Showing papers in "Exploration Geophysics in 2022"
TL;DR: In this article , the authors explore a strategy for interpolating regularly sampled aliased seismic data by incorporating deep external and internal learning, i.e. by combing external pretraining with internal unsupervised fine-tuning.
Abstract: Seismic data reconstruction is an inverse problem in the geophysical community. Deep learning-based methods directly learn the projection between undersampled and complete data from large training datasets. However, when the feature difference between the test and training datasets increases, the recovery performance is degraded. Fine-tuning the pretrained network on the undersampled test field data has been introduced to adapt the trained network to new data. However, the pseudo-labels of the fine-tuning process need to be obtained by some traditional method in advance. In this paper, we explore a strategy for interpolating regularly sampled aliased seismic data by incorporating deep external and internal learning, i.e. by combing external pretraining with internal unsupervised fine-tuning. The pretrained network is obtained from an external synthetic dataset. Then, the pretrained network is fine-tuned on the internal dataset to obtain the final trained network adapting the test data. The inputs and labels of the internal dataset are generated solely from the currently regularly undersampled test data. As such, the fine-tuning process is totally unsupervised. Finally, the interpolated result is acquired by feeding the test data into the trained network. The proposed algorithm learns the external priors from large external datasets and it learns the internal features from undersampled test data. Thus, the network has an enhanced capacity to adapt to new data. Poststack and prestack field data are provided to verify the performance of the proposed algorithm.
2 citations
TL;DR: Wang et al. as mentioned in this paper proposed a seismic structure-constrained inversion of controlled source audio-frequency magnetotelluric (CSAMT) data on a detailed survey and detection of karst caves.
Abstract: Karst cave is a sort of special and buried geological structure that was widely developed in the Permo-Carboniferous coal accumulation area of North China. It brings karst collapse and safety hazard in the mining industry. In this study, we propose a seismic structure-constrained inversion of controlled source audio-frequency magnetotelluric (CSAMT) data on a detailed survey and detection of karst caves. Instead of constrained by seismic impedance, the method in this study directly takes the seismic imaging results as structural constraints, which is different from the cross-gradient technique used by conventional structural constraints. First, the seismic migration section is divided according to the CSAMT inversion grid and applied pixel extraction for each grid. Clustering is carried out according to the structural information interpreted by the seismic migration section and the average pixel value of each cluster is calculated. Then the clustered results were used in the seismic structure-constrained inversion of CSAMT data based on cross-gradient technique. After that, as a karst cave model developed in limestone was established, the study compares the structure-constrained inversions with different clustering strategies shows a much more precision of karst cave detection than the method only applies CSAMT data. Moreover, experimental verification is provided in this study, which is for the detection of a suspected karst collapse column from Shandong Province, China. The comparison results further show that the structure-constrained inversion method proposed in this paper is applicable and may effectively improve the locating accuracy of karst caves.
2 citations
TL;DR: In this article , an analysis of the data recorded passively with a DAS system in a 900m deep well over a period of 12 weeks in the Perth metropolitan area, Western Australia, reveals the presence of several types of ambient energy in the subsurface, such as earthquakes, ocean swell and urban noise.
Abstract: Distributed acoustic sensing (DAS) is an emerging technology increasingly employed to monitor changes of formation properties, production noise and micro-seismic activity, and as an array of sensors in active seismic surveys. The data recorded with the DAS systems are very rich; some features observed in DAS records are often not well understood, and thus are underutilised. A systematic analysis of the data recorded passively with a DAS system in a 900-m deep well over a period of 12 weeks in the Perth metropolitan area, Western Australia, reveals the presence of several types of ambient energy in the subsurface, such as earthquakes, ocean swell and urban noise. In particular, over 85 days of the experiment, the analysis detected sixteen earthquakes, with epicentres ranging from 126 km to 900 km (for the local events) and from 2300 km to 6400 km (for the remote events). Signals with frequencies below 0.9 Hz are dominated by the oceanic swell. The recorded urban noise includes mine blasting, machinery and traffic. The experiment shows the ability of DAS to detect these events and as such is potentially useful for subsurface characterisation and monitoring.
2 citations
TL;DR: In this paper , a least-squares objective function in terms of numerical and exact integrals is proposed to improve the accuracy of the spectral-element method with orthogonal Legendre polynomials.
Abstract: The spectral-element method (SEM), which combines the flexibility of the finite element method (FEM) with the accuracy of spectral method, has been successfully applied to simulate seismic wavefields in geological models on different scales. One kind of SEMs that adopts orthogonal Legendre polynomials is widely used in seismology community. In the SEM with orthogonal Legendre polynomials, the Gauss-Lobatto-Legendre (GLL) quadrature rule is employed to calculate the integrals involved in the SEM leading to a diagonal mass matrix. However, the GLL quadrature rule can exactly approximate only integrals with a polynomial degree below 2N-1 (N is the interpolation order in space) and cannot exactly calculate those of polynomials with degree 2N involved in the mass matrix. Therefore, the error of the mass matrix originating from inexact numerical integration may reduce the accuracy of the SEM. To improve the SEM accuracy, we construct a least-squares objective function in terms of numerical and exact integrals to increase the accuracy of the GLL quadrature rule. Then, we utilise the conjugate gradient method to solve the objective function and obtain a set of optimal quadrature weights. The optimal mass matrix can be obtained simultaneously by utilising the GLL quadrature rule with optimal integration weights. The improvement in the numerical accuracy of the SEM with an optimal mass matrix (OSEM) is demonstrated by theoretical analysis and numerical examples.
