Development Plan Optimization and Uncertainty Study in a Major Deepwater Field in the US Gulf of Mexico

Abstract

Abstract This paper describes the development plan optimization and probabilistic uncertainty study using Latin Hypercube Experimental design constrained to production performance in Lower Miocene (LM) reservoirs of the Shenzi Field in deepwater Gulf of Mexico (DW GOM). The purpose of the development plan optimization was to identify, rank, and characterize future development opportunities i.e. infills and injectors in the LM reservoirs to arrest the field decline. The study uses history matched dynamic simulation models. Uncertainty parameters were identified and ranked through single variate sensitivity analysis with consideration of impact on history match quality. Top ranking uncertainty parameters were then characterized using probability distribution functions. Latin Hypercube Experimental design was then used to generate vectors of uncertainty parameters to be used in running many simulation cases. The simulation results from experimental design were filtered based on history match quality to 200 cases, a more manageable number for visualization and further simulation study. The 200 cases were then used to identify development opportunities and characterize their resource range. Identification and proper characterization of uncertainty parameters were essential to attain reliable estimates of resource range and opportunity ranking, and for gaining insights into the downside risks of each development opportunity. This is especially the case for scenario-based uncertainty parameters with discrete distributions e.g., geologic scenarios. Application of simple data analytics techniques and powerful visualization tools was important in thoroughly analyzing the results of many simulation cases, understanding key uncertainty parameters and interdependencies for each development opportunity. For most opportunities the incremental Estimated Ultimate Recoveries (EURs) calculated from the reference case model were optimistic compared to the P50 incremental EUR from the uncertainty study, highlighting the risks involved in making development decisions based on only reference case model results. A two well development concept with the minimum downside resource risk was identified. This was the case because the incremental EUR from the two wells was strongly correlated to a key uncertainty parameter but with opposite signs, thus reducing the downside resource risk. Development plan optimization and ranking of development opportunities were performed using hundreds of history-matched simulation cases to properly capture the subsurface uncertainties in the estimated resource range for each opportunity. This methodology resulted in identifying development concepts with minimum low case resource risk and largest mid case resource.