Abstract

The current state-of-the-technology for the analysis of reservoir performance data (i.e., the analysis of well test and production data) provides us with extraordinary tools for characterizing reservoir properties—hence, the term performance-based reservoir characterization.  This lecture presents a historical development and current status of reservoir performance analysis, along with the theory and application of the “modeling-based analysis” techniques for production and well-test performance.  Moreover, the lecture not only offers insight into the integration of reservoir performance analysis with geological and petrophysical data, but also gives us guidance into how such data types should be compared/correlated.

This lecture will also address the problem of data quality and data relevance since reservoir performance analysis has evolved to the point where the capabilities of the software tools often significantly exceed the quality of the data being analyzed (i.e., the various channels of time, rate, and pressure data obtained for a well or reservoir).

The future challenges for performance-based reservoir characterizations will be less focused on analytical models (which often have limiting theoretical and data constraints), but rather will emphasize numerical-modeling aspects.  Although the development has historically been less rigorous mathematically, simplified analytical approaches (and even empirical relations) afford us safeguards against unconstrained analyses.  Consequently, we must recognize that such simplified analyses are relevant in any future scenarios for developing integrated, performance-based reservoir characterizations using multiple technologies.  The future of performance-based reservoir characterization will include improved analytical and semianalytical reservoir models—but most importantly, we will place emphasis on numerical modeling, particularly for data integration.

Biography

Thomas A. Blasingame is an Associate Professor and holder of the Robert L. Whiting Professorship in the Department of Petroleum Engineering at Texas A&M University. He also serves as a petroleum consultant to several operating companies and service providers.  Dr. Blasingame holds BS, MS, and PhD degrees in petroleum engineering, and he has served as a faculty member at Texas A&M University for 14 years.  He has authored more than 60 papers, supervised more than 40 graduate research theses, and he performed major field studies involving geology, petrophysics, and engineering tasks.  Dr. Blasingame devotes much of his academic teaching and research work towards petrophysics, reservoir engineering, the analysis and interpretation of well performance, and technical mathematics—as well as individual well performance case studies and large integrated field studies.  He has been a Distinguished Member of the Society of Petroleum Engineers since 2000.