1 citations
TL;DR: In this paper , the objective functions of the first-order approximate exponential frequency FWI (FRE-EFWI) in elastic waves and the source terms of its back propagation formula were derived.
Abstract: The weak signals of artificial seismic records contain the subsurface medium information that is required in the inversion. But in the full waveform inversion (FWI), the weak signals contribute less to the objective functions. Therefore, how to improve the contribution of the weak signals in the objective functions of FWI is the problem that needs to be solved urgently. The research shows (Ren, D. 1980. Preliminary research on seismic record and instantaneous frequency. Oil Geophysical Prospecting 15 no. 1: 7–21) that instantaneous frequency attributes, which are very sensitive to the changes in subsurface velocity, have the potential to extract the weak signals from the seismic records. However, this frequency can only be estimated from the complex seismic signals. Empirical mode decomposition (EMD) method has been widely used in signal analysis so as to estimate the instantaneous frequency, but it is difficult to be applied in FWI due to the huge computation. In order to solve this problem, the instantaneous frequency is replaced with the first-order approximation of the exponential frequency in FWI. In this paper, the objective functions of the first-order approximate exponential frequency FWI (FRE-EFWI) in elastic waves and the source terms of its back propagation formula were derived. Besides, the FRE-EFWI method was proved to improve the contribution of the weak signals in the objective functions of FWI. In addition, the correctness and effectiveness of the method were demonstrated by the examples of FWI.
1 citations
TL;DR: In this article, the radioactive heat production (RHP) values of granitoid intrusions have been investigated for geothermal heat exploration, as granite is a major host for Heat-Producing Elements (HPE; U, Th & K).
Abstract: Granitoid intrusions traditionally form a focus for geothermal heat exploration, as granite is a major host for Heat-Producing Elements (HPE; U, Th & K). Airborne spectral gamma-ray data for the study area highlight variations in HPE abundances in granitic rock units, indicating variation in the Radioactive Heat Production (RHP) values of these rocks. The computed arithmetic means of RHP for granitic rocks range from 0.96 µWm−3 for tonalite-quartz diorite to 1.10 µWm−3 for granodiorite, followed by a gradual increase to 1.52 µWm−3 for monzogranite and 2.51 µWm−3 for alkali-feldspar granite. The major control on the distribution of U and Th elements in the granitoid rocks appears to have been primarily of magmatic differentiation and is reflected in the linear correlation between these elements. Besides, subsequent post-magmatic hydrothermal fluids play their important roles in remobilization of profitable secondary U-mineralizations to be trapped and enrichment in the alkali-feldspar granitic rocks.
1 citations
TL;DR: In this paper , a domain adaptation technique was applied to the convolutional neural network (CNN)-based moment tensor inversion method, which uses peak amplitudes and arrival times of P- and S-waves as input features.
Abstract: Microseismic monitoring is widely used to analyze the locations and growth directions of fractures formed at sites of hydraulic fracturing treatment and CO2 geologic sequestration. Because moment tensors can provide focal mechanisms, moment tensor inversion has received considerable attention in microseismic monitoring; the real-time processing of moment tensor inversion is important for rapid decision-making. Pre-trained machine learning (ML) models can make nearly instantaneous predictions in the application stage and thus present an attractive alternative to real-time processing. However, prior information regarding the velocity model at the target site is a prerequisite for generating the dataset used to train the ML model that is applied in moment tensor inversion. In addition, it is difficult to create the training dataset because it requires three-dimensional numerical modelling when the velocity model is complex; numerous simulations must be executed for sources with various locations and moment tensors. To overcome these limitations, we applied the domain adaptation technique to the convolutional neural network (CNN)-based moment tensor inversion method, which uses peak amplitudes and arrival times of P- and S-waves as input features. The CNN model was pre-trained with the dataset generated from a homogeneous velocity model. Then, in the domain adaptation stage, the pre-trained model was fine-tuned along with the target dataset. To validate the performance of the domain adaptation, moment tensors from both horizontal and tilted three-layer models were predicted. In each case, the domain-adapted model performance was similar to the performances of the CNN-based models that had been trained using the dataset generated with the exact target velocity models.
1 citations
TL;DR: Li et al. as discussed by the authors used the model-based acoustic impedance (AI) inversion method that utilizes seismic and logging data to improve the inverse resolution and accuracy of predicting reservoir thickness, and they showed that comprehensively using intermediate-frequency seismic information and high-lowfrequency logging data greatly broadens the seismic data frequency band and improves the dominant frequency of the reflected wave.
