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Abstract Rock strength is an essential parameter for geomechanical modeling. Many correlations are normally used for rock strength modeling. These empirical relationships are developed for specific basins, rock types, and ages different from the studied basin. Therefore, UCS needs to be validated using quantitative data on core samples. This paper represents a new approach for UCS estimation using lab test measurements for the first time in the Gulf of Suez. More than ninety core plug samples were used for the analysis, selected from twenty-seven wells distributed in ten different fields along the southern Gulf of Suez. The samples represent different facies, rock types, and rock strengths to help in monitoring the variation of the results based on each different parameter. A conventional uniaxial compressive strength test was proceeded in which confining pressure was zero. Well logs such as density and sonic logs used to build different relationships with the resulting UCS measurements. Rock strengths are generally influenced by the physical and elastic properties of rocks. Different rock types have different log-strength relationships, based on their lithology, age, burial history, and consolidation state. Therefore, it is important to avoid applying a relationship calibrated for one rock type to another. Correlations using interpreted parameters such as clay content or total porosity using conventional regression analysis provided a better strength prediction model. In addition, Calibration was improved by using dynamic elastic moduli as they exploit two independent tool responses (sonic and bulk density) which are often more sensitive to strength variations than density or sonic alone and are not overly reliant on interpreted logs. An actual sand management study proceeded using the new empirical equation results to validate it showed good matching. The results of the study represent a pioneering approach of using actual lab test measurements to calibrate the UCS values in the Gulf of Suez. The new data enhanced the geomechanical model results extremely, especially while proceeding sand management studies, which are sensitive to the UCS values.
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DOI: 10.2118/223207-ms
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