Modeling interwell fracture interference and Huff-n-Puff pressure containment in Eagle Ford using EDFM

Shale field operators have vested a tremendous interest in optimal spacing of infill wells and further fracture optimization, which ideally should have as little interference with the existing wells as possible. Although proper modeling has been employed to show the existence of well interference, few models have forecasted the impact of multiple inter-well fractures on child wells production and also implemented Huff-n-Puff and injection containment methods. These prognoses of the reservoir simulations abet to optimize further hydraulic fracture designs and improve the efficiency of Enhanced Oil Recovery (EOR) in unconventional reservoirs. This thesis presented a rigorous workflow for estimating the impacts of spatial variations in fracture conductivity and complexity on fracture geometries of inter-well interference when modeling EOR Huff-n-Puff. Furthermore, we applied a non-intrusive embedded discrete fracture modeling (EDFM) method in conjunction with a commercial reservoir simulator to investigate the impact of well interference through connecting fractures by multi-well history matching, to propose profitable opportunities for Huff-n-Puff application. In this sense, the value of our workflow relies on a robust understanding of fracture properties, real production data validation, and the add-on feature of multi-pad wellbore image logging interpretation in the process. First, according to updated production data from Eagle Ford, the model was constructed to perform four (parent) wells history matching including five inner (child) wells. Later, fracture diagnostic results from well image logging were employed to perform sensitivity analysis on properties of long interwell connecting fractures such as number, conductivity, geometry, and explore their impacts on history matching. However, the estimation of these inter-well connecting fractures which were employed for enhanced history matching varied significantly from unmeasured fracture sensitivities. Finally, optimal cluster spacing was recommended considering interwell interference. The obtained results lead our study to the implementation of Huff-n-Puff models that capture inter-well interference seen in the field and their affordable impact sensitivities focused on variable injection rates/locations and multi-point water injection to mimic pressure barriers. The simulation results strengthen the understanding of modeling complex fracture geometries with robust history matching and support the need to incorporate containment strategies when EOR Huff-n-Puff is implemented. Moreover, the simulation outcomes show that well interference is present and reduces effectiveness of the fracture hits when connecting natural fractures. As a result of the inter-well long fractures, the bottom hole pressure behavior of the parent wells tends to equalize, and the pressure does not recover fast enough. Furthermore, the EDFM application is strongly supported by complex fracture propagation interpretation from image logs through the child wells in the reservoir. Through this study, multiple containment scenarios were proposed to contain the pressure in the area of interest, considering more than 2000 hydraulic fractures. The model became a valuable stencil to inform the impacts on well location and spacing, the completion staging, initial huff-n-puff decisions, and subsequent containment strategies (e.g. to improve cycle timing and efficiency), so that it can be expanded to other areas of the field. The simulation results and understandings afforded have been applied to the field satisfactorily to support significant reductions in offset fracture interference by up to 50% and reduce completion costs up to 23% while improving new well capital efficiency. Consequently, these outcomes support pressure containment benefits that lead to increased pressure build, reduced gas communication, reduced offset shut-in volumes, and ultimately, improvements in net utilization and capital efficiency