In the recent past, the applicability and uncertainty of pore-pressure prediction methods that work based on seismic signals have been serious challenges in carbonate reservoirs. In this context, enormous research has been conducted on the prediction of pore pressure in these rocks, some of which have ended with failure due to the complexity of carbonates. To address the main cause of such failures, we experimentally simulate the pore fluid in carbonates under reservoir conditions to interpret and classify the factors contributing to the pore pressure. The results are then built into a novel hybrid experimental model for evaluating the feasibility of pore pressure prediction — one that could bridge the gap between laboratory and empirical approaches. For this purpose, 34 core samples are collected from different geologic formations at different wells penetrating reservoir intervals. The mechanical properties of the samples are investigated by conducting experiments in a triaxial cell where pore pressure is applied under different regimes while simultaneously acquiring the ultrasonic response of the sample. Sensitivity analyses of pore pressure are carried out under drained and undrained conditions and the results are used to evaluate our methodology. Pore pressure coefficients of P- and S-wave velocities are introduced in two different conditions, namely constant differential stress and constant pore pressure, with the same dimension as compressibility. Results are interpreted statistically and effective parameters are identified from a pool of many variables; these include the static bulk modulus, Young’s modulus, Biot’s coefficients, porosity, permeability, and sedimentary textures (e.g., micritization, neomorphism, cementation, fracture, blocky calcite, and dissolution). A feasibility study template is further introduced for investigating pore pressure detectability based on commonly available data in carbonate reservoirs by incorporating the main controlling factors. Our template and findings of this research are important for pore pressure prediction before performing further research and implementing operation programs. They also can decrease the risk of underestimating the pore pressure, thereby improving the well planning performance and mitigating the drilling hazards.

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