Formulating Smart Proxy Models for a Mature Asset’s Production Forecasting Under Uncertainty

Summary This paper discusses the main framework, development considerations and key results of smart proxy models formulated for quantifying uncertainties in production forecasts for a mature asset’s re-development requirements. Specifically, the models have been derived to promptly evaluate and subsequently account for the impact of new surveillance learnings (RST logging data) on the future re-development well planning. With the approach, uncertainties in production forecasts for future redevelopment wells are quickly re-assessed, each time new surveillance data is acquired. The results from the re-assessments are then incorporated into well planning discussions, thereby facilitating rapid decision making about reservoir management and field re-development planning, or further de-risking requirements, as appropriate. To highlight the main aspects, a case of mature asset in advanced stages of FEED is described. For this scenario, revision of prior production expectations (established at the concept select phase) was necessitated as more information was subsequently gathered through new drilling, logging and other measurements. Effectively integrating the proxy evaluation methodology and results into the asset’s well prognosis technical discussions, allowed for faster and more informed decision-making on re-development well planning. Ultimately, this provided strong and structured support for meeting the field life extension project production expectations, including considerations for risk mitigation.