Diagnostic fracture injection testing (DFIT) is an extremely popular technique to generate direct estimates of some of the key characteristics of shale reservoirs. DFIT analysis is generally done using analytical models traditionally developed for highpermeability reservoirs. The use of DFIT to analyze tight shale reservoirs introduces additional issues regarding applicability of these techniques for tight systems as well as operational issues such as long well shut-in times to obtain reasonable reservoir parameters. In this work we conduct geomechanics coupled reservoir flow simulations in order to forward model and analyze DFITs for tight shale gas reservoirs. This capability greatly enhances our ability to efficiently design the DFITs for tight shale reservoirs. In this work we simulate a typical DFIT using a geomechanics coupled reservoir flow simulator and generate the pre-closure and after-closure pressure response from the flow simulation model. This response is then analyzed using a standard Nolte pre-closure and after-closure analysis technique with an objective to evaluate the reservoir properties. We not only we show the validity of the Nolte analysis technique for tight rocks but we also provide guidelines on the amount of shutin time required to generate a reasonable estimate of the reservoir properties from DFIT pressure response. We also show that the geomechanics coupled flow simulation of DFIT can provide estimates on fracture dimensions which compare reasonably with those given by more traditional fracture design tools. We demonstrate that the geomechanics coupled reservoir flow simulation provides an additional advantage over traditional fracture design tools in that it can numerically model the system response even after fracture closure.

In recent years, liquid rich shale plays have become the focus of many operators developing unconventional resources. After years of drilling single wells in a section to hold leases, companies are facing key field development questions – what is the appropriate well spacing and what is the right development plan for their unconventional assets? Some operators have simply used a trial and error approach while others have designed and drilled pilots to test various well spacing scenarios and multiple field development strategies following an experimental design approach. Both of these methods could take significant time before conclusive results could be observed, and these field trials often involve significant capital investment to test a few combinations with the hope of inferring the optimal solution. Another key question many operators have is how does the optimal well spacing change with fluid type or with shale play? Liquid rich shale plays like Eagle Ford, Utica and Duvernay show multiple fluid gradients. Depending on which fluids a company's acreage contains, the optimal well spacing will vary as will the development plans. Therefore, it is very important to understand the effect of fluid composition on recovery and well spacing in liquid rich shale plays. In this work, a reservoir flow simulation model is built and history matched to a synthetic liquid rich shale well production history in order to predict the estimated ultimate recovery (EUR) for various well spacing scenarios. The flow simulation model incorporates dominant shale flow and storage mechanisms including multi-phase physics. Using the calibrated simulation model, a study was performed to quantify the reduction in EUR due to well interference and sensitivities to fluid composition were conducted to understand its effects on well productivity and recovery factor. Results indicate that the outlined workflow provides a reliable tool for performance evaluation of various field development strategies and that well performance and fluid composition can have a significant impact on well spacing and field development decisions.