Abstract: The Permian coal seams in eastern Yunnan and western Guizhou are thin, numerous, and staggered with other thin coal seams. Depicting the fine characteristics of coal reservoirs is pivotal for the safe and efficient exploitation of coal and coalbed methane (CBM), and is important for transparent mining. To improve the inverse resolution and accuracy of predicting reservoir thickness, this study used the model-based acoustic impedance (AI) inversion method that utilizes seismic and logging data. This method changes seismic data, reflecting stratigraphic interfaces, into AI data, reflecting lithologic structures. Moreover, it avoids the relevant assumptions of wavelets and reflection coefficients. Compared with other inversion methods, model-based AI inversion strengthens the description of thin reservoir horizontal and vertical changes. The results showed that comprehensively using intermediate-frequency seismic information and high-low-frequency logging data greatly broadens the seismic data frequency band and improves the dominant frequency of the reflected wave. Furthermore, the AI profile resolution and the prediction accuracy of the physical parameters for the target geological body can be improved. A cross-validation comparing the inverted thickness and measured thickness of borehole cores was applied to achieve fine prediction (error of appropriately 0.02–0.4 m), providing a basis for CBM development.
1 citations
TL;DR: In this article , the authors proposed a frequency-domain inversion method of the transmitting channel wave that directly uses the frequency shift characteristics of the channel wave to estimate the Q value of the coal channel, which offers a new strategy in the data processing of channel wave.
Abstract: Currently, the transmitting channel wave technique mainly uses the attenuation coefficient of the channel wave total energy to explore the geological structure of the coal seam face. In the case of weak geophone coupling and intense geological anomaly, the channel wave energy will be attenuated severely, which significantly affects the stability and accuracy of the result. The Q value of the coal channel is a critical parameter to evaluate the energy attenuation characteristics of the channel wave. The Q value is typically estimated by using the attenuation coefficient of the body wave, but the special coal channel model hinders the estimation of the Q value of the coal seam. According to the linear attenuation characteristics of the centroid frequency of the transmitting channel wave, a new method was proposed to assess the quality factor (Q) of the coal channel by using the centroid frequency change of the channel wave signal. The expected frequency was calculated as its centroid frequency according to the energy ratio of each frequency point through the spectral analysis of the channel wave signal. Combined with the transmission tomography technology, the imaging of the coal seam face based on the transmitting channel wave Q value was established. According to the sudden change of the Q value of the coal channel near the geological structure of the coal seam face, a geological interpretation method based on the abnormal Q value was proposed. The two-dimensional numerical simulation demonstrated that the centroid frequency of the transmitting channel wave signal decayed linearly with the propagation distance and the geological structure increased the frequency shift. Furthermore, three-dimensional numerical simulation validated the feasibility and effectiveness of the Q value inversion method. Field Experimental results showed that the algorithm exhibited improved stability and accuracy. This work proposed a novel frequency-domain inversion method of the transmitting channel wave that directly uses the frequency shift characteristics of the channel wave to estimate the Q value of the coal channel, which offers a new strategy in the data processing of channel wave.
1 citations
TL;DR: In this paper , a triple pore structure was adopted to divide the pore space into equant, intermediate and compliant pore structures, which can better describe the pressure dependence of the elastic moduli of rocks.
Abstract: The pressure dependence of elastic parameters of rocks is mainly controlled by the geometry of the pore space. In general, the compliant-stiff pore structure model can be used to reasonably describe this pressure dependence. However, our experiment measurements revealed that for tight sandstone rock with complex pore structures, the contribution of the compressibility of the stiff pores to the elastic modulus is significant. The dual porosity is not sufficient to explain the variation of ultrasonic velocity with pressure. For this reason, we adopted a triple pore structure to divide the rock pore space into equant pores, intermediate pores and compliant pores. Our laboratory measurement and model results show that this pore space division can better describe the pressure dependence of the elastic moduli of rocks. The low-frequency stress–strain measurements show that the fluid-saturated tight sandstone has obvious dispersion in the seismic frequency band, which is primarily attributed to the squirt flow effect. In order to study the pressure and frequency dependence of the elastic moduli of tight sandstone, we retrieved the geometric parameters of the pore structure from the pressure variation of the ultrasonic velocities under dry conditions. Based on this complex pore structure and the extension of the squirt flow model, we constructed an elaborate rock physics model to explain the pressure and frequency dependence of velocity. The model does not require adjustable parameters, and all parameters are measured and calculated by the laboratory, which improves the accuracy of theoretical modelling. The modified squirt flow model can be used to describe dispersion and attenuation in a wide frequency band, and fit well with the velocity measurements in both the low-frequency range and the ultrasonic frequency range under different pressures. Therefore, this rock physics model could be applied in the extraction of pore microstructure and fluid properties provided elastic moduli or velocities can be estimated accurately.
1 citations
TL;DR: In this paper , a cross-validation technique is used as a tool to diagnose and evaluate the performance of time-depth conversion at/away from well controls to predict the depth of Top Hartha and Zubair reservoirs using the dataset of East Baghdad Oil Field.
Abstract: The time-depth conversion process is a significant task in seismic interpretation to establish the link between geophysical information in the time domain and geological information in the depth domain at/away from well locations. Selecting the suitable velocity model for time-depth conversion to generate an accurate depth map is difficult if the accuracy of these models is unknown. In the current study, the cross-validation technique is used as a tool to diagnose and evaluate the performance of time-depth conversion at/away from well controls to predict the depth of Top Hartha and Zubair reservoirs using the dataset of East Baghdad Oil Field. To test this technique, four common velocity model approaches used for time-depth conversion with different scenarios of velocity parameters (initial velocity V 0 and depth gradient (K)) were applied to produce ten velocity models (1–10). According to the gradient variation of velocity with depth, check shot analysis, the velocity models (1–10) include three key velocities layer-cakes: Layer 1 (Middle Miocene-Upper Cretaceous), Layer 2 (Upper Cretaceous), and Layer 3 (Lower Cretaceous) with 18 horizons from Middle Miocene down to Lower Cretaceous. The cross-validation analysis reveals that the velocity model with a variable surface initial velocity and constant depth gradient (Model 9) was the most accurate with fewer mistie between actual and predicted depth. Consequently, this model is used to construct the depth map of the Hartha and Zubair reservoirs. Finally, this study progresses a workflow that can be applied to the region with any geological setting to investigate time-depth conversion uncertainty.
