The heterolithic thin-bedded sand and shale are very commonly associated reservoirs column in shallow water clastic depositional environment in Malaysia Basin. The complexity in reservoirs characterization of heterolithic thin-bedded sand often leads to underestimating the potential contribution of these types of the reservoir for development and exploration targets. The naturally laminated of heterolithic thin-bedded sand make it more difficult in building the realistic 3D geological model and has an impact on volumetric calculation and reserve estimation. This study is applied in the development phase by introducing Log resolution enhancement methods in laminated thin-bedded sand characterization to quantify the reservoir potential with high-resolution 3D modelling methods. The quantification of sand and shale in thin bedded analysis using core data and image logs, then transform into lithofacies classification from sand and shale volume cutoff. The distribution and computation of lithofacies and reservoir properties build into a 3D model is obtained from a geological depositional environment analog at field-scale of a conventional setting. The results indicated high-resolution 3D geological modelling successfully preserved the characterization of thin-bedded sand and shale; and revealed an excellent correlation with the image log. The presence of inter-bedded sand and shale of reservoir column in the 3D geological model provides the quantification of thin-bedded sand contribution and potential realistic volumetric estimation for the entire reservoir interval. The thin-bedded reservoir characterization and high-resolution 3D modelling technique successfully address the existent of heterolithic reservoir facies previously simplified.
Thinly bedded sand-shale heterolithic are commonly found as a marginal reservoir in the Malay Basin. In the evaluation of heterolithic reservoirs, a key challenge is to determine the appropriate petrophysical properties cutoff. This study used the Modular Dynamic Tester (MDT) pressure tests to determine the appropriate petrophysical properties cutoff applicable to heterolithic intervals. Intrinsic permeability analysis and MDT mobility plots were used to determine the cutoffs for shale volume and total porosity. Subsequently, hydrocarbon pore volume thickness (with shale volume and porosity cutoff applied) was plotted against water saturation to determine the water saturation cut-off value. In this case study, the reservoir cutoffs applied are shale volume less than 60% and total porosity in excess of 12 %. The hydrocarbon pay cutoff was set at a water saturation less than 85 %.
The traditional method of geologic modelling requires the interpretation of geological sections during digitization. But this traditional method has its limitations, the main limits are; it is usually time consuming and the model produced is unique to each individual geologist interpretation and may not be easily replicated by others. This study proposes an alternative workflow method for modelling, constructing and interpreting 3D geologic static model with multi-source data integration. The volume base method (VBM) was used to construct the 3D model. The combination of deterministic and probabilistic methods was used to model the facies workflow process to capture the geometrics of depositional environmental element. The truncated Gaussian simulation method was used with vertical trends option to obtain vertical transitional lithofacies in most of the reservoirs. Verification of results and detailed discussion of the proposed workflow and methodology is based on comparison with the conventional method. The saturation height function (SHF) equation applied to the water saturation model and permeability model improved the 3-D properties modelling workflow. The pillar gridding process was identified as the stage that increases the timeframe in 3-D modelling workflow. The results have proven to improve the overall timeframe and maximize the value of the field studies. The proposed method can be applied to a broad and complex geologic area. And is useful for marginal field development, by contributing economically and improving the deliverability of the entire project.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.
hi@scite.ai
10624 S. Eastern Ave., Ste. A-614
Henderson, NV 89052, USA
Copyright © 2024 scite LLC. All rights reserved.
Made with 💙 for researchers
Part of the Research Solutions Family.