Handil is a mature swamp oil and gas field located in Mahakam Delta, East Kalimantan, Indonesia. Hydrocarbon is accumulated within series of multi-layered reservoirs, which are mainly channels and crevasse splay by facies. This study focuses on Handil Gas Pool, also known as Handil Deep Zone interval. This stratigraphic interval is the deepest and primarily produces gas through a depletion drive production mechanism. The unavoidable reservoirs pressure depletion occurred with high variation across the field. Still, Handil is expected to face upcoming aggressive drilling campaign. Therefore, the evaluation of the field remaining stakes becomes even more crucial, particularly for Handil Gas Pool interval, which represents the deepest development target.

Conducting a more conventional reservoirs study method, such as history matching with a dynamic model, in Handil Gas Pool context can be relatively complex and resources-consuming. This complexity arises due to the need for regular updates with newly drilled well data. Nevertheless, identifying and location reservoirs pressure depletion remains key to optimizing future development targets. Hence, a more efficient and practical solution has been deemed necessary to overcome these challenges.

The methodology used in this study was based on integrating reservoir pressure depletion into the static reservoir model. The workflow incorporated dynamic data synthesis, production history and allocation analysis, as well as reservoir pressure estimation through P/z analysis. The study also introduced the definition of Reservoir Pressure Unit (RPU), which served as the basis for modeling and analysis. By estimating and applying the current reservoir pressure, a depleted static reservoir model was generated, representing the current Remaining Gas-in-Place. Furthermore, the volume estimation of booked undeveloped reserves was taken out from the model.

This comprehensive approach resulted in a Producible Gas-In-Place model that can be utilized for estimating and proposing future development targets. The implementation of a well-designed automated well screening workflow, in combination with a detailed dynamic review, facilitated the identification and optimization of future development targets. Among more than 70 initial well candidates, over 20 have been identified as having potential above the current economic threshold. The findings demonstrate the efficiency and practicality of the proposed methodology in identifying future development well targets and its potential for application in similar mature gas fields.

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