TL;DR: In this article , the authors compared historical 2D seismic surveys and found two seismic acquisition parameters that have the greatest influence when imaging beneath mafic igneous rocks in offshore and onshore basins from Australia's Northwest Shelf.
Abstract: Mafic igneous units within sedimentary basins can be widespread and severely attenuate seismic reflection data. Attenuation obscures imaging of sub-igneous sedimentary units, impeding exploration in prospective and frontier basins. This study compared historical 2D seismic surveys and found two seismic acquisition parameters that have the greatest influence when imaging beneath mafic igneous rocks in offshore and onshore basins from Australia’s Northwest Shelf. These parameters were found by using a 3D model developed with integrated 2D seismic and well data in the Browse, North Carnarvon, Onshore and Offshore Canning basins. Simultaneously comparing the 2D seismic lines in 3D space revealed that the surveys with the longest, streamer length and the most receivers are the most effective at imaging beneath igneous units. Additionally, we identified potential depocenters obscured by igneous horizons from a regional basement map. These depocenters correlate with older basins that are infilled by pre-rift, Paleozoic sediment and capped by mafic igneous rocks formed during late Permian-Mesozoic rifting events. Much of the Northwest Shelf maintains a frontier status, but exploration outcomes can be improved. Therefore, maximising streamer length and number of receivers to future seismic surveys can result in more effective exploration opportunities in basins with known igneous occurrences.
TL;DR: For a vertical magnetic dipole (VMD) on or under the surface of a conductive half-space, explicit analytic formulae, not Hankel transform expressions, have been derived for the transient electric field induced below the ground, and the corresponding Hertz potential as discussed by the authors .
Abstract: For a vertical magnetic dipole (VMD) on or under the surface of a conductive half-space, explicit analytic formulae, not Hankel transform expressions, have been derived for the transient electric field induced below the ground, and the corresponding Hertz potential. These formulae permit rapid calculation of surface and underground dB/dt and B-field components, as well as of the induced current distribution. The solution allows the current produced by the surface reflection to be isolated, revealing how the interaction with the ground surface is responsible for the downward diffusion of the smoke ring. The mathematical form of the solution has also permitted confirmation of a prediction that the current distribution from a buried dipole in the limit of late time is a scaled version of the current distribution produced by a VMD on the ground surface.
TL;DR: In this article , a modified staggered-grid finite-difference (M-ESG) scheme was proposed to accelerate the wavefield simulation process while preserving or even improving the modelling accuracy.
Abstract: Compared with the standard staggered-grid finite-difference (FD) methods, equivalent staggered-grid (ESG) ones can significantly reduce the computational memory for acoustic wave modelling in the variable-density media. To further enhance the simulation efficiency and accuracy, one way is to optimize the FD coefficients, another way is to design new FD stencils. In this paper, we propose a modified ESG (M-ESG) scheme which can significantly accelerate the wavefield simulation process while preserving or even improving the modelling accuracy. We calculate the FD coefficients by approximating the temporal and spatial derivatives simultaneously based on time–space domain (TS-D) dispersion relation of the discrete wave equation. Our M-ESG scheme in the TS-D can maintain basically the same accuracy as the conventional ESG (C-ESG) one when the FD coefficients are derived by the Taylor-series expansion (TE) approach. Note that the TS-D dispersion relation is nonlinear with respect to the FD coefficients of the C-ESG scheme, so it is difficult to obtain the optimized FD coefficients for the discrete wave equation. However, we can minimize the L2-norm error of the dispersion relation based on our M-ESG scheme to implement a linear FD coefficients optimization strategy, which is easy and efficient. Comparisons with TE- and optimization-based C-ESG schemes demonstrate the accuracy, stability, and efficiency superiorities of our TE- and optimization-based M-ESG ones.
TL;DR: In this paper , the authors delineated subsurface features that affect the configuration of reservoirs in the Abu Gharadig basin using an integrated interpretation of potential field and seismic reflection data.
