Integration of Pressure-Transient Data in Modeling Tengiz Field, Kazakhstan—A New Way To Characterize Fractured Reservoirs
- Yan Pan (Chevron) | Mun-Hong Hui (Chevron ETC) | Wayne Narr (Chevron) | Gregory R King (Chevron) | Terrell Tankersley (Chevron) | Steve Jenkins (Tengizchevroil) | Eric Flodin (Chevron) | Phil Bateman (Chevron) | Chris Laidlaw (Chevron) | Hai Xuan Vo (Chevron)
- Document ID
- Society of Petroleum Engineers
- SPE Reservoir Evaluation & Engineering
- Publication Date
- January 2016
- Document Type
- Journal Paper
- 5 - 17
- 2016.Society of Petroleum Engineers
- Reserovir modeling, Tengiz Field, Pressure transient data, Dynamica data integration, Naturally fractured reservoirs
- 5 in the last 30 days
- 613 since 2007
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A systematic work-flow to integrate pressure-transient data collected from single-well buildup tests in numerical reservoir-simulation models for a fracture/matrix system is presented. The results of its application in a sector model in the southeast region of Tengiz field in Kazakhstan are also discussed. The procedure starts with a selected numerical-simulation model, either a discrete fracture/matrix (DFM) model or a dualporosity dual-permeability (DPDK) model, and follows with the analysis of a numerically generated buildup test to calculate the fracture spacing and shape factor of the model. Then, following the correlations between pressure-transient-analysis results and the average or representative values of the model-input parameters near the well, which contain the previously obtained fracture spacing and shape factor, the numerical-model parameters are adjusted in each iteration to match the pressure-transient behavior observed in the buildup test including the interporosity flow between matrix and fracture and the radial flow in the total system. Before field application, the numerical-simulation results from both DFM and DPDK models were validated against analytical pressure-transient solutions for a dual-porosity system. The gridding and time-steps were calibrated to reproduce the analytical transient behavior. Finally, the new work-flow was applied to a sector model of Tengiz field in the southeast region focusing on two wells. Following the developed work-flow, a DFM model was constructed, and its fracture and matrix properties were adjusted to honor buildup-test data at both wells and the transient data collected during a pulse test conducted between them. The study results show that the key factors of a DFM model on buildup transient response are the fracture permeability, fracture aperture, and matrix permeability in the well-drainage area, and the dominant parameters on pulse-test response are the fracture permeability and matrix porosity in the influence area between the two wells. Using the correlations quantitatively for each simulation step could reduce the total number of iterations needed to converge to the numerical solution. The modified model also generated flow distribution along the wellbore, consistent with production-logging data at one well. The resulting sector map of pressure change during buildup test indicates the area with well connected fracture network. Dynamic transient data contain rich information about reservoirs, and the effective integration of dynamic and static data would have a big impact on reservoir management by potentially minimizing the number of wells to be drilled, maximizing the production, and optimizing recovery. The novelty of this study is the quantitative use of the correlations between pressure-transient-analysis results and the representative values of the input parameters in a numerical model to reduce the number of simulation iterations. Its application in Tengiz is also one of the rare examples in which single-well and multiple-well transient data, production logging, and image-log data are all available.
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