A State-of-the-Art Literature Review on Capacitance Resistance Models for Reservoir Characterization and Performance Forecasting

Rafael Wanderley de Holanda, Eduardo Gildin, Jerry L. Jensen, Larry W. Lake and C. Shah Kabir
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Rafael Wanderley de Holanda: Petroleum Engineering Department, Texas A&M University, College Station, TX 77843-3116, USA
Eduardo Gildin: Petroleum Engineering Department, Texas A&M University, College Station, TX 77843-3116, USA
Jerry L. Jensen: Chemical and Petroleum Engineering Department, University of Calgary, Calgary, AB T2N-1N4, Canada
Larry W. Lake: Department of Petroleum and Geosystems Engineering, University of Texas, Austin, TX 78712-1585, USA
C. Shah Kabir: Department of Petroleum Engineering, University of Houston, Houston, TX 77204-0945, USA

Energies, 2018, vol. 11, issue 12, 1-45

Abstract: Capacitance resistance models (CRMs) comprise a family of material balance reservoir models that have been applied to primary, secondary and tertiary recovery processes. CRMs predict well flow rates based solely on previously observed production and injection rates, and producers’ bottomhole pressures (BHPs); i.e., a geological model and rock/fluid properties are not required. CRMs can accelerate the learning curve of the geological analysis by providing interwell connectivity maps to corroborate features such as sealing faults and channels, as well as diagnostic plots to determine sweep efficiency and reservoir compartmentalization. Additionally, it is possible to compute oil and water rates by coupling a fractional flow model to CRMs which enables, for example, optimization of injected fluids allocation in mature fields. This literature review covers the spectrum of the CRM theory and conventional reservoir field applications, critically discussing their advantages and limitations, and recommending potential improvements. This review is timely because over the last decade there has been a significant increase in the number of publications in this subject; however, a paper dedicated to summarize them has not yet been presented.

Keywords: capacitance-resistance model; reservoir modeling; material balance; waterflooding; enhanced oil recovery (search for similar items in EconPapers)
JEL-codes: Q Q0 Q4 Q40 Q41 Q42 Q43 Q47 Q48 Q49 (search for similar items in EconPapers)
Date: 2018
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (4)

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