Subsurface Integration Leading to Improved History Matching: Case Study Using Malaysian Heterogeneous Carbonate Gas Field

Abstract

Abstract It is well known that some of the carbonate fields in Central Luconia Gas Province, Sarawak, Malaysia, are subjected to severe geological heterogeneities and aquifer behavior. These are not usually well understood and captured during the initial field development study. This could potentially result in unreliable estimation of the hydrocarbon in place and estimated recovery factor as well as selected depletion and production strategies. The studied field in this work, which is located in Central Luconia area, is believed to have a common strong aquifer with the neighboring fields and is a highly heterogeneous reservoir. The field has numbers of extensive and localized baffles/barriers together with high intensity of karstified areas, resulting in significant variations of reservoir characterization and hence dramatically affects the flow behavior in the reservoir, well productivity, water break-through and high abandonment pressure. Due to these heterogeneities, reliable prediction and control of the waterfront and movement, as well as the optimized production policy have significant impact to the hydrocarbon ultimate recovery from the field. This paper presents the adopted methodology and results of the integrated study done on this complex reservoir to monitor waterfront and contact movement by incorporating the effect of the karst areas and tight zones into the field dynamic model to improve the predictability of the final history matched model. The karst areas were mapped out from the available semblance maps and the permeability of those areas were re-evaluated accordingly. The field experienced various pressure patterns and there are several pressure drifts due to the different pressure depletion pattern through the tight zones. This complex pressure patterns have been used as a guideline in incorporating the karst areas and representative tight zones in the model. By applying this methodology, the resulting history matched model showed significant improvements and demonstrated a more representative tool in monitoring and optimizing waterfront and movement in the reservoir. Based on this study, the recovery factor of the field can also be improved by 11%.