Insights on Fractured Domains in Reservoirs Resulting from Modeling Complex Geology/Structures - Case Study of the Ratana Field in the Potwar Basin, Pakistan

Exploration success in fold-and-thrust belts, like the Potwar petroleum province, is impacted by seismic imaging challenges and structural complexity. Success partly relies on the ability to validate subsurface models and model a range of properties, such as reservoir permeability. This is particularly important in the case of tight carbonate reservoirs such as the Eocene Sakesar Formation, where the recovery of economic quantities of hydrocarbons is conditioned by the presence of fracture-enhanced permeability. This requires the application of geological and geophysical modeling techniques to address these challenges, to minimize uncertainty and drive exploration success. The interpretation and structural validation of the Ratana structure presented here allows the proposal of a consistent and robust structural model even in areas of higher uncertainty in the data, such as along faults. The dynamically updatable, watertight, complex 3D structural framework created for the top Sakesar reservoir was used in combination with an assisted fault interpretation algorithm to characterize the fault and fracture pattern. The results showed a higher density of high amplitude fractures on the flanks of the structure rather than along the hinge. These results are supported by the incremental strain modeling based on the kinematic evolution of the structure. Together, this helped to characterize potential fracture corridors in areas of the seismic volume that previously proved challenging for human driven interpretation. Our results allow us to reduce the uncertainty related to the geometrical characteristics of the reservoir and provide insights into potential exploration well targets to maximize chances of success, suggesting that permeability and hydrocarbon flow may be higher at the margins of the Ratana structure, and not at the crest, which was the focus of previous exploration and production efforts.

Seismic gravimetric modeling in geological problems of Saratov region sections

Geological and geophysical modeling is a modern and classic method of processing and interpretation, which is relevant in the segment of geological exploration of any geophysical method. The article presents the material of two-dimensional modeling based on the results of gravity and seismic exploration in the licensed areas of the Saratov region.

Insights and Lessons from 3D Geological and Geophysical Modeling of Mineralized Terranes in Tasmania

Over the last two decades, Mineral Resources Tasmania has been developing regional 3D geological and geophysical models for prospective terranes at a range of scales and extents as part of its suite of precompetitive geoscience products. These have evolved in conjunction with developments in 3D modeling technology over that time. Commencing with a jurisdiction-wide 3D model in 2002, subsequent modeling projects have explored a range of approaches to the development of 3D models as a vehicle for the better synthesis and understanding of controls on ore-forming processes and prospectivity. These models are built on high-quality potential field data sets. Assignment of bulk properties derived from previous well-constrained geophysical modeling and an extensive rock property database has enabled the identification of anomalous features that have been targeted for follow-up mineral exploration. An aspect of this effort has been the generation of uncertainty estimates for model features. Our experience is that this process can be hindered by models that are too large or too detailed to be interrogated easily, especially when modeling techniques do not readily permit significant geometric changes. The most effective 3D modeling workflow for insights into mineral exploration is that which facilitates the rapid hypothesis testing of a wide range of scenarios whilst satisfying the constraints of observed data.

Pareto-Based Multiobjective Particle Swarm Optimization: Examples in Geophysical Modeling

It has been recently revealed that particle swarm optimization (PSO) is a modern global optimization method and it has been used in many real world engineering problems to estimate model parameters. PSO has also led as tremendous alternative method to conventional geophysical modeling techniques which suffer from dependence to initial model, linearization problems and being trapped at a local minimum. An area neglected in using PSO is joint modeling of geophysical data sets having different sensivities, whereas this kind of modeling with multiobjective optimization techniques has become an important issue to increase the uniqueness of the model parameters. However, using of subjective and unpredictable weighting to objective functions may cause a misleading solution in multiobjective optimization. Multiobjective PSO (MOPSO) with Pareto approach allows obtaining set of solutions including a joint optimal solution without weighting requirements. This chapter begins with an overview of PSO and Pareto-based MOPSO presented their mathematical formulation, algorithms and alternate approaches used in these methods. The chapter goes on to present a series synthetic modeled of seismological data that is one kind of geophysical data by using of Pareto-based multiobjective PSO. According to results matched perfectly, we believe that multiobjective PSO is an innovative approach to joint modeling of such data.

A Review of Geophysical Modeling Based on Particle Swarm Optimization

This paper reviews the application of the algorithm particle swarm optimization (PSO) to perform stochastic inverse modeling of geophysical data. The main features of PSO are summarized, and the most important contributions in several geophysical fields are analyzed. The aim is to indicate the fundamental steps of the evolution of PSO methodologies that have been adopted to model the Earth’s subsurface and then to undertake a critical evaluation of their benefits and limitations. Original works have been selected from the existing geophysical literature to illustrate successful PSO applied to the interpretation of electromagnetic (magnetotelluric and time-domain) data, gravimetric and magnetic data, self-potential, direct current and seismic data. These case studies are critically described and compared. In addition, joint optimization of multiple geophysical data sets by means of multi-objective PSO is presented to highlight the advantage of using a single solver that deploys Pareto optimality to handle different data sets without conflicting solutions. Finally, we propose best practices for the implementation of a customized algorithm from scratch to perform stochastic inverse modeling of any kind of geophysical data sets for the benefit of PSO practitioners or inexperienced researchers.

Post-Impact Faulting of the Holfontein Granophyre Dike of the Vredefort Impact Structure, South Africa, Inferred from Remote Sensing, Geophysics, and Geochemistry

Better characterization features borne from long-term crustal modification processes is essential for understanding the dynamics of large basin-forming impact structures on Earth. Within the deeply eroded 2.02 Ga Vredefort Impact Structure in South Africa, impact melt dikes are exposed at the surface. In this study, we utilized a combination of field, remote sensing, electrical resistivity, magnetic, petrographical, and geochemical techniques to characterize one such impact melt dike, namely, the Holfontein Granophyre Dike (HGD), along with the host granites. The HGD is split into two seemingly disconnected segments. Geophysical modeling of both segments suggests that the melt rock does not penetrate below the modern surface deeper than 5 m, which was confirmed by a later transecting construction trench. Even though the textures and clast content are different in two segments, the major element, trace element, and O isotope compositions of each segment are indistinguishable. Structural measurements of the tectonic foliations in the granites, as well as the spatial expression of the dike, suggest that the dike was segmented by an ENE–WSW trending sinistral strike-slip fault zone. Such an offset must have occurred after the dike solidified. However, the Vredefort structure has not been affected by any major tectonic events after the impact occurred. Therefore, the inferred segmentation of the HGD is consistent with long-term crustal processes occurring in the post-impact environment. These crustal processes may have involved progressive uplift of the crater floor, which is consistent with post-impact long-term crustal adjustment that has been inferred for craters on the Moon.

Aplicación del método de iluminación por campo de onda en un modelo subthrust en la Cuenca del Valle Superior del Magdalena (Colombia)

Complex structures like subthrust show high risk during the definition of structural traps in low quality seismic images in depth, so we can use the structural interpretation to simulate the subthrust illumination by wavefield of a prospect area in order to reduce the uncertainty and support the oil exploration process. In general, we performed an exercise of 2D geophysical modeling using a wavefield illumination simulator. At first, we interpreted two geological models from a seismic line in depth. The geological interpretation was adjusted with information about structural styles in this part of Upper Magdalena Basin. Then, we use a velocity scenario and assign these velocities to both geological models. The wavefield illumination method allows us to see all of the wavepaths in the different pair of source-receivers in order to do a fast evaluation of the structure illumination. This could be used to improve the seismic acquisitions in structurally complex media.