Abstract: The current study aims to determine the basement configuration and basement-related structural elements of the Abu Gharadig basin.: We delineated subsurface features that affect the configuration of reservoirs in the study area using an integrated interpretation of potential field and seismic reflection data. The study area lies in the North-Western Desert of Egypt to the east of the Qattara Depression, between latitudes 29° 00’ and 30° 00’ N and longitudes 28° 00’ and 30° 00’ E. Gravity data interpretation delineates shallow features, with NNE-SSW as the major trend and NW-SE as the minor trend. Given that the Euler structural index is approximately zero, these trends probably represent major faults with steep dips and large throws, which juxtapose considerable thicknesses of rocks with contrasting magnetization. On the other hand, the most common tectonic trends prevailing in the deeper levels are the NEN-SWS and NW-SE as the major trends and ENE-WSW as a minor trend. At the same time, the dominant tectonic trend from the Euler solution is NNW-SSE as a major trend and NNE -SSW and WNW-ESE as minor trends. The interpretation of magnetic data indicates the study area dissect by different trends where the trends of shallow features are NNW-SSE as a major trend and E-W as a minor trend. On the other hand, the most common tectonic trends prevailing in the deeper levels are the NNE-SSW and WNW-ESE as major trends and E-W, ENE-WSW, NEN-SWS, and NWN-SES as minor trends. At the same time, the dominant tectonic trend from the Euler solution is N-S as a major trend and NW-SE and NE-SW as minor trends. In the study area, the depth to the top of the basement rocks ranges from 1731.7 m to more than 4736.6 m. Main faults only affect the Lower and Upper Cretaceous sequences, according to seismic interpretation, and appear to be in two trends, the NW-SE and NWN-SES. These structural trends affect the configuration of oil reservoirs in the study area. The study area contains valuable reservoirs according to boreholes drilled in the stud area.
TL;DR: In this article , a solution set strategy was added to the asynchronous MMC parallel simulated annealing (PSA) algorithm for the first time to overcome the low computational efficiency in SA inversion of Transient Electromagnetic (TEM) data.
Abstract: This paper focuses on low computational efficiency in simulated annealing (SA) inversion of Transient Electromagnetic (TEM) data. Asynchronous multiple Markov chains (MMC) parallel strategy is a very promising SA acceleration method, which can be accelerated almost linearly. However, this method also reduces the accuracy of the solution. To overcome this problem, we added the solution set strategy to the asynchronous MMC parallel simulated annealing (PSA) algorithm for the first time. In this new algorithm, each thread independently searches for direction and exchanges data with the solution set in the shared memory. We used both the synthetic and field data to test the new algorithm. The synthetic data tests showed that the MMC PSA results are better than those of the original MMC PSA. We analyzed the efficiency of the new algorithm. Compared with the sequential VFSA, the maximum speedup of the new algorithm is approximately 10 times. The field data test also showed that the improved MMC PSA algorithm has good practicability. These tests demonstrate that the improved algorithm is effective, showing that its convergence speed is greatly improved without reducing the accuracy.
TL;DR: In this paper, the estimated pattern denoising (EPD) wavelet transform was proposed for random noise attenuation in geophysical data, which combines the capability of the Gaussian filter and dual-tree rational dilation wavelet Transform (DT-RADWT) in random noise detection and suppression.
Abstract: This paper introduces the estimated pattern denoising (EPD) wavelet transform for random noise attenuation in geophysical data. The proposed approach combines the capability of the Gaussian filter and dual-tree rational dilation wavelet transform (DT-RADWT) in random noise detection and suppression; we called this method Estimated Pattern Denoising (EPD). The EPD is an innovative approach in terms of estimation of the location and amplitude of the noise pattern, directly from the data. The employed approach produces a higher quality factor (Q-factor) than the conventional dyadic discrete wavelet transform (DWT) and separates the noise from the signal with higher accuracy. The EPD provides a data-driven scheme that resolves the complexity of the random noise model in noise suppression, using an auxiliary Gaussian filter. This approach does not require prior information about the noise source, statistical distribution, or frequency range. We show successful suppression of random noise using the proposed approach on synthetic and real field data.
TL;DR: In this article , the authors show the application of the EMD for demarcating the zones of gas-hydrates and free-gas bearing sediments in the Mahanadi basin of the eastern Indian margin.
Abstract: Empirical mode decomposition (EMD) is an effective tool for signal analysis that splits the data into individual modes, called the intrinsic mode functions, which are associated with symmetric and narrow-band waveform ensuring that the instantaneous frequencies are smooth and positive. However, some negative features encumber its direct application namely the mode mixing and splitting, aliasing and endpoint artefacts. Two variants, ensemble EMD (EEMD) and complete ensemble EMD (CEEMD) have been recently introduced to overcome these problems. We intend to show the application of the EMD for demarcating the zones of gas-hydrates and free-gas bearing sediments. Gas-hydrates are ice-like crystalline substances that occur in shallow sediments along the outer continental margins and in the permafrost regions, and are considered as viable major future energy resources of the world. Gas-hydrates in marine environment are generally identified by an anomalous reflector, known as the bottom simulating reflector, on seismic section. The present study demonstrates that the EMD can be effectively utilised in demarcating the zones of gas-hydrates and free-gas bearing sediments with a field example in the Mahanadi basin of the eastern Indian margin.
TL;DR: In this paper , the authors compared complex resistivity results with geological characteristics of epithermal Au-Ag mineralisation and confirmed by drilling cores in three dimensions, through a step-by-step clustering analysis, to identify the boundary between the target and background.
