ABSTRACTFractures represent a critical structural feature in unconventional reservoirs, as they create essential pathways for the migration and accumulation of oil and gas. Therefore, fracture characterization is a fundamental task in the exploration of unconventional hydrocarbon resources. Conventional fracture characterization methods typically do not account for the inherent anisotropy of the formation, which arises from the sedimentary environment and fluid distribution, often leading to inaccurate fracture predictions. To address this challenge, we propose a petrophysical model that incorporates inherent anisotropy, employing rock physics modelling to accurately characterize fracture distribution. Furthermore, to reduce the substantial workload involved in manually calibrating the petrophysical model, we introduce a one‐dimensional convolutional neural network combined with an attention mechanism. By leveraging the advanced nonlinear learning capabilities of the convolutional neural network, we aim to fit the petrophysical model and extend its application across all exploration wells and the entire field. The effectiveness and feasibility of the proposed method are demonstrated through experiments using actual borehole data from a fracture‐dominated reservoir.

ABSTRACT Accurate simulation of seismic waves is essential for achieving high‐precision full‐waveform inversion (FWI). Within the Cartesian coordinate system‐based frequency‐domain finite‐difference (FDFD) framework, we propose a one‐direction composition average‐derivative optimal method for the 3D heterogeneous isotropic elastic‐wave equation, referred to as the 45‐point scheme. The results of dispersion analysis and weighted coefficient optimization demonstrate that the 45‐point scheme achieves higher dispersion accuracy than the existing 27‐point average‐derivative scheme. More importantly, by constructing the impedance matrix along the ‘composition’ direction, the bandwidth of the sparse impedance matrix increases only slightly, with nonzero elements compactly distributed in strips. On the basis of the multifrontal massively parallel sparse direct solver (MUMPS) on a supercomputer platform, the 45‐point scheme does not significantly increase computational complexity compared to the 27‐point scheme. To further test the performance of the 45‐point scheme, we provide several numerical experiments, including simple homogeneous and complex SEG/EAGE overthrust models. In comparison with the 27‐point scheme, the 45‐point scheme yields a notable improvement in computational accuracy, particularly for large grid ratios, while imposing only a modest increase in computational cost. These findings thus strongly suggest that the 45‐point scheme holds promise as a viable option for the forward part of frequency‐domain FWI in practical high‐accuracy seismic imaging applications.

ABSTRACTThe transient electromagnetic method (TEM) is a prominent geophysical technique, and the TEM inversion for resistivity models is a crucial aspect of physical exploration. However, TEM inversion faces challenges such as nonlinearity, multiple solutions and ill‐conditioning, which can lead to inaccurate results. In response to these challenges, metaheuristic algorithms have been extensively studied for their innovative approaches to solving inverse problems. Despite this, many existing metaheuristic inversion algorithms exhibit limitations, including premature convergence, slow convergence speed and inadequate computational accuracy. To address these issues, an improved bat algorithm (IBA) that incorporates logistic chaotic mapping and a spiral flight strategy (Logistic Chaotic Mapping and Spiral Flight Strategy‐Based Bat Algorithm, LSBA) has been proposed. The logistic chaotic mapping strategy is utilized to initialize the population of the bat algorithm to enhance the initial convergence rate. Moreover, the spiral flight strategy facilitates the bats’ escape from local optima, thereby improving the algorithm's local exploration capabilities and solution accuracy. Numerical simulations, synthetic models and field experiments have demonstrated that the LSBA significantly enhances solution precision (the degree of closeness between the algorithm's inverted parameters and the true values), convergence speed and anti‐noise performance. The LSBA effectively retrieves the stratigraphic parameters of the true model and accurately represents the geological information of actual mining areas, thereby validating the efficacy and feasibility of the proposed approach in TEM inversion.

