TY - JOUR
T1 - Using a segregated flow model to forecast production of oil, gas, and water in shale oil plays
AU - Male, Frank
N1 - Funding Information:
The author would like to thank the Alfred P. Sloan Foundation for funding much of this research as part of the project “The Role of Shale Oil in the U.S. Energy Transition.” Funding also came from the State of Texas Advanced Resource Recovery (STARR) project and the Bureau of Economic Geology’s Tight Oil Resource Assessment industrial associates program. Production data was extracted from the IHS Markit Enerdeq database, licensed to the Bureau of Economic Geology. Ian Duncan, Robin Dommisse, Larry Lake, and Michael Marder provided insights and helpful discussions about the research.
Publisher Copyright:
© 2019 Elsevier B.V.
PY - 2019/9
Y1 - 2019/9
N2 - Application of a segregated-flow assumption to a physics-based flow model simplifies decline analysis for multi-phase fluid production. The segregated flow model assumes that, during production, oil and water can be treated as taking different flow paths from the matrix to the hydrofracture network. This simplifies forecasting production of both the oil and water phases. Subsurface and reservoir property data for horizontal fractured wells are limited. As a consequence, attempts to estimate decline curves and ultimate recoveries utilizing full-physics, multiphase reservoir simulations are poorly constrained. In contrast, robust production forecasts can be made using a simple, physics-based model based on scaling laws. In this study, analysis of production decline has been carried out on 10,000 Permian basin, 12,000 Bakken and Three Forks, and 10,000 Eagle Ford oil wells. Additionally, 5000 Eagle Ford and 1000 Permian shale gas wells were analyzed. The approach enables estimation of the time to boundary-dominated flow and drainage volume for each well. In addition, the ultimate recoveries of oil, gas, and water were estimated. These can be used to compare wells drilled using different technologies or in different formations, plays, and geographic locations. Physics-based, segregated-flow models are broadly applicable to analysis of production from tight oil reservoirs. Empirical observations show that flow can be treated as segregated, where water and oil follow independent paths to the wellbore. Therefore, this model can be used to perform reliable, fast, automated decline analysis for tight oil fields.
AB - Application of a segregated-flow assumption to a physics-based flow model simplifies decline analysis for multi-phase fluid production. The segregated flow model assumes that, during production, oil and water can be treated as taking different flow paths from the matrix to the hydrofracture network. This simplifies forecasting production of both the oil and water phases. Subsurface and reservoir property data for horizontal fractured wells are limited. As a consequence, attempts to estimate decline curves and ultimate recoveries utilizing full-physics, multiphase reservoir simulations are poorly constrained. In contrast, robust production forecasts can be made using a simple, physics-based model based on scaling laws. In this study, analysis of production decline has been carried out on 10,000 Permian basin, 12,000 Bakken and Three Forks, and 10,000 Eagle Ford oil wells. Additionally, 5000 Eagle Ford and 1000 Permian shale gas wells were analyzed. The approach enables estimation of the time to boundary-dominated flow and drainage volume for each well. In addition, the ultimate recoveries of oil, gas, and water were estimated. These can be used to compare wells drilled using different technologies or in different formations, plays, and geographic locations. Physics-based, segregated-flow models are broadly applicable to analysis of production from tight oil reservoirs. Empirical observations show that flow can be treated as segregated, where water and oil follow independent paths to the wellbore. Therefore, this model can be used to perform reliable, fast, automated decline analysis for tight oil fields.
UR - https://www.scopus.com/pages/publications/85065727812
UR - https://www.scopus.com/pages/publications/85065727812#tab=citedBy
U2 - 10.1016/j.petrol.2019.05.010
DO - 10.1016/j.petrol.2019.05.010
M3 - Article
AN - SCOPUS:85065727812
SN - 0920-4105
VL - 180
SP - 48
EP - 61
JO - Journal of Petroleum Science and Engineering
JF - Journal of Petroleum Science and Engineering
ER -