Abstract: Electrochemical reactions at the interface between groundwater and sulphides are remarkable. Sulphides in mineralised zones are relatively abundant compared to hydrothermal alteration zones and host rocks. Complex resistivity is a geophysical tool for visualising difference between various subsurface electrochemical reactions. The epithermal Au–Ag mineralisation at Moisan hill (South Korea) occurs in the extensively disseminated pyrite zone, a typical feature of advanced argillic and argillic alteration zones. The epithermal vein at Moisan had a strike length of >500 m horizontally and approximately 300 m vertically and was controlled by the WNW fault zone. In this context, the deposit was subjected to a test bed to demonstrate the applicability of the complex resistivity survey for mineral exploration. To compare complex resistivity results with geological characteristics of epithermal mineralisation, we visualised the complex resistivity survey results and Au–Ag mineralised zones confirmed by drilling cores in three dimensions. The quartz veins of the targets showed high resistivity and a strong phase response; however, both the alteration zones and host rocks showed lower resistivity and a weaker phase response than the target zones. Through a step-by-step clustering analysis, a simple map integrating both kinds of the geophysical models was generated, to identify the boundary between the target and background. Geologic survey and drilling investigations indicate that the target is well-localised in a mineralised zone. The complex resistivity survey is a useful tool for exploring epithermal Au–Ag deposits.
TL;DR: In this paper , a method of using bidirectional long short-term memory (LSTM) to solve the problem of anomaly identification in marine controlled-source electromagnetic data was proposed.
Abstract: The magnitude versus offset (MVO) curve, a type of frequency domain marine controlled-source electromagnetic data, is the most common way to identify electromagnetic anomalies in oil and gas reservoirs. However, in actual exploration, it can be difficult to identify the boundary of the high resistance anomaly when there are response signals of multiple emission frequencies. Also, the noise would reduce the accuracy of manually detecting electromagnetic anomalies. The robustness of the bidirectional long short-term memory (LSTM) network is relatively strong, and the LSTM neural network would get the most out of the sequence information of the data for feature extraction purposes and to achieve automatic classification and identification. Therefore, this paper proposes a method of using bidirectional LSTM to solve the problem of anomaly identification in marine controlled-source electromagnetic data. The LSTM unit was applied to establish anomaly identification models of single-layer LSTM, two-layer LSTM, and bidirectional LSTM, respectively. In this paper, theoretical data were calculated by a one-dimensional uniform layered medium model, and the synthetic noise data were constructed by adding random noise with different signal-to-noise ratios. The three types of models were trained, verified, and tested, respectively, to compare the accuracy of electromagnetic anomaly identification. According to the comparison, a conclusion can be drawn that the bidirectional LSTM model suggests the best manifestation of learning the characteristics of the sample. Its electromagnetic anomaly identification accuracy reached 100% in the theoretical dataset and 79.58% in the synthetic noise dataset.
TL;DR: In this paper, a 2D frequency-domain acoustic FWI technique using a 9-point FDM-based modeling scheme that includes an embedded boundary method was developed. But the authors also showed that the EBM-based FWI is able to estimate subsurface velocity distributions even though the model has irregular topography, which spoils the result of the conventional FWI.
Abstract: In the implementation of full waveform inversion (FWI) to identify subsurface velocity distributions with land seismic data, which are often acquired in regions with irregular topography, wave equation-based modelling requires caution. In particular, when using the finite difference method (FDM), unwanted scattered waves are generated because irregular surfaces crossing a rectangular grid are discretized via a staircase approximation; hence, if the problems caused by this staircase approximation are disregarded, FDM-based FWI may fail due to the presence of undesirable wavefields. To resolve this problem, this study develops a 2D frequency-domain acoustic FWI technique using a 9-point FDM-based modelling scheme that includes an embedded boundary method (EBM). This study suggests a workflow for the whole EBM-based FWI process from the calculation of coefficients for the EBM-based 9-point FDM modelling to applying it to FWI for proper velocity updates. In numerical examples, using velocity models with a tilted surface and an arbitrarily fluctuating surface, we synthesize seismic data and verify the accuracy of EBM-based 9-point FDM modelling and its superiority over the conventional FDM by comparing it with wavefields derived from the spectral element method. Then, we show that our EBM-based FWI is able to estimate subsurface velocity distributions even though the model has irregular topography, which spoils the result of the conventional FWI.
TL;DR: In this article , an inverse filtering scheme that can compensate absorption and dispersion caused by intrinsic attenuation in subsurface media with a heterogeneous model is presented, which can suppress highfrequency noise at the same time, one is to design a compensation operator with a fixed gain limit, and the other is to introduce an adaptive frequency-varying band calculation method.
Abstract: We have presented an inverse filtering scheme that can compensate absorption and dispersion caused by intrinsic attenuation in subsurface media with a heterogeneous model. We have adopted two methods to suppress high-frequency noise at the same time, one is to design a compensation operator with a fixed gain limit, and the other is to introduce an adaptive frequency-varying band calculation method. We use VSP data and seismic velocity data to estimate model of the whole work area in a unique way. The proposed scheme can be incorporated into conventional seismic data processing workflow. Tests on synthetic and real data set demonstrate effectiveness of the proposed inverse filtering.
TL;DR: In this paper , a cascade of de-multiple methods were tested to attenuate multiple energy under various seafloor bathymetry and tectonic areas, and a spatial dependent predictive deconvolution was performed in the x-t domain.
