Abstract
An integrated model-building exercise was conducted for Field P in the Malay Basin. A model-based estimate of a robust and realistic no-further-activity (NFA) forecast was essential for planning the effective implementation and monitoring of Enhanced Oil Recovery (EOR) processes. Field P has been in production for 40 years. Over 100 wells have been drilled through three target zones targeted for enhanced oil recovery (EOR), providing a clear structural understanding. Being a shore-facies deposit, strong connectivity was observed despite several north-south trending faults. Until now, production has been carried out through a total of 90+ strings, with some allowing commingled production across different zones. Analysis of probe-based pressure data during various drilling campaigns helped provide a qualitative mapping of the nature of shale barriers and their role in controlling water movement. Thorough analysis of production data in a spatial sense aided in understanding the overall recovery process, particularly the water encroachment pattern. Challenges such as the absence of relative permeability data, complex or unique pressure trends during production, poor cement bonds in wells, and commingled production resulting in inadequate allocation to zones were overcome through systematic analysis of reservoir and well performance. A combination of classical reservoir engineering techniques (such as data visualization and material balance approaches) and advanced modeling approaches, like assisted history matching, was utilized to generate multiple realizations of history matches.
A total of eighteen uncertainty parameters were identified. The objective functions contain too many entities and parameters. Therefore, using a single objective function to eliminate uncertain parameters was considered misleading. The first phase of AHM focused on regional pressure matches to reduce uncertainty related to the aquifer, ensuring a reasonable match of the drive mechanism. The second phase of AHM concentrated on other parameters (such as relative permeability parameters, vertical permeability, and transmissibility across zones) to match oil rate and pressure data. These parameters were grouped under different objective functions. Having multiple independent objective functions provided a unique advantage in achieving simultaneous matching of these functions.
This study contributed to achieving a robust and reasonable history match addressing the typical challenges of a mature field. This was done through the application of classical reservoir engineering techniques, well-designed visualization, preconditioning of static models with qualitative observations, and a customized approach in AHM. Most significantly, a systematic approach to the problem in phases and manageable pieces was adopted.
This detailed and appropriately scaled approach greatly assisted the team in achieving a successful history match for the field. This approach could be replicated in many other mature fields.
