An improved interwell connectivity model to obtain interwell connectivity information by using complex well data. (February 2021)

• Record Type: Journal Article
• Authors: Liu, Shun; Cao, Lin; He, Heng; Yang, Tao; Zhou, De-sheng
• Is Part Of: Simulation. Volume 97:Number 2(2021)
• Page Start: 135
• Page End: 143
• Publication Date: 2021-02
• Subjects: Interwell connectivity -- Bayesian theory -- projection gradient -- history matching; Computer simulation -- Periodicals; 003.3
• DOI: 10.1177/0037549719846368
• Languages: English
• ISSNs: 0037-5497

Abstract

Information on interwell connectivity is important in reservoir field dynamic analysis. However, all conventional methods, such as the tracer test, interference well test, and numerical simulation, have disadvantages. These disadvantages include the length of time taken, high costs, and the effect on oilfield production. Thus, research focus has been directed toward the development of approaches that use production and injection data to obtain interwell connectivity data. Prevailing interwell connectivity models are sensitive to shut-ins, and their corresponding inversion methods are unreliable. The improved interwell connectivity model presented in this study exhibits enhanced robustness to shut-ins. The application of seepage theories and numerical simulation methods enables the main model parameters to absorb prior geological knowledge to characterize the reservoir and improve the initial estimate of connectivity. Corresponding inverse methods for model parameters are implemented based on Bayesian inverse theory and the projection gradient method and obtain greater robustness for the model parameter, compared with those in previous studies. Testing of a heterogeneous synthetic reservoir and a Z16 reservoir block demonstrates that the methodology can precisely determine the interwell connectivity and can be used in real oilfields.