Application of Nonlinear Probability Models to Mature Infill Risk Assessments and Opportunity Screening

Summary This paper discusses a comprehensive infill risk assessment framework and opportunities screening procedure devised and applied to the decision-making considerations for extending the field life of a mature oilfield. Within the risk assessment framework, the paper describes the definition of nonlinear probability models (based on the probit model specification), and the application of the probit models towards enhancing the infill risk assessment and opportunities screening activity. Enhancement through a robust and quantitative routine is imperative to accurately capture the inherent complexities, nonlinearities and interdependencies of subsurface conditions, risks, uncertainties, and economic viability. To elucidate on the workflows, risk assessment design considerations, and key results, the case of a mature offshore carbonate field under strong aquifer drive is presented. For this field, the risk assessment framework allowed for better decision making in the screening and selection of suitable infill candidates. Similarly, the approach made it possible to promptly identify and recommend robust risk mitigation strategies relevant to the selected infill opportunities (with respect to completion and well type considerations). Clearly, there is value in this sort of approach because optimal infill decisions are the ones that maximize the oil recovery at realistic cost, even in the presence of anticipated risk events.