De-Risking Subsurface Uncertainties in Static Model Workflow for Ngimbang Carbonate Build-Up in Recently Discovered Field Located in North Madura II Block, Indonesia

Abstract

EJ-7 field is a green field located about 65 km NE of Surabaya in the offshore Northeast Java Basin in water depth of about 25m. EJ-7 was drilled and tested oil in Ngimbang Carbonate. There was no wireline logging data acquired successfully from the reservoir as the operation encountered total losses. Although the reservoirs are generally of good quality, it remains a challenge to capture the uncertainties in the static model due to the limited information available, especially from wells and seismic data. The integration of log data, geology and geophysical (G&G) interpretation and pressure analysis are the key factors to comprehend and to reduce the uncertainties, especially in fluid contact definition, which will give significant impact to resource estimation. Detail static modeling techniques and methodologies were applied to address and mitigate the uncertainties in EJ-7 Field. Valuable information from logs, seismic, regional sedimentology study and pressure analysis were integrated into the static model. The robust workflow was designed to capture the subsurface uncertainties, adopting the latest machine learning and a prudent selection of P10, P50 and P90 scenarios. Ultimately, the probable property maps of P90, P50 and P10 were utilized for forecasting as input to the numerical flow simulation to model the dynamic behavior of the reservoir, optimize the number of well count for development, and calculate the overall project economic value. Moreover, a seamless collaborative work with a third-party study also provided more constructive work to mitigate all the uncertainties through optimizing the well locations and the development concept for EJ-7 Field.