Geophysical Data Processing Research Articles

Rapid analysis of drill core data for detection of geological boundaries

Regolith geochemical and geophysical patterns related to underlying mineralisation may be difficult to detect in regions where the regolith is thick, transported or has developed complex layering during its mineralogical and geochemical evolution. Detection and accurate logging of geochemical and mineralogical interfaces and horizons within drill samples obtained from such regolith profiles, including the boundary between regolith and underlying bedrock can be critical for detection and interpretation of geochemical patterns. In turn, this assists in selecting zones for systematic sampling and the optimum combination of geochemical, mineralogical and geophysical analysis and data processing to enhance signals or patterns associated with mineralisation.This study presents a multivariate data-driven approach to detecting boundaries within regolith and other profiles potentially incorporating near real-time, in-situ geochemical, mineralogical, and petrophysical data acquisition methods to aid decision-making during stratigraphic/exploration drilling campaigns. The approach is demonstrated using geochemical and mineralogical data from a drillhole at the McKinnons Au deposit in New South Wales (NSW), Australia. Embedding feature (variable) selection techniques to support vector machines and random forest approaches, followed by application of a wavelet tessellation technique encoded in Data Mosaic™ to the selected variables, delivered more detailed and refined identification of zonation and boundaries within the regolith compared with approaches using only visual core logging and geochemical assays. The method was subsequently applied to geochemical, petrophysical and spectral data acquired from two drillholes in the Delamerian Orogen of western NSW. Several subtle lithological boundaries were detected within the regolith and the interface between weathered profiles and basement rocks at different spatial scales. This included some zones displaying elevated Pb and Zn within the saprock part of the regolith profile. A critical zone above the saprock, highlighted by a high variance interval was also detected using the multivariate wavelet tessellation. This indicated shorter core sampling intervals may be needed to improve the likelihood of detecting mineralisation in this region. The methodology improves the identification of mineralised zones by enabling dynamic drilling adjustments through near real-time knowledge feedback, which also reduces costs and enhances field efficiency.

Self-potential signal processing based on NMF

Abstract In recent years, new algorithms have been continuously applied in the field of geophysical data processing, all of which have achieved good results. However, there is currently no dedicated signal separation method for self-potential field signal processing. In this paper, we propose a self-potential signal separation algorithm based on non-negative matrix factorization (NMF) to perform blind source signal separation. We aim to separate different self-potential signals from the collected mixed signals, laying the foundation for subsequent work such as feature recognition. We utilized analytical formulas of simple polarization bodies and forward modeling procedures to generate a series of self-potential signal data. Subsequently, we conducted numerical simulation experiments for signal separation. The numerical simulation results demonstrate that the proposed algorithm is capable of separating self-potential signals of different models from mixed signals.

The correlation between the active/buried faults and aeromagnetic data in inner and inner-east Anatolia, Turkey

The paper focuses on investigating the active/buried faults in inner and inner-east Anatolia, Turkey based on aeromagnetic data and comparison with the active fault map. This region includes the major tectonic units of Turkey and the largest basins of Turkey (Tuzg.lü Basin (TB) and Sivas Basin (SB)). Thus, the region deserves a detail investigation to delineate the lineaments of the active/buried fault system or the causative sources located in the upper crust. To this end, the region has been divided into two parts as region-1 and 2 including TB and SB, respectively. In this context, the geophysical data processing techniques including power spectrum analysis, high‑pass filter, and second vertical derivative method (SVD) have been applied to the aeromagnetic data of the both regions. Firstly, by utilizing power spectrum analysis, the average depths of the deep and shallow causative sources in the region-1 have been calculated as 11.37 km and 5.01 km whereas those depths are 8.5 km and 3.24 km for region-2. Afterwards, to enhance the responses of the residual anomalies, the high‑pass filter and the SVD method have been applied to the data. Hereby, these potential lineaments produced from the SVD map have been compared with the active fault map to delineate the uncovering buried faults and their lineaments in the region. Contrary to the discussion in the literature, this study revealed for the first time that the Tuzgölü fault zone located in the eastern part of lake does not merge with the Ecemis fault (EF) zone. Furthermore, the study has shown that this fault zone extended from Kayseri city to Sivas city does not junction with North Anatolian Fault Zone in the north, as well.

