Shale Gas Well Production Optimization using Modified RTA Method - Prediction of the Life of a Well

Baek, Seunghwan (Texas A&M University) | Akkutlu, I. Yucel (Texas A&M University) | Lu, Baoping (Sinopec Research Institute for Petroleum Engineering) | Ding, Shidong (Sinopec Research Institute for Petroleum Engineering) | Xia, Wenwu (Harding Shelton Petroleum Engineering & Technology Limited)

OnePetro 

Abstract

Routine history-matching and reservoir calibration methods for horizontal wells with multiple hydraulic fractures are complex. Calibration of important fracture and matrix quantities is, however, essential to understand the reservoir and estimate the future recoveries. In this paper, we propose a robust method of simulation-based history-matching and reserve prediction by incorporating an analytical solution of production Rate Transient Analysis (RTA) as an added constraint. The analytical solution gives the fracture surface area contributing to the drainage of the fluids from the matrix into the fractures. The surface area obtained from the RTA is the effective area associated with the production—not total area. It is the most fundamental and the most significant quantity in the optimization problem. Differential evolution (DE) algorithm and a multi-scale shale gas reservoir flow simulator are used during the optimization. We show that the RTA-based optimization predicts the quantities related to completion design significantly better. Further, we show how the estimated total fracture surface area can be used to measure the hydraulic fracturing quality index, as an indication of the quality of the well completion operation. The most importantly, we predict that the fractures under closure stress begin to close much sooner (100 days) than the prediction without the RTA-based fracture surface area constraint. The deformation continues under constant closure stress for about 20 years, when the fractures are closed nearly completely. This work attempts to use the traditional reservoir optimization technologies to predict not only the reserve but also the life of the unconventional well.