Abdullah K Idrees

Title: Abdullah K Idrees: Innovator in Sedimentary Reservoir Analysis

Introduction

Abdullah K Idrees is a notable inventor based in Dhahran, Saudi Arabia. He has made significant contributions to the field of sedimentary reservoir analysis through his innovative patent. His work focuses on utilizing machine learning to enhance the understanding of grain size distribution in subterranean environments.

Latest Patents

Abdullah K Idrees holds a patent titled "Relative grain size determination and flow characterization in sedimentary reservoirs." This patent describes a method for generating a relative grain size value for subterranean depth intervals by executing a machine learning model that processes petrophysical well log data. The generated relative grain size value indicates the proportions of grain sizes of sedimentary rock materials at un-cored depth intervals. The machine learning model is trained using observed grain size data from cored intervals. Based on the relative grain size value, flow index values for un-cored depth intervals of production wells are determined. The flow index is influenced by effective porosity, total clay content, and the relative grain size value. This innovative approach allows for the identification of target depth intervals for hydrocarbon production based on flow index values.

Career Highlights

Abdullah K Idrees is currently employed at the Saudi Arabian Oil Company, where he applies his expertise in sedimentary reservoir analysis. His work has contributed to advancements in the understanding of hydrocarbon production and reservoir characterization.

Collaborations

Abdullah has collaborated with notable colleagues, including Mohammed M Alshalan and Weihua Wang, to further enhance the research and development in his field.

Conclusion

Abdullah K Idrees is a pioneering inventor whose work in sedimentary reservoir analysis through machine learning has the potential to transform hydrocarbon production strategies. His innovative patent reflects his commitment to advancing the field and improving resource extraction methods.