VELOCITY AND EVOLUTION OF SHOCK WAVES IN SAND WITH INCREASING WATER CONTENT

Interest in the problems of shock wave propagation in saturated porous media is associated with studying seismic exploration issues, modeling the hummer effect during hydraulic fracturing, studying the water-gas impact on formations for the purpose of efficient oil production, etc. Experimental work on waves in bulk media is usually carried out in shock tubes. Traditionally, shock tubes are used to study the characteristics of the propagation of shock waves in various media, to analyze the wave properties of these media based on the speed of the shock waves and the change in the shape of the pulse along the passage of the first – main pulse. In a shock tube equipped with a section of bulk media, the wave is repeatedly reflected from the surface of the porous medium under study and the upper end of the tube. Re-reflected waves can be used to study changes in the environment that occurred under the influence of a shock wave, i.e. as probing pulses. In this article, sounding is understood as identifying acoustic properties (changing the shape of shock pulse diagrams and their velocities). This paper presents the results of experimental studies of the propagation of shock waves of small amplitude in sand with a volumetric content of liquid in the pore space from 0 to 40 %, and illustrates the influence of the presence of liquid in the pores on the shape of the main and probing pulses. The research was carried out using the Shock Tube installation, in the Laboratory of Experimental Hydrodynamics of the Mavlyutov Institute of Mechanics of Ufa Branch RAS. An increase in the speed of wave propagation was established with increasing water saturation of sand in the range from 0 to 40 %. An increase in the amplitude of reflected waves when passing through sand, the formation of peaks and stretching of pulses were discovered. The research results can be used in processing geophysical data to interpret seismograms of sandy deposits saturated with gas-liquid systems.

Machine Learning‐Based Hydrofacies Classification: Effects of Noise and Regularization

AbstractThis study utilizes an unsupervised ML approach, the expectation‐maximization (EM) algorithm using Gaussian Mixture Models (GMM), to integrate near‐surface geophysics measurements for hydrofacies classification. We examined the impact of noise and noise estimation on classification across two synthetic models with varying lateral heterogeneity, simulating and inverting resistivity and seismic data with noise levels ranging from minimal to very high. The algorithm proved robust in accurately reconstructing hydrofacies when noise was correctly estimated or not significantly underestimated, showing minimal misclassification in shallow hydrofacies. However, severe underestimation of noise during inversion led to increased misclassifications and artifact‐laden hydrofacies models, especially in shallow regions. Higher lateral heterogeneity lessened the negative impact of noise, slightly improving algorithm performance when noise was correctly estimated. We also explored the influence of geophysical measurement uncertainties on classification uncertainty through hydrofacies probability maps, noting the greatest impact when noise was underestimated. Additionally, we investigated the effect of the regularization trade‐off parameter on the hydrofacies classification and show how the performance of the algorithm can be evaluated in the absence of ground truth data using the average silhouette score of the classification with data obtained from a basement complex field site. We found that moderate regularization (λ = 200) yielded the best hydrofacies model, as indicated by the highest average silhouette score. Our findings underscore the effectiveness of unsupervised ML for facies classification and emphasizes the critical role of accurate noise characterization in geophysical data processing for enhancing the integration of subsurface heterogeneity information into hydrological models.

