurements from surface seismic data and interpret those results in terms of rock physics - often referred to as Quantitative Interpretation (QI).
Instructor: Prof. Martin Landrø (Norwegian University of Science & Technology)
The course discusses various methods for monitoring subsurface injection of CO2. Specifically, the following topics will be covered:
- Rock physics related to injection of CO2 into porous rock
- Time-lapse seismic methods
- Gravity and electromagnetic methods
- Saturation and pressure effects
- Early detection of leakage
- Mapping overburden geology and identification of potential weakness zones
- Field examples
- Well integrity issues
- Using gas leakage as a proxy to study potential leakage of CO2
- Laboratory experiments of CO2 flooding including acoustic measurements
Instructor: Prof. Serge Shapiro (Freie Universitaet Berlin)
Stimulations of rocks by fluid injections (e.g., hydraulic fracturing) belong to a standard reservoir-development practice. Productions of shale oil, - shale gas, - heavy oil, - geothermal energy require broad applications of this technology. The fact that fluid injection causes seismicity (including microseismicity and, sometimes, significant induced earthquakes) has been well-established for several decades. Waste water injection into rocks, large-scale water reservoir constructions and underground carbon sequestrations are other examples of potentially seismogenic fluid impact on geologic structures. Understanding and monitoring of fluid-induced seismicity is necessary for hydraulic characterization of reservoirs, for assessments of reservoir stimulation results and for controlling seismic risk of fluid injections and production. The course provides systematic quantitative rock-physical and geomechanical fundamentals of all these aspects of the fluid-induced seismicity.
Instructor: Dr Philippe Doyen (Independent Consultant)
Three-dimensional numerical earth models play an increasingly important role in the petroleum industry to improve reservoir management and optimize hydrocarbon recovery. A key challenge for reservoir geoscientists is the quantitative integration of 3D and 4D seismic data into static and dynamic earth modeling workflows. Using a combination of theory and illustrations from real field studies, this two-day course reviews best practices and challenges for constraining earth models with seismic information and quantifying subsurface uncertainty.
Instructor: Dr Dario Grana (University of Wyoming)
Integrated reservoir modeling workflows provide a set of techniques to create three-dimensional numerical earth models in terms of elastic, petrophysical and dynamic properties of the rocks at different time steps during exploration and production. The course focuses on the quantification of uncertainty in the data, in the physical models and in the predictions in reservoir modeling workflows. Topics include uncertainty quantification in seismic reservoir modeling, geostatistical reservoir simulations, fluid flow modeling, and reservoir monitoring. The link between uncertainty quantification and decision-making will be introduced through decision-making theory. The course will include demonstrations of the methodologies on real case applications.