A Novel Approach to History Matching and Optimization of Shale Completions and EUR - A Case Study of Eagle Ford Well

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Abstract Many operators have used in the past various methods to analyze and optimize the horizontal well (HW) completions in the Eagle Ford play with varied results. Typically, such methods focus on different parts of this complex problem in relative isolation and as a consequence do not utilize all available data simultaneously. This paper presents a simulation-based method for analyzing the problem in an integrated fashion by modeling the fracturing and Stimulated Reservoir Volume (SRV) creation process, followed by well cleanup and production. Consequently, all available data are used to constrain the history match (HM), resulting in a more reliable tool for optimization. In this work, the authors developed a comprehensive integrated model of a typical Eagle Ford well in the Dimmit County. The HM process showed that injection and production scenarios must be modeled in tandem to get better insights into the flow physics rather than simulating them separately. The best accuracy is obtained when the real sequence of fracturing is modeled. It was found that only a fraction of the created fracture and SRV lengths contribute to production. Whereas fracture half-lengths of ~250 ft were generated during injection, only about ¼ of fracture and ¾ of SRV contributed. Effect of completion efficiency was also investigated. It was shown that the assumption of only 2 perforation clusters per stage is not plausible while assuming some other scenarios offers good HM and prediction very similar to uniform efficiency. Optimization work considered several scenarios. Cases with larger cluster/stage spacing with the same pumped volume are not desirable. However, the use of double the cluster spacing gives slightly higher estimated ultimate recovery in 30 years, and could offer significant completion cost savings. Use of current injection volumes and current well spacing (500 ft) leaves significant reservoir volume undrained, which is a target for well spacing optimization. Pressure (as opposed to stress) dependent permeability functions adequately capture the permeability variation both for injection and production. The work shows how the integrated reservoir/fracturing/geomechanics modeling can be used to optimize completions and EUR for shale wells.

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