Scenario-Based Pore Pressure Prediction to Reduce Drilling Risks, Examples From the Sarawak Asset, North West Borneo, Malaysia

Abstract

Pore-pressure prediction in a mature hydrocarbon province with producing fields bears issues different from an exploration or immature basin setting. Appraisal and production activities can introduce anadditional set of complications that needs to be considered to make well-constrained pore-pressurepredictions. Problems for infill drilling can arise from severe changes in rock strength (fracture gradientreduction), caused by depletion of reservoirs through production, or development drilling in neighboringfields, if there is pressure communication via a common aquifer. Increases above initial pressure can be caused by crossflow from overpressured reservoir layers through poor cement bonds or abandonments. Reservoirs can also receive additional pressure through water or gas injection. The Luconia gas province is a mature basin and several stages of successful exploration, appraisal, development and infill-drilling campaigns. Shell, supported by its partners, has successfully overcome the above mentioned issues by thorough and innovative pore-pressure prediction approaches. In addition to the standard bracketing of uncertainties, 3 key process elements are employed:proper framing of the pore-pressure prediction and continued interfaces with all stakeholders anda 'scenario-based'prediction approach, that captures all possible effects caused by appraisal and production of the target reservoir or neighboring fields, and that predicts their impact on the pore pressure of the reservoir to be drilled.Risks identified are captured and mitigated via a 5 point pore-pressure prediction that spans a facilities design range as well as a wider drilling range. The drilling-range end members have a low probability of occurring, but have to be captured to enable hardware selection that ensures safe drilling execution. State of the art technologies are employed to achieve this, including 4D seismic, regional databases, innovative modeling methodologies and full integration in a well-delivery process.