Novel Reservoir Modeling and Experimental Design Approach to Tackle the Challenge of Modeling Highly Compartmentalized Reservoirs under Large Uncertainties in a Mature Offshore Field, Malaysia

Abstract

Abstract The field under the study is located offshore Sabah, Malaysia. It is a mature field with 55 wells, and has been on production for more than 30 years. Despite continual efforts to improve the reservoir description and subsequent placement of infill wells, the average ultimate recoveries of the production wells in the field remain stubbornly low. In terms of reservoir continuity, the field represents the "Perfect Storm" in that the reservoir sands are thin, interbedded with shales, and appear to be extensively faulted. Furthermore, the problems of characterization are exacerbated by poor seismic imaging over the crest of the field, and an unreliable well-to-well correlation due to a lack of clearly distinguishable marine shales. As a structural modelling subject, the field represents a complex problem which exposes the limitations of pillar gridding for geo-cellular model construction. The recovery factor for the field stands at 9% indicating significant recoverable reserves remain, driving the need to better understand the reservoir geology and how this relates to production behavior. A novel reservoir modelling approach was required which would retain enough granularity in the model grid to represent the complex structural & stratigraphic compartmentalization, but without the penalty of excessive simulation run times. The complex stacked stratigraphy and fluid distribution was delineated through integrated analysis of the seismic (in so much as this was possible), the fluid contacts at the wells and the reservoir pressure data, resulting in an initial model of 835 discrete structural/stratigraphic compartments. Within this structural framework, stochastic modelling of net sand facies was used to create the heterogeneous sands and shale which form the fabric of the reservoir which reproduced the baffled connectivity required to emulate the severe pressure depletion and subsequent recovery that is commonly seen. Oil in place volume estimates were re-confirmed by the history matched dynamic model via experimental design, which also resulting multiple best match cases. The multiple static and dynamic models permitted a consistent approach to identifying infill drilling targets and assessing redevelopment feasibility, and the associated uncertainties. With the focus on regions that are currently inaccessible from the existing infrastructure, the study ultimately recommended the location of two new drilling platforms to provide optimal access to the remaining oil. The novel reservoir modeling, which includes the integration of seismic, fluid contact and pressure data to better define reservoir correlation and compartmentalization, was successfully applied to quantify the size of the prize of this highly compartmentalized reservoir. The experimental design approach was then instrumental in managing the principle uncertainties in a consistent way to develop a range history matched subsurface models used to identify future development options.