ABSTRACTTime‐lapse seismic signals and their relation to variations in reservoir pore pressure and fluid saturations are, in general, well understood. Occasionally time‐lapse (4D) seismic data do present some intriguing anomalies that cannot be properly explained by our general well stablished expectations, forcing us to consider less conventional hypotheses. We present one such case, occurring in a weakly cemented sandstone reservoir in the North Sea. This reservoir presents a few 4D seismic softening signals occurring as a response to pore pressure decrease, where no saturation changes are expected. With a detailed multidisciplinary analysis, we assess all possible explanations for this type of signal and show that conventional explanations in terms of fluid saturation changes and/or elastic stress variations fail to explain the full characteristic of the observed anomalies. As an alternative hypothesis, we propose the possibility of pore collapse, an inelastic rock damage process, as an unconventional explanation to the observed anomalies. We show that this hypothesis is the only one that explains all the characteristics of the observed anomalies in terms of their lateral and vertical extents, as well as their magnitude and temporal evolution behaviour. We then conduct a theoretical modelling feasibility study to estimate the critical pressure for initiation of rock damage and estimate the amount of rock damage needed to produce the observed 4D seismic signals. This feasibility study suggests that the reservoir effective pressure achieved during field production is likely not enough to crush grains and cause reservoir compaction. However, they may be enough to cause cement and weak grain cracking, which we estimate through rock physics modelling to be a sufficient mechanism for producing the observed softening anomalies. This makes weakly cemented sandstones more prone to this type of counterintuitive signal, as cement damage occurs at lower effective pressures, more commonly achieved during reservoir production. We also highlight important considerations regarding plans of CO2 storage into depleted reservoirs, as the possibility of rock damage during production would complicate the monitorability of the injected CO2 plume.

ABSTRACTBorehole seismic investigations play a major role for high‐resolution imaging of geological structures at depth. The resulting borehole seismic data enable a direct characterisation of the target units as well as their physical properties along the well and in its direct vicinity. Analysing seismic data acquired at different scales within the borehole provides additional notable insights and allows an improved geological and petrophysical interpretation. In our work, we processed zero offset vertical seismic profiling data and full waveform sonic log data as part of a multiscale borehole seismic imaging workflow to better characterise a mineral exploration target at Ludvika Mines (Blötberget mining area, Central Sweden). Data processing mainly comprised wavefield separation and corridor stacking, followed by migration of the full waveform sonic log data using a diffraction stack approach. Additional borehole data, that is, impedance logs and a lithological borehole profile, were used for the integrated interpretation to provide the basis for an assignment of the reflectors to a specific lithological unit. Besides the existing structural models derived from surface seismic investigations, the new images from borehole seismic data reveal the internal structure of the mineralisation at a significantly higher resolution, complement the geophysical characterisation and can be used for a subsequent reliable mineral resource estimate.

ABSTRACTAccording to Huygens' principle, all points on a wave front act as secondary sources emitting spherical waves and the envelope of these spherical waves forms a new wave front. In the mathematical formulation of Huygens' principle, the waves emitted by the secondary sources are represented by Green's functions. In many present‐day applications of Huygens' principle, these Green's functions are replaced by their time‐reversed versions, thus forming a basis for backpropagation, imaging, inversion, seismic interferometry, etc. However, when the input wave field is available only on a single open boundary, this approach has its limitations. In particular, it does not properly account for multiply reflected waves. This is remedied by a modified form of Huygens' principle, in which the Green's functions are replaced by focusing functions. The modified Huygens' principle forms a basis for imaging, inverse scattering, monitoring of induced sources, etc., thereby properly taking multiply reflected waves into account.

Abstract The success of horizontal loop electromagnetic method in determining ore body model parameters is intricately tied to the inversion process. However, geophysical inverse problems often grapple with ill‐posed and non‐unique mathematical difficulties. To handle this situation, we presented two new metaheuristics: the Barnacles Mating Optimizer and the Hunger Games Search algorithm. This pioneering approach is the first in the literature to employ both optimizers simultaneously to invert electromagnetic anomalies. To test the core functionality of these inversion tools, we simplified the horizontal loop electromagnetic problem by using a single frequency. Before carrying out the data inversions, a synthetic anomaly caused by a simple multi‐source model was used to perform some modal analyses. These analyses revealed the composite modality character of the inversion process and highlighted the necessity of an algorithm that effectively balances global exploration (thoroughly searching the model space while avoiding local minima) and local exploitation, which focuses on approximating the global optimum closely. In addition, the findings indicated the importance of conducting post‐inversion analyses to evaluate potential uncertainties in the estimations. Initial experiments with nine challenging benchmark functions revealed that Hunger Games Search outperforms in tackling optimization problems. The performances of both algorithms were then examined using synthetic horizontal loop electromagnetic anomalies and two field data sets from Australia. To achieve a balanced comparison, we fine‐tuned the control parameters of both algorithms, optimizing their performance under comparable conditions. These assessments provided valuable insights into the effectiveness of each algorithm when properly configured. Uncertainty appraisal analyses mostly confirmed the consistency and mathematical consistency of the obtained solutions. In the real data inversion cases, the outputs of Hunger Games Search showed strong agreement with the drilling data. This study illustrates the stronger performance of the Hunger Games Search algorithm relative to Barnacles Mating Optimizer in the presented scenarios and demonstrates its effectiveness in estimating source parameters using horizontal loop electromagnetic anomalies.

