Enhancing Resource Management Through Advanced Geoscience and Model Calibration: Insights from the HPHT Context

In the quest for sustainable and efficient resource management, advanced geoscience studies and precise model calibration play a pivotal role. This paper presents field studies examples from the HPHT mature context, to understand and manage resource uncertainty, thereby promoting new field opportunities and development. Thanks to robust full-field model calibration, it is possible to perform predictions with more confidence. By leveraging wells data and seismic interpretations, and advanced geostatistical methods, we have developed detailed geological models that significantly reduce uncertainty in production predictions and resource estimation. Dynamic model calibration and assisted history-matching techniques have been crucial in refining our models. These techniques involve adjusting the model parameters to match historical production data, thereby improving the accuracy of future predictions. This iterative process ensures that the model remains consistent with observed data, enhancing its reliability for decision-making. The use of analogs and honoring previous study findings has been integral to our approach. By comparing our fields with similar geological and dynamic settings and incorporating insights from past work, we have enriched and benchmarked our understanding and improved the robustness of our models. Moreover, teamwork and the integration of geophysics, geology, and reservoir engineering have had a profound impact on the study results. Accurate history matching has been achieved thanks to a deep understanding of geoscience and reservoir characteristics, which has been essential for refining our models. This integrated approach has not only enhanced the accuracy of our predictions but also ensured that the results were delivered on time. The collaborative efforts of multidisciplinary teams have once again ensured comprehensive analyses and innovative solutions, delivering results on time and with good accuracy, driving the success of our resource management strategies.