Historically the evaluation of unconventional reservoirs dominantly relied on analytical methods like Decline Curve Analysis (DCA) and Rate Transient Analysis (RTA). Although they are effective and convenient, the lack of fundamental understanding such as fracture geometry leads to high uncertainties in analysis and consequently challenges in improving the accuracy of forecast or explaining the production mechanism.

A geomechanical integrated reservoir modeling approach is developed to precisely tackle this limitation. Because of the extremely low permeability and widely utilized horizontal drilling with multiple hydraulic fracture design, a conventional modeling approach could not be adopted directly without the critical addition of geomechanical workflow. The complete approach includes 1) Geomodelling 2) RTA and hydraulic fracture modeling 3) graphic processing unit (GPU) based reservoir simulations and 4) Poro-elastic impacts on stress modeling. The change of each portion will impact the whole, therefore a workflow with fewer tools and iterations greatly benefits the efficiency of the methodology. A single tool including fracture modeling and dual-porosity simulation were deployed and successfully demonstrated the power of this process in business operation.

A few field examples are used to demonstrate this approach. They include the history matching (HM), optimization of completion and spacing strategy for 1) a dry gas field 2) a black oil field and 3) a workflow for new entry field with almost no data. The lack of lab measurements (such as SCAL, k, sigma) are common and the assumptions used are elaborated. It is important to recognize simulation uncertainties, So the hypothesis has tested by utilizing modeling design from pilot wells.

Although almost everyone in the industry recognizes the importance of integrated modeling, practical application has been very challenging. The coupling of geomechanics and reservoir simulation typically not only requires extremely long cycle times to deliver, but also relies on significant computational power. Therefore, analysis of different realizations is generally not feasible, and appropriate uncertainties are not captured. The presented approach illustrated as an integrated method using one tool which successfully reduced the cycle time of pad level modeling to weeks, therefore improved the efficiency of reservoir engineers significantly.

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