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Fluid substitution in NMR T_(2)distribution and resistivity independent saturation computation using synthetic capillary pressure data

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Petroleum Research 2023年第1期8卷 77-86页

作者： ilius mondal Kumar Hemant Singh Department of Earth Science Indian Institute of Technology BombayIndia

Petrophysicists and reservoir engineers utilise the capillary pressure and saturation-height function for calculating the water saturation of any reservoir,at a given height above the free water *** results have a big impact on reserve *** majority of capillary pressure studies are carried out in labs with core ***,on the other hand,are usually altered from their original state before being delivered to ***,the accuracy of discrete sets of core data in describing entire reservoir parameters,is still up for *** of the capillary pressure curve in reservoir condition is an important subject that is challenging to *** use of nuclear magnetic resonance(NMR)logs for oil and gas exploration has grown in popularity over the last few ***,most of the time the utilization of the data is limited for evaluating porosity-permeability,distributions and computation of irreducible water *** the advent of fluid substitution methods,NMR T_(2)distributions may now be used to synthesize core equivalent capillary pressure *** fluid substitution workflow,our study introduces a better approach for obtaining capillary pressure curves from the NMR T_(2)*** available core data has been used to calculate calibration parameters for better saturation height *** workflow introduces a novel approach in resistivity independent saturation *** the exploratory wells of our study area,computed water saturation derived from the saturation height function exhibits encouraging agreement with resistivity based water saturation from multi-mineral *** NMR based saturation height modelling approach has been included in study area for the first time so far.

关键词： Carbonate reservoir NMR fluid Substitution Capillary pressure Saturation height function Resistivity independent saturation

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Understanding pore characteristics through core-based petrographic and petrophysical analysis in a heterogeneous carbonate reservoir:A case study from the Mumbai Offshore Basin,India

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Petroleum Research 2023年第4期8卷 469-480页

作者： ilius mondal Kumar Hemant Singh Department of Earth Science Indian Institute of TechnologyBombayIndia

Carbonate rocks exhibit complex and heterogeneous pore structures;such heterogeneity is manifested by the occurrence of a wide variety of pore types with different sizes and geometries as a result of depositional and diagenetic *** complications substantially increase the uncertainty of predicted rock hydraulic parameters because samples with comparable porosities might have very different permeability *** this study,small-scale characterisation of porosity and permeability in heterogeneous Eocene limestone samples from the Bassein Formation of the B-X structure of the MK Field in Mumbai Offshore Basin,India,was carried out,employing an integrated framework that in-corporates thin-section petrography,routine core analysis,mercury injection capillary pressure and nuclear magnetic resonance *** pore characteristics of these carbonates range from poor to *** studied samples exhibited large ranges of porosity,permeability and other associated petrophysical *** pore types,as well as their orientations and connectivity,are the primary factors causing the *** of the complexity of the pore networks,a simple lithofacies classification alone would have been insufficient to link porosity and *** reservoir char-acteristics in the study area are strongly linked to the development and/or destruction of reservoir porosity-permeability during different phases of ***-four carbonate core samples from the limestone unit were studied and classified into microfacies and pore type classes,producing an accurate assessment of reservoir *** comprehensive workflow incorporates the pore volume distributions and pore throat attributes for each rock *** carbonate microfacies were identified by petrographic analysis and their petrophysical characteristics,such as porosity,permeability,pore throat size,pore volume and fluid flow factors,were *** study demonstrates how macro-porosity

关键词： Carbonatereservoir Permeability Mercury injection capillary pressure Nuclear magnetic resonance Porosity partitioning

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Core-log integration and application of machine learning technique for better reservoir characterisation of Eocene carbonates,Indian offshore

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Energy Geoscience 2022年第1期3卷 49-62页

作者： ilius mondal Kumar Hemant Singh Indian Institute of Technology Bombay India

Rock types,pore structures and permeability are essential petrophysical outputs,and they contribute considerably to the highest degree of uncertainty in reservoir *** factors have a strong influence on exploration and field development *** analysis is the best approach for estimating permeability,assigning rock types and characterising pore *** logs are the most often employed method for estimating the parameters at each data point of reservoirs since there are more un-cored wells than cored *** intelligence,on the other hand,is gaining popularity in the geosciences due to the ever-increasing complexity and volume of available subsurface *** is also obvious in the demand for faster and more accurate interpretations in order to identify reservoir characteristics in increasingly difficult and complicated petroliferous *** Neural Networks and Self-Organizing Maps are examples of machine learning approaches that can be used in both supervised and unsupervised modes for modelling and *** carbonates of Mukta oilfield are the major pay rocks of strong geological heterogeneity in terms of their porosity and permeability relationship with pore *** paper outlines a novel method of rock fabric classification,pore structure characterization,flow unit classification and robust reservoir permeability modelling based on an integrated approach that incorporates core measurements,log data and machine learning *** pore structure has been characterised by the combination of conventional core,capillary pressure and nuclear magnetic resonance *** neural network has added an adequate benefit in accurate permeability modelling by utilizing the concepts of rock classifications and hydraulic flow units.

关键词： Permeability Microfacies MICP NMR Hydraulic flow unit Artificial neural network Reservoir characterisation

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