Integrated Workflow for Reservoir Development and Optimization in a Low-Seismic-Resolution Formation: A Case Study of a Gas Reservoir in Pakistan

Oil and gas companies have implemented cost-controlled policies for hydrocarbon exploration since significant discoveries have ceased. This approach makes it challenging to achieve a well-defined sub-surface structure, especially given the structural uncertainties and intricacies associated with new discoveries. Consequently, developing optimized fields becomes a real hurdle. This study presents a development strategy that employs integrated dynamic data to define the structure of a reservoir with low seismic resolution and enhance its recovery. The primary focus of this paper is on a recently discovered formation within one of Pakistan's oldest gas giants. The sandstone units that produce gas are found in beds that vary in thickness from 10 to 50 meters and are separated by intervals of mudstone. The low seismic resolution has made locating hydrocarbon extraction spots above the Gas-Water-Contact (GWC) challenging, resulting in a 60% well failure rate. To address this, a workflow was developed that analyses dynamic datasets and reinterprets seismic data to define the reservoir structure accurately. This involved reinterpreting MDT data and formation gradients, re-evaluating core samples, closely examining variations in reservoir pressure, analyzing well failures, creating thickness maps, and examining PVT properties. The initial drilling of four wells in this reservoir resulted in only two successes, both in the Western compartment. However, after producing only 123 BCF, sudden water production led to a lower recovery compared to the estimates of Gas Initially in Place (GIIP). After conducting further geological evaluations and acquiring 3D seismic data, more wells were drilled, which led to the discovery of a new deposition with a different gas-water contact (GWC). Only one well was successfully completed as a producer, adding about 38% more reserve, while the rest were unsuccessful due to high structural uncertainty. To address this issue, a detailed algorithm was developed to integrate dynamic data sets with seismic reinterpretation and thickness mapping. This approach helped in drilling two more successful wells, which added approximately 22% more reserves to the current mix. Further evaluation of the dynamic data from these wells revealed that the two compartments were in communication with each other, despite having a 60m difference in their GWCs. Finally, two more wells are planned, which are expected to increase recoverable volumes by 10-20%, from these compartments. The workflow described in this paper presents a robust algorithm for integrating dynamic data with geological interpretation to delineate a low-resolution reservoir. This is essential since seismic interpretation alone cannot be relied upon for developing such reservoirs. Additionally, the paper outlines robust engineering models and data analyses in a more systematic manner to determine optimum locations for future wells, enabling access to undrained locations.