Abstract Reducing the uncertainty of reservoir characterization requires to better identify the small‐scale structures of the subsurface from the available data. Studying the seismic response of meter‐scale, stratigraphic heterogeneities typically relies on the generation of reservoir models based on outcrop examples and their forward seismic modelling. To bridge geological information and seismic modelling, these methods allocate values of acoustic properties, such as mass‐density and P‐wave velocity, according to discretized properties like layer‐type lithology or facies units. This strategy matches the current workflow in seismic data inversion in industry, where modelling workflows are based on lithofacies distributions. However, from stratigraphic modelling, we know that meter‐scale heterogeneities occur within certain facies and lithologies. Here, we evaluate the difference on the seismic response between allocating acoustic properties in a grain size–based, semi‐continuous manner versus discretized manners based on lithology and facies classifications. To do so, we generate a reference geological simulation that we populate with acoustic properties, mass‐density and P‐wave velocity, using three different strategies: (1) based on grain size distribution; (2) based on facies distribution; and (3) based on lithology. The method we propose includes the generation of realistic geological simulations based on stratigraphic modelling and the transformation of its output into acoustic properties, honouring the intra‐lithology and intra‐facies, small‐scale structures. We, then, generate seismic data by applying a forward seismic modelling workflow. The synthetic data show that the grain size–based simulation allows the identification of small‐scale, stratigraphic heterogeneities, such as beds with strong density and velocity contrasts. These stratigraphic structures are smoothened or may completely disappear in the facies and lithology discretized simulations and, therefore, are not (well) represented in the synthetic seismic data. Recognizing meter‐scale, stratigraphic heterogeneities is relevant for the characterization of the fluid flow in the reservoir. However, current discrete and lithology‐based strategies in seismic inversion are not able to resolve such heterogeneities because real subsurface properties are not discrete properties but continuous, unless there are stratigraphic discontinuities such as erosional surfaces or faults. This research works towards a better understanding of the relationship between changes in these continuous properties and the observed seismic data by introducing greater complexity into the discretized geological simulations. Here, we use synthetic seismic images with the goal of eventually aiding in fine‐tuning seismic inversion methodologies applied to real seismic data. One pathway is to foster the development of inversion approaches that can leverage stratigraphic modelling to get stronger geological priors and replace the standard but inadequate multi‐Gaussian prior.

Abstract The deep coalbed methane development is in its initial stage, with limited research on elastic anisotropy of coals in deep coalbed methane reservoirs. To study the elastic anisotropy of coals in deep coalbed methane reservoirs, three sets of cylindrical primary coals are collected from the relatively shallow area of the Taiyuan 8# coal formation, a key site for deep coalbed methane extraction. The microscopic observation, basic physical property test, ultrasonic velocity measurement and theoretical modelling are constructed to study the pressure sensitivity of elastic properties and the factors affecting the elastic anisotropy of coal samples. The velocity increases rapidly with confining pressure increasing at confining pressures below 13 MPa but relatively stabilizes at higher pressures. The velocity perpendicular to the bedding plane is more sensitive to pressure than that parallel to the bedding plane. As confining pressure increases, the velocity anisotropy decreases but remains noticeable at the highest pressure. Based on the microstructure and ultrasonic experiment results, an anisotropic rock physics model for the deep coalbed methane reservoir is constructed to quantitatively analyse the effects of the clay and organic matter and pore structure on the elastic anisotropy of coals. The modelling analysis indicates that P‐ and S‐wave velocity anisotropies decrease as the degree of preferred orientation of organic matter and clay decreases, which increases with the increase of organic matter and clay content. The equivalent pore aspect ratio and lamination index of studied coals are obtained from a practical inversion scheme based on the proposed model. The results can support the anisotropic rock physics inversion of deep coalbed methane reservoirs and the accurate prediction of engineering sweet spot parameters.