Chebyshev polynomial-based Fourier transformation and its use in low pass filter of gravity data

In this paper, we introduce the novel Chebyshev Polynomials Least-Squares Fourier Transformation (C-LSQ-FT) and its robust variant with the Iteratively Reweighted Least-Squares technique (C-IRLS-FT). These innovative techniques for Fourier transformation are predicated on the concept of inversion, and the C-LSQ-FT method establishes an overdetermined inverse problem within the realm of Fourier transformation. However, given the LSQ approach’s vulnerability to data outliers, we note the potential for considerable errors and potentially unrepresentative model estimations. To circumvent these shortcomings, we incorporate Steiner’s Most Frequent Value method into our framework, thereby providing a more reliable alternative. The fusion of the Iteratively Reweighted Least-Squares (IRLS) algorithm with Cauchy-Steiner weights enhances the robustness of our Fourier transformation process, culminating in the C-IRLS-FT method. We use Chebyshev polynomials as the basis functions in both methods, leading to the approximation of continuous Fourier spectra through a finite series of Chebyshev polynomials and their corresponding coefficients. The coefficients were obtained by solving an overdetermined non-linear inverse problem. We validated the performance of both the traditional Discrete Fourier Transform (DFT) and the newly developed C-IRLS-FT through numerical tests on synthetic datasets. The results distinctly exhibited the reduced sensitivity of the C-IRLS-FT method to outliers and dispersed noise, in comparison with the traditional DFT. We leveraged the newly proposed (C-IRLS-FT) technique in the application of low-pass filtering in the context of gravity data. The results corroborate the technique’s robustness and adaptability, making it a promising method for future applications in geophysical data processing.

An alternative 2D ICEEMDAN-based denoising method and its application in processing magnetic anomaly data

Due to environmental noise and human factors, magnetic data collected in the field often contain various noises and interferences that significantly affect the subsequent data processing and interpretation. Empirical Mode Decomposition (EMD), an adaptive multiscale analysis method for nonlinear and non-stationary signals, is widely used in geophysical and geodetic data processing. Compared with traditional EMD, Improved Complete Ensemble EMD with Adaptive Noise (ICEEMDAN) is more effective in addressing the problem of mode mixing. Based on the principles of 1D ICEEMDAN, this paper presents an alternative algorithm for 2D ICEEMDAN, extending its application to two-dimensional scenarios. The effectiveness of the proposed approach is demonstrated through synthetic signal experiments, which show that the 2D ICEEMDAN exhibits a weaker mode mixing effect compared to the traditional bidimensional EMD (BEMD) method. Furthermore, to improve the performance of the denoising method based on 2D ICEEMDAN and preserve useful signals in high-frequency components, an improved soft thresholding technique is introduced. Synthetic magnetic anomaly data testing indicates that our denoising method effectively preserves signal continuity and outperforms traditional soft thresholding methods. To validate the practical application of this improved threshold denoising method based on 2D ICEEMDAN, it is applied to ground magnetic survey data in the Yandun area of Xinjiang. The results demonstrate the effectiveness of the method in removing noise while retaining essential information from practical magnetic anomaly data. In particular, practical applications suggest that 2D ICEEMDAN can extract trend signals more accurately than the BEMD. In conclusion, as a potential tool for multi-scale decomposition, the 2D ICEEMDAN is versatile in processing and analyzing 2D geophysical and geodetic data.

Application of Non-negative Matrix Factorization in Processing Self-potential Signals Caused by Geo-microbe

Microorganisms play a significant role in the evolutionary process of the Earth and are closely related to the modification and evolution of the Earth’s surface circles at different spatial and temporal scales. Given geological microbiology in the self-potential signal data can be represented with non-negative matrix, which makes use of non-negative matrix factorization method to deal with the data become possible. This paper introduces the basic principle of non-negative matrix factorization method, based on non-negative matrix factorization method is discussed to isolate the self-potential signal data in geological microbes may and effect. By separating two natural potential signals containing noise with blind sources, the separation effect is good and the non-negative matrix factorization method is found to be an effective method for extracting their self-potential signal data. Although this numerical simulation is the self-potential signal is introduced in the work of geological microbiology, but this method also has reference significance for other signal data processing, can also be used to other geophysical data processing, the implementation of the research on environmental protection, to improve the cognitive complex biological geological process of shallow earth environment has important significance.

