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The geological factors, including porosity, lithology, and fluid characteristics, control the Rock Physics Models. Several retrospective studies have examined the methods for discriminating and calculating these geologic parameters in the lower Goru Formation sand reservoir. However, there is significant potential that remains unexplored because of inadequate attention to sand distribution. Therefore, this study proposes the development of a Rock Physics Model (RPM) and a Rock Physics Template (RPT) to identify overlooked inadequately consolidated sand reservoirs. Through the analysis of datasets from five wellbores, we built a modified RPM and RPT for the lower Goru Formation clastic reservoir in Pakistan. The evaluation and comparison of RPMs, including stiff-sand, soft-sand, Greenberg, Castagna, and Raymer’s models, aimed to calibrate the ideal model for future researchers. The results indicate that the stiff-sand model is the most suitable RPM. Furthermore, the RPT is used to test the reliability of the predicted results, which is helpful for formation assessment, reservoir delineation, and prospect evaluation across diverse LGF sand reservoir fields. The proposed model facilitates porosity computation based on seismic impedance throughout the LGF in the Indus Basin, Pakistan, and other regions worldwide with similar geologic characteristics and reservoir distributions. The integration of the modified RPM and RPT not only enhances our understanding of the lower Goru Formation clastic reservoir in Pakistan but also provides a framework for future exploration and reservoir management, providing valuable insights applicable to diverse LGF sand reservoirs globally.

Complex pore structures with multiple inclusions challenge the predictive accuracy of rock physics models. This study introduces a novel method for estimating a single equivalent pore aspect ratio that optimizes rock physics model predictions by minimizing discrepancies with experimental measurements in porous rocks with multiple inclusions with variable aspect ratios and proportions. The proposed methodology uses digital rock physics numerical simulations for validation. A comparative analysis is conducted between the equivalent aspect ratio derived from optimized rock physics models, numerical simulations, and the aspect ratio distribution estimated from digital rock samples. The approach is tested on both synthetic and real core samples, demonstrating its robustness and applicability to field data, including core samples and well log data. The validation results confirm that the method enhances predictive accuracy and offers a versatile framework for addressing pore complexity in subsurface rock formations.

Low porosity-permeability structures and microcracks, where gas is produced, are the main characteristics of tight sandstone gas reservoirs in the Sichuan Basin, China. In this work, an analysis of amplitude variation with offset (AVO) is performed. Based on the experimental and log data, sensitivity analysis is performed to sort out the rock physics attributes sensitive to microcrack and total porosities. The Biot–Rayleigh poroelasticity theory describes the complexity of the rock and yields the seismic properties, such as Poisson’s ratio and P-wave impedance, which are used to build rock-physics templates calibrated with ultrasonic data at varying effective pressures. The templates are then applied to seismic data of the Xujiahe formation to estimate the total and microcrack porosities, indicating that the results are consistent with actual gas production reports.

For the successful discovery and development of tight sand gas reserves, it is necessary to locate sand with certain features. These features must largely include a significant accumulation of hydrocarbons, rock physics models, and mechanical properties. However, the effective representation of such reservoir properties using applicable parameters is challenging due to the complicated heterogeneous structural characteristics of hydrocarbon sand. Rock physics modeling of sandstone reservoirs from the Lower Goru Basin gas fields represents the link between reservoir parameters and seismic properties. Rock physics diagnostic models have been utilized to describe the reservoir sands of two wells inside this Middle Indus Basin, including contact cement, constant cement, and friable sand. The results showed that sorting the grain and coating cement on the grain’s surface both affected the cementation process. According to the models, the cementation levels in the reservoir sands of the two wells ranged from 2% to more than 6%. The rock physics models established in the study would improve the understanding of characteristics for the relatively high Vp/Vs unconsolidated reservoir sands under study. Integrating rock physics models would improve the prediction of reservoir properties from the elastic properties estimated from seismic data. The velocity–porosity and elastic moduli-porosity patterns for the reservoir zones of the two wells are distinct. To generate a rock physics template (RPT) for the Lower Goru sand from the Early Cretaceous period, an approach based on fluid replacement modeling has been chosen. The ratio of P-wave velocity to S-wave velocity (Vp/Vs) and the P-impedance template can detect cap shale, brine sand, and gas-saturated sand with varying water saturation and porosity from wells in the Rehmat and Miano gas fields, both of which have the same shallow marine depositional characteristics. Conventional neutron-density cross-plot analysis matches up quite well with this RPT’s expected detection of water and gas sands.

Carbonate reservoirs exhibit strong heterogeneity in the distribution of pore types that can be quantitatively characterized by applying Xu–Payne multi-porosity model. However, there are some prerequisites to this model the porosity and saturation need to be provided. In general, these application conditions are difficult to satisfy for seismic data. In order to overcome this problem, we present a two-step method to estimate the porosity and saturation and pore type of carbonate reservoirs from seismic data. In step one, the pore space of the carbonate reservoir is equivalent to a single-porosity system with an effective pore aspect ratio; then, a 3D rock-physics template (RPT) is established through the Gassmann’s equations and effective medium models; and then, the effective aspect ratio of pore, porosity and fluid saturation are simultaneously estimated from the seismic data based on 3D RPT. In step two, the pore space of the carbonate reservoir is equivalent to a triple-porosity system. Combined with the inverted porosity and saturation in the first step, the porosities of three pore types can be inverted from the seismic elastic properties. The application results indicate that our method can obtain accurate physical properties consistent with logging data and ensure the reliability of characterization of pore type.

