Predicting sand size distribution based on well logs of east Malaysia basins

• Published in: IOP Conference Series: Earth and Environmental Science
• Main Author: Geraman J.J.A.J.; Mat-Shayuti M.S.; Othman N.H.; Alias N.H.; Marpani F.; Tengku Mohd T.A.
• Format: Conference paper
• Language: English
• Published: Institute of Physics 2023
• Online Access: https://www.scopus.com/inward/record.uri?eid=2-s2.0-85152963512&doi=10.1088%2f1755-1315%2f1151%2f1%2f012019&partnerID=40&md5=487b2954c1d3c97cc2537764cf11fd2c

Sand management is an integral part of petroleum production especially in brown fields. A big influence in sand control strategy is sand size distribution, which is not always accessible due to difficult and costly coring analysis. Hence, this paper aims to test the ability of selected numerical models in predicting the sand size distribution based on well logs and reports. Three models were tested namely Krumbein and Monk, Berg, and Van Baaren, with the estimations later were compared with the actual data from the fields of Sabah and Sarawak located in East Malaysia basins. From the result, the model by Van Baaren showed the closest agreement with the actual data, with excellent accuracy for particle size close to 100 µm. This was followed by Berg, while Krumbein and Monk model displayed the least fitting. The models then were fine-tuned by introducing correction coefficients determined via numerical solver, and the calibrated formulas improved the accuracy by 12%. Despite more studies and refinement are required before this method can be proliferated, the result from this study indicates its huge potential. © 2023 American Institute of Physics Inc.. All rights reserved.