A Practical Solution to Capture Subsurface Complexity to Match Production Performance at Field F Off the Coast of Sarawak, Offshore Malaysia

Abstract After several years of production, a discrepancy existed between network model and field performance at gas field Field F. Further investigations indicated the volume was still intact and there was no surface issue, indicating a possible need to deviate from the current simple material balance model for reservoir performance analysis. The objectives of this paper are to discuss the analysis done to ascertain the root cause of the discrepancy as well as the proposed solution. Subsurface and surface endeavors were conducted to achieve the objectives: Updating the dynamic model as well as RTA with the latest production data to confirm the volume range. Analysing past pressure and production data, as well as performing field production testing, to investigate a possible backpressure issue. Acquiring new field data such as MRT, PBU and SGS for formation damage investigation and reservoir pressure data analysis. Reconciling solution points between well model and tank model. From dynamic modelling as well as RTA updated using the latest production data, it was confirmed that the volume of Field F was still within the same range as the previous subsurface understanding. At the same time, from historical pressure and production data analysis, as well as production testing at Field F and nearby Field N sharing the same hub facility, it was demonstrated that there was no backpressure issue. From the new MRT, PBU and SGS data acquired, it could be deduced that there was no formation damage at the wells to have caused the discrepancy. The ensuing information from the data acquisition efforts revealed that the reservoir pressure might have different outlooks that could lead to different GIIP assessments from the previous subsurface understanding. Reconciling solution points between well model and tank model by employing the IPR dP shift would not be technically justifiable unless a smaller GIIP was used. Competing observations from the analyses conducted seemed to point to replacing the material balance model used in the network model with a dynamic model, which would erode the simplicity of the reservoir performance analysis, especially in a hub environment. Retaining a simple material balance model, however, was possible by acknowledging the subsurface complexity, going back to basics and considering another possible subsurface understanding. An alternative numerical PTA showed the possibility of two different zones of differing drainage rates but still connected, supported by petrophysical evidence. A two-tank MBAL model using P* which respected both subsurface and surface perspectives backed by static and dynamic data became a practical solution to capture the subsurface complexity to match the production performance at Field F.