Summary In Mumbai offshore, Miocene carbonates are deposited with intermediate clastic inputs under cyclic sea level changes and have undergone diagenesis from time to time. Miocene carbonate layers deposited southwest of Mumbai High are producing a good amount of hydrocarbon from 1 to 2 Ω·m resistivity pays. A total of 58 representative core plugs from four different wells were studied to identify the reason for low resistivity and to classify rock facies types and porosity systems using scanning electron microscopy (SEM), thin-section nuclear magnetic resonance (NMR), and petrophysical core data. It was observed from the core study that Miocene carbonates have complex porosity systems and mud-supported to grain-supported reservoir facies. Dominance of mud-supported matrix is the main reason for low resistivity in Miocene carbonate layers as observed from integrated advanced log and core studies. Conventional petrophysical evaluation using constant petrophysical parameters (a, m, n) or linear correlation of cementation factor with porosity can lead to erroneous results in this scenario. A petrofacies-dependent correlation among cementation factor and porosity is attempted in this study for realistic evaluation of low-resistivity carbonate reservoirs. Different cementation factors vs. porosity relations have been derived for various carbonate formations worldwide. Shell formula demonstrates that cementation factor increases with decreasing porosity while correlation derived by Borai and Rafiee brought out inverse relation among cementation factors with porosity in tight carbonates and is providing almost constant cementation factor beyond 0.2. But, in our study, a core porosity-cementation factor plot of reservoir facies is showing that below 0.1, m values are increasing with increase of porosity, which is contradictory to Shell formula. This trend of cementation factor at low porosities is due to the presence of secondary porosity. In the porosity range 0.1–0.25, cementation factor increases eventually with the increase of porosity, but beyond porosity values 0.25, increase in porosity causes decrease of cementation factor. This is due to increasing content of mud-supported matrix, which is overall increasing the total porosity but eventually decreasing cementation in a rock. A new nonlinear correlation has been established between m and porosity for Miocene carbonates of Mumbai offshore area, by incorporating all the factors affecting cementation factor (m). Finally, saturation estimated using variable m either using newly established core derived correlation or resistivity image data is giving representative and improved saturation against low-resistivity reservoir layers compared with constant m.
Since gas hydrates are unconventional reservoirs, they pose unique challenges for identification, characterization, quantification, and extraction. The conventional approach—elastic logs—can provide a better method for identification through attribute analysis. On the other hand, geomechanical studies for wellbore stability analysis pave the way for the effective exploitation of gas hydrates. It is crucial to predict elastic logs against gas-hydrate-bearing sediments, which requires an effective rock physics model. In the present work, a study pertaining to the National Gas Hydrate Program-02 (NGHP-02) campaign in the Krishna‐Godavari (KG) Offshore Basin, India, where gas hydrates are deposited primarily in two facies—a shale-dominated shallower one and a sand-dominated deeper one that has been identified by responses of conventional and spectroscopy logs—is discussed. It is commonly known that depositional heterogeneity impacts petrophysical and elastic properties. To address this issue, an innovative approach has been adopted to model compressional and shear log data using rock physics modeling of gas hydrate reservoirs based on the depositional type of gas hydrate. Guidance from the change of compressional velocity data from log and core with an increase of gas hydrate saturation shows gas hydrate deposition in the study area can be explained through a matrix/grain-supported model. The Jason grain-supported rock physics model appeared best suited among different available rock physics models, depending on the clay volume and porosity in our study area. Using input from a robust multimineral petrophysical evaluation and rock physics modeling, the finalized model is propagated to test wells for predicting compressional, shear, and density logs, with the predicted data validated by core-measured compressional and shear data. Model consistency is indicated by a high correlation from multiwell crossplots of modeled and recorded elastic logs (compressional and shear velocity) with acoustic impedance. The developed rock physics model better discriminates gas hydrate in the shaly sand layer and gas hydrate in the sand-dominated layer, calcite, and shale in the VpVs domain.
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