Abstract: Reducing multiple contaminations in reflection seismic data remains one of the primary challenges in marine seismic data processing. Besides geological settings, its effectiveness is also dependent on the multiple removal methods. In this study, we undertook two legacy 2D multi-channel seismic data crossing the accretionary wedge off SW Taiwan to test the efficiency of various multiple-attenuation scenarios. The tectonic domain has resulted from the incipient arc-continent collision between the northern rifted margin of the South China Sea and the Luzon volcanic arc. The wedge extends from shallow water to deep water bathymetries, hence promoting both short-period and long-period multiples within the seismic records. A cascade of de-multiple methods was tested to attenuate multiple energy under various seafloor bathymetry and tectonic areas. The first step relies on the periodicity nature of multiples. Spatial dependent predictive deconvolution in the x-t domain was performed to attenuate reverberations and improve temporal resolution in the time domain. Wave-equation multiple attenuation (WEMA) was applied to suppress the water layer multiples based on a combination of numerical wave extrapolation in the shot domain through water layer and water bottom reflectivity. Surface-related multiple elimination (SRME) aimed to attenuate the residual water bottom multiple and peg-leg multiple by assuming surface-related multiples can be kinematically predicted via convolution of pre-stack seismic traces at possible surface multiple reflection locations. The second step exploits the spatial move-out difference behavior between primaries and multiples. Parabolic Radon transforms far-offset multiples by subtracting noise energy in the τ-p domain, whereas the frequency-wave number (F-K) filter aimed to eliminate any residual multiples energy in the F-K domain. Predictive deconvolution improved seismic resolution and suppressed sea-bottom reverberation energy in the continental and lower wedge slopes, but not in the upper wedge slope. WEMA, Radon filter, and F-K filter reduced multiples energy both at the continental slope and wedge slope; whereas SRME made minimal impact on both areas. Since the reflection seismic datasets stretch diverse tectonic environments and water depth, there was no single multiple attenuation method capable to suppress multiples in all tectonic environments and bathymetry.
TL;DR: In this article , the authors evaluate the effectiveness of coherent noise clustering in reconstructing leaked signals after conventional noise attenuation filters using Generalised Auto Regressive Conditional Heteroskedasticity (GARCH) model.
Abstract: ABSTRACT The main purpose of this research is to evaluate the effectiveness of coherent noise clustering in reconstructing leaked signals after conventional noise attenuation filters. We use Generalised Auto Regressive Conditional Heteroskedasticity (GARCH) model. We apply clustering, conditional variance, and conditional standard deviation analysis to synthetic and experimental seismic field data. The conditional variance and conditional standard deviation of coherent noises that are attenuated by the Ormsby and f-k filter are calculated. Each cluster is labelled using the two-dimensional average clustering method and then leaked signals are reconstructed from the initially filtered data to improve the signal-to-noise ratio. Results show that the proposed method mostly reconstructs the leaked signals after conventional filters.
TL;DR: Wang et al. as discussed by the authors proposed a new attribute (DI) to discriminate the hydrocarbon-associated anomalies and predict the reservoir parameters including porosity and water saturation quantitatively in Upper Gumai formation of W field, South Sumatra Basin.
Abstract: Reservoir characterization and fluid discrimination based on seismic reflection amplitude play important roles in seismic exploration industry. Stable fluid-sensitive attributes from seismic data can help reduce uncertainties of hydrocarbon prediction in interwell locations and increase the reliability of drilling plans. In this study, in combination with seismic AVO inversion impedance and the rock physics template analysis, we proposed a new attribute (DI) to discriminate the hydrocarbon-associated anomalies and predict the reservoir parameters including porosity and water saturation quantitatively in Upper Gumai formation of W field, South Sumatra Basin. The new attribute (DI) is constructed using a set of combined impedances derived from prestack seismic inversion with the constraint of rock physics. Numerical modelling based on patchy-saturated model was implemented to test the sensitivity and stability of the new attribute and results showed that the DI attribute can predict the existence of hydrocarbon-filled sands with less ambiguity. With known well log data in W field, a feasibility study including cross-plotting and histogram methods was carried out and concluded that the DI attribute contributes higher resolution in distinguishing the hydrocarbon-filled sands from the background trend. In the process of quantitative interpretation, the DI attribute shows a good regression relationship with porosity and water saturation properties within the hydrocarbon sands with the correlation coefficients reaching 92% and 85%, respectively. By using seismic AVO inversion impedance, combining the application of the DI attribute and Vp/Vs ratio for lithology and fluid contents discrimination was conducted to improve the reservoir prediction accuracy in the field. Application results show that low values of the DI attribute (<18,000 m/s.g/cc) was indicative of hydrocarbon-filled sands effectively while Vp/Vs ratio presented a higher resolution in separating wet sand, dry-sand from shale. By using the linear regression relationship derived from cross-plotting analysis with well data, we calculated the volumes of porosity and water saturation from DI attribute and successfully screened out the hydrocarbon accumulation distribution, which reveals the potential zones of exploration interest in South Sumatra Basin.
TL;DR: In this paper , a new method for calculating the precise subsurface velocity structure from ground penetrating radar (GPR) reflection data that does not require boreholes or log data is presented.