Evaluation of the Possibilities Validation of Interval Velocity Models Using Non-Seismic Data and Its Impact on Geological Interpretation of PreSDM Results

The paper presents the problem of generation and validation of Velocity Interval Depth (VID) models with the application of non-seismic geophysical and geological data. The study area is a part of the Carpathian Foredeep located close to its contact with the Carpathian Overthrust. In this area of complicated geological structure, hydrocarbon deposits have been successfully explored for decades with seismic methods and drilling. The research applied the Simultaneous Joint Inversion (SJI) of independent geophysical data, which is a modern methodology of geophysical data processing, that is still under development. Such an attempt was necessary due to the lack of a sufficiently dense grid of wells in the study area, in which seismic velocities would be correctly recorded. Such data would be then applied for the generation of relevant VID models, which in turn, could be used to perform the Prestack Depth Migration (PreSDM) procedures. The application of procedures taking advantage of independent geophysical and geological data enabled researchers to control the generation process of the spatial VID model in the areas without wells. The analyses aimed to verify the correctness of VID model evaluation and its influence on the quality of seismic imaging in the area of the Carpathian Overthrust. Precisely, the influence was tested of such non-standard generation procedure of seismic velocity fields, not only on the PreSDM results but also on the geological interpretation of both the Rączyna and the Jodłówka gas deposits. The latter aspect of the presented results seems to be crucial to the effectiveness of petroleum exploration in the transition zone between the Carpathian Orogen and the Carpathian Foredeep.

Real and Virtual maps conception in web mapping: a case of cartographic support for geological exploration in Andaman deep water basin

Abstract. The current task of cartographic support for geological exploration and the oil and gas industry is to meet the needs for rapid access to spatial data by specialists. The preparation of specialized data for publication in interactive web maps involves a number of technical issues. Some of them are explored in detail in case of a cartographic support for a cameral processing and interpretation of geological, geophysical and other geoscientific data in Andaman deep water basin. The points highlighted here are in fact a reflection of the role of interactive web maps, regardless of the thematic content, in the development of the Real and Virtual maps concept. The experimental work presented in this article illustrates most of the R/V transformations first developed by H. Moellering in early 1980s. Solving the operations for transformations between real maps, interactive maps, initial (raw) thematic data and cartographic databases will help enrich cartography with new methods of creating and using data, expanding and adapting the communicative conception of cartography to modern realities. An example of the web map developed also shows how the cartographer can simplify the work of professionals in other sectors, their communication with each other through the map language and its web representations. The use of web maps in the poorly studied Andaman deep water basin shows how web maps can contribute to the quality implementation of government programs for increasing exploration and the subsequent development of mineral resources.

Applying Map Filters and Inversion Model for Gravity Data in Matlab-based Application

In general, there are two types of processes using the gravity method, that is the basic processes and the advanced processes. The basic process includes Gravity Meter reading conversion until the gravity corrections process. While the advanced process is a process to put an edge on the geological appearance of the research area that is already in the form of a map. The advanced process includes map filtering and inversion modeling. This advanced processing of gravity data is very useful, one of which is to separate regional anomalies and local anomalies, while inversion modeling is useful for knowing the approximate location of the anomaly depth. What will be applied to the software is advanced processing, because in its application this processing is required in every geophysical research and requires data processing support tools. However, for now, gravity data processing software, especially for the filtering and data modeling process is available as a licensed software. Where not everyone can access it because of limited costs and those who are still in the learning stage in lectures need practicing to process the geophysical data. The purpose of implementing this filtering process and inversion modeling is to provide access to gravity data processing for free and open source so that it can make it easier for students to process the data while practicing in the field, and in the future this software can be the basis for learning and development in the field of geophysical computing. This research was made using a descriptive method with a complete step and explanation of the creating and applying of the geophysical data processing into a software, so the detail processes inside it can be known. A literature study was also conducted to determine the basic formula that will be used as a reference in calculating gravity data in order to obtain the expected processing and modeling results. After that, the final step is to apply all of the components in a program to create a software based on MATLAB for the final result of this research. This software will containing map filtering and inverse modeling for gravity data which can be used for data processing.

