Improved Reservoir Fluid Estimation for Prospect Evaluation Using Mud Gas Data

Reservoir fluid estimation for exploration prospects can be random and have large uncertainties. Typically, the reservoir fluid estimation in a prospect can be derived from a geochemical basin model or seismic data interpretation with regional knowledge. An analog reservoir fluid sample will often be selected for reservoir fluid estimation. Such analog samples can come from a neighboring field at some distance. The best approach for accurate reservoir fluid estimation is based on the reservoir fluid data from nearby wells when available. This paper demonstrates that mud gas data from wells inside or near the exploration prospect provides a much-improved reservoir fluid estimation. In our previous work (Yang et al., 202, 2022), we developed novel methods to estimate reservoir fluid properties from advanced and standard mud gas (SMG) data. This paper uses three field cases to illustrate how mud gas data can be translated into reliable reservoir fluid estimations for prospect evaluation for potential developments. We have SMG data available for the three field cases. The first two cases are examples of gas and oil prospect evaluations based on legacy wells without reservoir fluid samples. The last example is a prospect evaluation of overburden for potential production. The new mud gas data method provides accurate reservoir fluid estimations for three prospect evaluations with significantly reduced uncertainty. The implementation of the new method for prospect evaluation has not been reported previously. Due to the wide availability of SMG data, the new method can be broadly implemented for prospect evaluations and generates large business impacts.