Comprehensive Optimization Methodology for Stimulation Design of Low-Permeability Unconventional Gas Reservoirs
- Srimoyee Bhattacharya (University of Houston) | Michael Nikolaou (University of Houston)
- Document ID
- Society of Petroleum Engineers
- SPE Journal
- Publication Date
- June 2016
- Document Type
- Journal Paper
- 947 - 964
- 2016.Society of Petroleum Engineers
- Unconventional resources, Shale gas, Tight gas, Hydraulic fracturing, Optimization
- 2 in the last 30 days
- 592 since 2007
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Over the past decade, multiple-fracture horizontal wells (MFHWs) have proved successful in recovering oil and particularly gas from very-low-permeability reservoirs. For MFHW planning and design, it is important to be able to make decisions on several variables, such as number of wells, number of fractures per well, amount and type of proppant per fracture, fracture dimensions (length, width, and height), and possibly others. Standard practice for making such decisions is mostly empirical. However, empiricism may not be as successful for new cases that are significantly different from old ones. In such cases, what-if analysis is used by combining intuition with numerical simulators to assess the outcomes of possible decisions. Even though this approach may produce feasible results, it is unlikely that it leads to optimal decisions because of the complexity of the problem. Therefore, a systematic methodology is needed for MFHW planning and design that produces optimal solutions efficiently and effectively.
In this work, we develop such a methodology that optimizes net present value (NPV). The methodology poses the design problem as nested optimization in which the outer-optimization shell involves decisions on the number of wells, number of fractures per well, and amount of proppant, whereas the inner optimization maximizes the productivity index (PI) by selecting optimal fracture dimensions. The proposed methodology integrates in a systematic way a fracture-design module, a production-estimation module, and an economics module. Because the methodology is automated and numerically efficient, one can use it effectively for field development.
A case study is used to illustrate the applicability of the proposed methodology, and suggestions are made for further improvements.
|File Size||2 MB||Number of Pages||18|
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