Sensing prior constraints in deep neural networks for solving exploration geophysical problems

One of the key objectives in geophysics is to characterize the subsurface through the process of analyzing and interpreting geophysical field data that are typically acquired at the surface. Data-driven deep learning methods have enormous potential for accelerating and simplifying the process but also face many challenges, including poor generalizability, weak interpretability, and physical inconsistency. We present three strategies for imposing domain knowledge constraints on deep neural networks (DNNs) to help address these challenges. The first strategy is to integrate constraints into data by generating synthetic training datasets through geological and geophysical forward modeling and properly encoding prior knowledge as part of the input fed into the DNNs. The second strategy is to design nontrainable custom layers of physical operators and preconditioners in the DNN architecture to modify or shape feature maps calculated within the network to make them consistent with the prior knowledge. The final strategy is to implement prior geological information and geophysical laws as regularization terms in loss functions for training the DNNs. We discuss the implementation of these strategies in detail and demonstrate their effectiveness by applying them to geophysical data processing, imaging, interpretation, and subsurface model building.

Sequential Seismic Anisotropic Inversion for VTI Media with Simulated Annealing Algorithm Aided by Adaptive Setting of Optimization Parameters

As an important geophysical data processing technique, seismic inversion estimates subsurface rock properties with seismic observations. However, anisotropic inversion, intended for a vertical transverse isotropy (VTI) media that primarily describes shale gas/oil resources, suffers from high nonlinearity. Simulated annealing is a widely used global optimization algorithm for solving nonlinear seismic inverse problems, but it involves multiple optimization parameters (e.g., initial temperature, search limit, and perturbation range). The importance of such parameters has been proven whilst the relevant analysis is limited in seismic inversion studies. This work hereby proposes a sequential anisotropic inversion method for VTI media, wherein we combine Bayesian linear and simulated annealing nonlinear inversion schemes. The simulated annealing is featured by adaptive optimization parameters aided by the linear result. Rather than the conventional method, the adaptive setting can be implemented trace by trace for complex reservoirs, which endows the method with enhanced stability and extended applicability. Synthetic tests and practical application demonstrate the validity of the method, wherein the obtained stiffness parameters facilitate the characterization of potential shale reservoirs with an improved accuracy.

Formikoj: A flexible library for data management and processing in geophysics—Application for seismic refraction data

We introduce the open-source library formikoj, which provides a flexible framework for managing and processing geophysical data collected in environmental and engineering investigations. To account for the substantial changes regarding the market shares of operating systems within the last two decades, the library is specifically implemented and tested for cross-platform usage. We illustrate the applicability of the formikoj library for the forward modeling of seismic refraction waveform data with the SeismicWaveformModeler based on a custom subsurface model and survey geometry. We use these synthetic seismic data set to demonstrate the fundamental seismic refraction processing capabilities of the SeismicRefractionManager; thus, illustrating the ability to combine modeling and processing tasks in a single workflow. Based on real 3D field measurements we present the available range of possibilities provided by the formikoj library for the processing of seismic refraction survey data. In particular, we explore different visualization techniques of the seismic traveltime readings to enhance their consistency prior to the inversion with the third-party library pyGIMLi. The low-level access provided by the formikoj library aims at enabling users to implement novel modeling, visualization and processing tools specifically designed for their objectives as well as other geophysical methods.

