We invite you to take part in the SEG, EAGE, AAPG, joint session. The session will take place on Tuesday, March 27, 2007 in the Conference Hall of “MSU Science Park”. Time: 7:00 p.m.
We invite you to take part in the SEG, EAGE, AAPG, joint session. The session will take place on Tuesday, March 27, 2007 in the Conference Hall of “MSU Science Park”. Time: 7:00 p.m.
Context and author bio
Reservoir quality prediction is a fundamental part of any field development or exploration program. Increasingly deep, overpressured and tight reservoir targets require careful modeling of diagenesis, fluid properties and timing of migration to successfully identify permeable reservoirs. In the last decade, significant advances have been made at both the field and reservoir scale in reservoir quality prediction. Rick Tobin is a recognized industry leader in this field.
TNK-BP is pleased to sponsor this important presentation.
Rick Tobin is a senior geologist with the BP Exploration and Production Technology Group in Houston, specializing in diagenesis and reservoir quality prediction. He received geology degrees from James Madison University (B.S., 1977) and from the University of Cincinnati (M.S. 1980, Ph.D. 1982). His technical specialties and current research interests include sedimentology, sedimentary petrology, fluid inclusion microthermometry, diagenesis, and reservoir quality modeling. Tobin is an active member of AAPG, SEPM, and Sigma Xi.
Abstract:
In the petroleum industry, reservoir quality (RQ) studies are focused on the prediction of primary depositional texture, secondary burial diagenesis, and the resulting effects on mineralogy, texture, and pore system characteristics. RQ work provides critical solutions to common business problems associated with both pre-drill exploration (e.g., reserve calculations and flow rate estimates), as well as post-drill development and appraisal (e.g., rock/log/seismic calibration, pay definition, reservoir compartmentalization, facies trends, and formation sensitivity). Given recent industry trends towards deep, diagenetically altered reservoir targets, RQ predictions have become a critical component of reservoir risk analysis and have lead to a number of recent deep drilling successes.
The RQ technology discipline has evolved substantially over the past few decades. Early qualitative forecasts were followed by quantitative predictions using simple empirical trends of porosity and permeability with depth. In some cases, empirical correlations of porosity with other variables like Time Temperature Index (TTI) and vitrinite reflectance (VR) have been used. In the 1990’s, experimentally-derived compaction curves for variety of sandstone facies types were developed. These curves, along with the development of some new analytical techniques provided the necessary impetus for the development of new modeling tools in the late 1990’s. These tools included mass balance chemical modeling approaches along with diagenetic modeling software. The net effect has been a fundamental step change from routine reservoir rock description to more rigorous, high-resolution descriptions geared towards predictive numeric modeling.
The most widely used commercial RQ modeling software includes 1D models (ExemplarTM, TouchstoneTM), and 2D / 3D models (TmapTM). These programs are being used by industry to predictively model RQ attributes in a variety of basins worldwide. The resulting predictions provide the necessary data used to build reservoir quality risk maps and 3D visualizations, and are being applied to play fairway analysis, prospect prediction, and appraisal through development applications.
Future directions for this rapidly evolving technology area will likely include increased emphasis on production and field development applications, along with testing the limits of model applicability in HTHP (High Temperature High Pressure) and tight gas settings. Model performance improvements will likely focus on expansion of reservoir rock properties being modeled (e.g., geophysical, mechanical and electric rock properties), potential integration of chemical modeling applications with existing diagenetic models, and improved understanding of the effects of water saturation on cement kinetics.