Abstract: Adequate knowledge of velocity is required for accurate data imaging and depth conversion, as well as for quantifying the distribution of soil water content. Without complementary borehole information in the form of dielectric permittivity and/or porosity logs along the profile, it is currently impossible to reliably estimate the high-frequency electromagnetic velocity distribution in the probed subsurface region. Here, we present a new method for calculating the precise subsurface velocity structure from ground penetrating radar (GPR) reflection data that does not require boreholes or log data. This study investigates the ability of the pulse_EKKO PRO GPR system to predict a vertical profile for the possible velocity estimation of a layered and contaminated geophysical test site in Hangzhou, China. All data were acquired and saved on the GPR system in various files (projects) before analysis using GPR software to obtain approximated velocity modelling using common midpoint (CMP) gathers. Using the velocity spectrum analysis, a vertical profile of the interval velocities can be derived from each CMP gather. The findings of this study indicate that the proposed method is effective and sustainable. Furthermore, owing to the efficacy of the method in terms of field effort and computational complexity, it can easily be expanded to 3D GPR velocity exploration, increasing its importance in comparison to standard offset-based techniques for estimating velocity using GPR.
TL;DR: In this paper , a dictionary combination (shearlet + DCT) under the morphological component analysis (MCA) framework was used to obtain the optimal solution to obtain reconstruction results.
Abstract: The reconstruction of data is a critical preliminary work in the seismic data processing. Compressed sensing (CS) has been well applied in the field of reconstruction. The key point of CS is random sampling, which converts the mutual interference alias caused by regular undersampling into lower-amplitude outside noise. But traditional sampling methods lack constraints on sampling points, emerging too much alias. Segmented random sampling (SRS) effectively controls the distance between sampling points. On the other hand, a single mathematical transformation will lead to incomplete sparse expression and bad restoration effects. Morphological component analysis (MCA) decomposes a signal into several components with outstanding morphological features to approximate the complex internal structure of data. In this paper, we found a new dictionary combination (shearlet + DCT) under the MCA framework and used the block coordinate relaxation algorithm to get the optimal solution to obtain reconstruction results. Tests of 2D data and 3D data have proved that the proposed method can get a better effect when reconstructing the SRS data.
TL;DR: In this article , a multi-attribute framework was proposed to detect subtle faults in 3D seismic data obtained from the Krishna-Godavari (KG) basin, with results displayed on synthetic and real datasets.
Abstract: This study improves a collection of attributes to detect subtle faults in three dimensional data obtained from the Krishna-Godavari (KG) basin, with results displayed on synthetic and real datasets. Seismic attributes, for instance, curvature and coherence, are often used to delineate discontinuities, such as faults and fractures where hydrocarbons may have been trapped. These attributes have their advantages subjective to the seismic data. In this paper, we propose a multi-attribute framework for identifying subtle faults inside seismic volumes. Curvature attribute is a powerful and popular technique to deal with these faults. The faulted horizon is fitted on the quadratic surface using the least-square method, and the most positive and most-negative curvature attributes are calculated, which are further used in saliency map calculations. Several signal processing techniques, such as Hough transform and ant tracking, have been used to delineate faults. Here, we have proposed a novel signal processing approach based on energy variations known as top-down saliency on the curvature attributes using 3D-FFT local spectra and multi-dimensional plane projections. To analyze the directional nature of seismic data, the directional center-surround technique is employed for visual attention. Furthermore, the log-Gabor filter and image erosion are applied to the saliency-rendered seismic volume to highlight the oriented amplitude discontinuities at faults. Most of the time, these discontinuities may not be very prominent to find the subtle faults and other trace-to-trace hidden geological features in three-dimensional seismic data. In our work, calculated attributes assist us in mapping these changes, because they are all differently sensitive to the faults and fractures in unique ways. Experimental results on real field seismic data from the Krishna-Godavari basin prove that the proposed algorithm is effective and efficient in tracking subtle and minor faults, better than previous works.
TL;DR: In this paper , the authors developed a magnetometer system designed for the AUV URASHIMA with a renewed navigation data distribution system, which was used for near-bottom magnetic surveys.
Abstract: Marine magnetic field surveys conducted near the sea bottom are useful in producing images of the oceanic crust in order to ascertain its volcanic eruption history, active hydrothermal systems, and hydrothermal deposit evolution. An autonomous underwater vehicle (AUV) can carry out self-controlled survey operations while maintaining a stable vehicle attitude at low altitudes above the seafloor. As a result of these benefits, AUVs have attracted attention for various missions. The total magnetic field intensity is generally used for subsurface magnetization images. Recently, vector magnetic anomaly analysis has been considered to be extremely effective for high-accuracy estimation of subsurface magnetization structures. However, correcting for the anomalous magnetic field produced by the vehicle body is one of the difficulties that hinders vector magnetic anomaly analysis. Therefore, we developed a magnetometer system designed for the AUV URASHIMA with a renewed navigation data distribution system. Experimental observation was carried out around a submarine mud volcano with a small magnetic anomaly off Tanegashima Island. The results show that correction for the magnetic field of the vehicle because of the attitude, especially for changes in pitch, is essential for near-bottom magnetic surveys using AUVs. Based on these results, we proposed a suitable data acquisition method to remove the pitching effects of the vehicle for figure-eight turns. Next, practical observation was carried out in the hydrothermal area, and the proposed correction method for magnetic data reduced the pitch variation effect. These results indicate that the correction for the magnetic field of the vehicle based using attitude data, especially for pitching variations, is required in order to obtain high-quality magnetic anomaly data using AUVs. However, a short-period variation of approximately 10 nT caused by abrupt pitch changes remains.