Diamond-bearing lithosphere of the Siberian platform (based on geophysical data). Precambrian heredity, Paleoproterozoic plume magmatism, diamond content of the Anabar tectonic province

In the first part of the article [15], we presented the results of the analysis of the structural relationship of prospective areas and tectonic zonation of the Siberian Platform (SP). Here we demonstrate the reflection of the heredity of structural-material complexes (SMC) of the Precambrian basement of the SP to the Paleoproterozoic mantle-plume events in the geophysical fields. The analysis of the attributes of the prospective areas, as images of the SMC of the deep Precambrian, made it possible to determine the area of maximum thermal-mantle impact on the SP Precambrian lithosphere of the Early Proterozoic superplume, as well as its presumed center in the northwestern segment of the SP. The spatial distribution of the attributes, revealing the correlation of the components with the prospecting areas, contributed to the refinement of the position of the system of orthogonal lineaments on the SP, in general, corresponding to the framework reported in Basharin’s work [3]. The published geological and geophysical materials and the results of processing geophysical data showed that the deep structure of the central part of the Anabar tectonic province (AN) has the attributes characteristic of the Archean diamondiferous cratons. This can indicate the presence of a diamondiferous lithospheric root within AN. The southwestern segment of AN corresponds with the position of the Angara-Vilyui ore belt (AVRP) [2], which, along with other data, can allow us to extend the ore belt in the northeast direction, as well as recognize it in the rank of the Siberian diamond province. The prospects for the discovery of new industrial-diamond-bearing kimberlite fields are associated with the territory of the AN, the positions of the diamond-bearing lithospheric root, zones of deep crustal-mantle faults within it and its boundaries.

Determination of buried active faults and earthquake potential for Izmir and its surroundings (western Turkey) using aeromagnetic anomalies and seismological data

The paper aims to delineate buried faults in Izmir city and its surroundings, western Turkey using aeromagnetic and seismological data. In this context, the geophysical data processing techniques including reduced‑to‑pole transform (RTP), power spectrum analysis, high-pass filter and second vertical derivative method (SVD) have been applied to the total field aeromagnetic data of the study area. First, to remove the undesirable effects caused by the dipolar nature of the Earth field, RTP transform has been applied to those data. Second, the average depths of the regional and residual sources in the region have been calculated as 16.84 km and 3.75 km, respectively using power spectrum analysis. After, to emphasize the effects of the residual anomalies, the high-pass filter has been applied to the RTP data. Finally, the second vertical derivative method (SVD) has applied to the filtered data for delineating the uncovering buried faults and their lineaments in the eastern part of the Aegean extension. The results from those methods show five major fault zones that could cause devastating earthquakes in the area. Especially, the study reveals for the first time that one of these faults which lies from Doganbey to the city center of Izmir in the literature actually reaches out to Manisa city in the NE direction. As a result, these lineaments can be evaluated as traces of buried faults could be an important clue in predicting earthquake potential. A comparison of seismicity map and the heat flow map shows that the region (between Cesme and Seferihisar) represented with a low b‑value has a high potential earthquake. The spatial distribution of the earthquakes, b‑values and heat flow values in the depths may be related to the existence thin lithospheric mantle. Furthermore, the region represented by strong aeromagnetic anomalies may be considered to be magmatic material arising from the magma filling inside the strike-slip faults. The fault structure observed on the SVD map are also important for the geothermal energy potential of the region as well.

Topographic data in the cartographic support of geological exploration: current state and prospects

The purpose of the current study is an attempt to characterize the scientific and practical issues of modern topographic data preparation and its use in geological exploration. The study is based on the long-term author’s experience in cartographic support of field and cameral geological and geophysical works and on the analysis of modern research in topographical mapping. The specifics of providing access to modern topographic data in the Russian Federation, the Republic of India and the Republic of Colombia, where the main experimental work has been carried out, are briefly described. The content features of the topographic map sheets of these countries are shortly summarized. Practical results of solving such exploration tasks as survey network design, creation of terrain sketch, processing and interpretation of geological and geophysical data, creation of digital terrain models, and preparation of base maps for web services are presented. The prospective directions for further research in improving the use of topographic data in geological exploration are given. It has been found that topographic maps and data are increasingly being used as base layers in the creation of the modern web map services. A balanced and critical approach to the use of global topographic data resources is need for geological exploration as a state’s strategic activity. The industry needs publicly available national multiscale topographic maps as well as theoretical and methodological foundations for the use of web mapping advances in mineral prospecting and exploration.