This book introduces readers to the field of seismic data interpretation and evaluation, covering themes such as petroleum exploration and high resolution seismic data. It helps geoscientists and engineers who are practitioners in this area to both understand and to avoid the potential pitfalls of interpreting and evaluating such data, especially the over-reliance on sophisticated software packages and workstations alongside a lack of grasp on the elementary principles of geology and geophysics. Chapters elaborate on the necessary principles, from topics like seismic wave propagation and rock-fluid parameters to seismic modeling and inversions, explaining the need to understand geological implications. The difference between interpretation of data and its evaluation is highlighted and the author encourages imaginative, logical and practical application of knowledge. Readers will appreciate the exquisite illustrations included with the accessibly written text, which simplify the process of learning about interpretation of seismic data. This multidisciplinary, integrated and practical approach to data evaluation will prove to be a valuable tool for students and young professionals, especially those connected with oil companies.

Micro‐continuum models are versatile and powerful approaches for simulating coupled processes in two‐scale porous systems. Initially oriented for modeling static single‐phase flow in microtomography images with sub‐voxel porosity, the concept has been extended over the years to multi‐phase flow, reactive transport, and poromechanics. This paper introduces an integrated micro‐continuum framework to model coupled processes in porous media. It reviews state‐of‐the‐art models and discusses applications in geosciences including Digital Rock Physics with sub‐voxel porosity, moving fluid‐solid interface at the pore‐scale due to geochemical reactions, fracture‐matrix interactions, and solid deformation. Finally, the paper discusses future developments in micro‐continuum models. Key Points Micro‐continuum models are hybrid‐scale approaches for solving flow and transport in porous media State of the art micro‐continuum models handle full Temperature‐Hydrodynamics‐Mechanics‐Chemistry coupling in unsaturated environments Applications include Digital Rock Physics with sub‐voxel porosity, pore‐scale reactive transport, and poromechanics

Permeability estimation is pivotal in reservoir characterization; however, prevailing methods lack a standardized approach. Traditionally reliant on core samples, permeability assessment encounters limitations across diverse thicknesses and wells. An innovative core-independent two-step rock physics template (RPT) can be designed to estimate elastic and conductive properties. The suggested RPT employs the T-matrix method to leverage well-log data encompassing porosity, fluid saturation, and various textural parameters. The estimation process for textural parameters involves addressing uncertainties through the fixed form variational inference (FFVB) with the trust region reflective optimization algorithm. These uncertainties span estimated textural parameters, seismic wave propagation velocity, electrical resistivity, and hydraulic permeability. Micro and macro voids, micro-spherical pores porosity, and their semi-axis are modeled using Beta distributions for both prior and variational families. The noise in the model assumes an inverse gamma distribution for sonic travel time and true formation resistivity. Validation of the proposed method is achieved by comparing the FFVB results with Metropolis Hasting's sampling method in three depths and also through geological observations and experimental analyses on available core samples. The inverse problem, involving the determination of textural parameters through sonic travel time and resistivity, is solved. Subsequently, the forward problem is addressed to estimate permeability. The robustness of the inverse problem is underscored by minimal discrepancies between measured sonic travel times, true formation resistivity values, and the results of the forward problem. The method demonstrates its effectiveness in permeability estimation, even in regions lacking core data, thereby emphasizing its reliability and applicability in diverse geological settings.

Fluid–mineral and fluid–rock interfaces are key parameters controlling the reactivity and fate of fluids in reservoir rocks and aquifers. The interface dynamics through space and time results from complex processes involving a tight coupling between chemical reactions and transport of species as well as a strong dependence on the physical, chemical, mineralogical and structural properties of the reacting solid phases. In this article, we review the recent advances in pore-scale imaging and reactive flow modelling applied to interface dynamics. Digital rocks derived from time-lapse X-ray micro-tomography imaging gives unprecedented opportunity to track the interface evolution during reactive flow experiments in porous or fractured media, and evaluate locally mineral reactivity. The recent improvements in pore-scale reactive transport modelling allow for a fine description of flow and transport that integrates moving fluid–mineral interfaces inherent to chemical reactions. Combined with three-dimensional digital images, pore-scale reactive transport modelling complements and augments laboratory experiments. The most advanced multi-scale models integrate sub-voxel porosity and processes which relate to imaging instrument resolution and improve upscaling possibilities. Two example applications based on the solver porousMedia4Foam illustrate the dynamics of the interface for different transport regimes (i.e., diffusive- to advective-dominant) and rock matrix properties (i.e., permeable vs. impermeable, and homogeneous vs. polymineralic). These parameters affect both the interface roughness and its geometry evolution, from sharp front to smeared (i.e., diffuse) interface. The paper concludes by discussing the challenges associated with precipitation processes in porous media, rock texture and composition (i.e., physical and mineralogical heterogeneity), and upscaling to larger scales.

A Bayesian linear inversion methodology based on Gaussian mixture models and its application to geophysical inverse problems are presented in this paper. The proposed inverse method is based on a Bayesian approach under the assumptions of a Gaussian mixture random field for the prior model and a Gaussian linear likelihood function. The model for the latent discrete variable is defined to be a stationary first-order Markov chain. In this approach, a recursive exact solution to an approximation of the posterior distribution of the inverse problem is proposed. A Markov chain Monte Carlo algorithm can be used to efficiently simulate realizations from the correct posterior model. Two inversion studies based on real well log data are presented, and the main results are the posterior distributions of the reservoir properties of interest, the corresponding predictions and prediction intervals, and a set of conditional realizations. The first application is a seismic inversion study for the prediction of lithological facies, P- and S-impedance, where an improvement of 30% in the root-mean-square error of the predictions compared to the traditional Gaussian inversion is obtained. The second application is a rock physics inversion study for the prediction of lithological facies, porosity, and clay volume, where predictions slightly improve compared to the Gaussian inversion approach.