Interwell Connectivity and Diagnosis Using Correlation of Production and Injection Rate Data in Hydrocarbon Production

摘要

This report details progress on inferring interwell communication from well rate fluctuations. Starting with the procedure of Albertoni and Lake (2003) as a foundation, the goal of the project is to develop further procedures to infer reservoir properties through weights derived from correlations between injection and production rates. A modified method, described in Jensen et al. (2005) and Yousef et al. (2005), and herein referred to as the ''capacitance model'', produces two quantities, {lambda} and {tau}, for each injector-producer well pair. We have focused on the following items: (1) Approaches to integrate {lambda} and {tau} to improve connectivity evaluations. Interpretations have been developed using Lorenz-style and log-log plots to assess heterogeneity. Testing shows the interpretations can identify whether interwell connectivity is controlled by flow through fractures, high-permeability layers, or due to partial completion of wells. Applications to the South Wasson and North Buck Draw Fields show promising results. (2) Optimization of waterflood injection rates using the capacitance model and a power law relationship for watercut to maximize economic return. Initial tests using simulated data and a range of oil prices show the approach is working. (3) Spectral analysis of injection and production data to estimate interwell connectivity and to assess the effects of near-wellbore gas on the results. Development of methods and analysis are ongoing. (4) Investigation of methods to increase the robustness of the capacitance method. These methods include revising the solution method to simultaneously estimate {lambda} and {tau} for each well pair. This approach allows for further constraints to be imposed during the computation, such as limiting {tau} to a range of values defined by the sampling interval and duration of the field data. This work is proceeding. Further work on this project includes the following: (1) Refinement and testing of the waterflood optimization process, including optimization on more complex situations e.g., time effects on revenue and water injection and disposal costs. (2) Completion of the spectral-based analysis and determination of the effects of near-wellbore gas on the results. (3) Revision of the capacitance model procedures to provide more robust results which are insensitive to the initial estimates of {tau} needed in the nonlinear regression.