3-D Forward Modeling of Transient EM Field in Rough Media Using Implicit Time-Domain Finite-Element Method

In a heterogeneous medium (usually called a rough medium) with fractured formations, the propagation of an electromagnetic (EM) field is a type of subdiffusion. Current mainstream geophysical EM data processing methods cannot be applied to data acquired on heterogeneous Earth, as they are not governed by the classic diffusion theory. To evaluate the influence of roughness on the transient EM (TEM) signal for a complex model and contribute to data inversion, we proposed a novel three-dimensional (3-D) forward modeling scheme for TEM in rough media. First, we derived the governing equation with a fractional-order time derivative for the subdiffusion of EM waves in rough media. Then, we proposed a novel time discretization using an unequal step length for the Caputo operator, which significantly reduces the total number of time steps. Finally, an implicit time-domain finite-element method using unstructured tetrahedron discretization was adopted to solve the 3-D forward problem. Furthermore, an efficient time segmentation strategy combined with parallel RHS construction was proposed to accelerate modeling. The numerical results prove that the proposed method is accurate and efficient, and will be a powerful numerical method for analyzing TEM wave propagation and processing TEM data in areas with multiscale fractures or porosity.

Improving the efficiency of processing the results of reservoir filtration studies and parameters when modeling complex oil reserves

The issues of improving the efficiency of processing the results of studies of the filtration properties of reservoirs within the oil and gas producing areas of the central part of the West Siberian oil and gas province are considered. The high degree of development of the hydrocarbon resources of the studied territory is characterized by the presence of long-term developed deposits, which determines the solution of tasks aimed at increasing the success of the search for complex deep-lying reservoirs, the efficiency of their exploration and additional exploration, since the overlying productive horizons are practically developed. This task is one of the most important at the current stage of field development in this region, in the context of falling oil production at the main large fields, and has no unambiguous solution.This article covers the issues of reservoir modeling using new scientific and methodological approaches to the processing of geophysical data and the possibility of using modern software products when grouping development objects according to criteria corresponding to a reservoir of a certain lithotype. This approach allowed us to build high-quality geological models and justify the use of the most effective complex of geophysical studies for modeling low-amplitude (no more than 15 m) and small-sized (less than 20 km2) oil deposits. In the course of research: The results of the reservoir filtration properties were processed; low-amplitude and small-size sediments of channel sediments (river valleys) were established; the industrial oil and gas content of complex sediments characterized by low-amplitude and small-size sediments (Tyumen formation, object Ю2) was proved; The interpretation of geophysical studies of wells was carried out, the results were compared with the energy characteristics of the reflected waves (seismic studies), zones saturated with water-oil-gas fluid were established (3D models were built), and the possibility of using this technique for identifying and mapping complex deep oil deposits was shown.

High-resolution imaging of subsurface infrastructure using deep learning artificial intelligence on drone magnetometry

The use of drones fo r geophysical data acquisition and artificial intelligence (AI) for geophysical data processing, imaging, and interpretation are active focus areas in current industry and academic applications. Unlocking their cumulative potential in single-focus applications can have a transformative impact, possibly leading to dramatic cost reductions in key use cases and new application areas for enhanced actionable business intelligence. We present field study results from Texas and California that show the potential for imaging pipelines and other subsurface infrastructure by using AI-based methods on high-resolution aboveground magnetic data. The superior resolution and interpretability over conventional geophysical inversion is demonstrated. The method has the potential to provide actionable intelligence in several business-use cases for detecting and characterizing pipelines, crossing zones for multiple pipes, etc. at dramatically reduced costs. The advanced algorithms and workflows used resulted in a 100-fold increase in efficiency and delivered results in two days compared to what could take several months using generally available open-source deep learning AI workflows and software. Future direction of development is to validate against excavation-/drill-bit-/inline-tool-based ground truth and further extend and develop this process to deliver near real-time results. The techniques used are general and can be applied to other geophysical data including seismic, electromagnetic, and gravity at various scales and resolution.