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- Volume 66, Issue 4, 2018
Geophysical Prospecting - Volume 66, Issue 4, 2018
Volume 66, Issue 4, 2018
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Automatic stacking‐velocity estimation using similarity‐weighted clustering
Authors Guochang Liu, Chao Li, Xingye Liu, Qiang Ge and Xiaohong ChenABSTRACTLocal seismic event slopes contain subsurface velocity information and can be used to estimate seismic stacking velocity. In this paper, we propose a novel approach to estimate the stacking velocity automatically from seismic reflection data using similarity‐weighted k‐means clustering, in which the weights are local similarity between each trace in common midpoint gather and a reference trace. Local similarity reflects the local signal‐to‐noise ratio in common midpoint gather. We select the data points with high signal‐to‐noise ratio to be used in the velocity estimation with large weights in mapped traveltime and velocity domain by similarity‐weighted k‐means clustering with thresholding. By using weighted k‐means clustering, we make clustering centroids closer to those data points with large weights, which are more reliable and have higher signal‐to‐noise ratio. The interpolation is used to obtain the whole velocity volume after we have got velocity points calculated by weighted k‐means clustering. Using the proposed method, one obtains a more accurate estimate of the stacking velocity because the similarity‐based weighting in clustering takes into account the signal‐to‐noise ratio and reliability of different data points in mapped traveltime and velocity domain. In order to demonstrate that, we apply the proposed method to synthetic and field data examples, and the resulting images are of higher quality when compared with the ones obtained using existing methods.
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Compressive sensing approach for two‐dimensional magnetotelluric inversion using wavelet dictionaries
Authors C.G. Nittinger and M. BeckenABSTRACTWe present a 2D inversion scheme for magnetotelluric data, where the conductivity structure is parameterised with different wavelet functions that are collected in a wavelet‐based dictionary. The inversion model estimate is regularised in terms of wavelet coefficient sparsity following the compressive sensing approach. However, when the model is expressed on the basis of a single wavelet family only, the geometrical appearance of model features reflects the shape of the wavelet functions. Combining two or more wavelet families in a dictionary provides greater flexibility to represent the model structure, permitting, for example, the simultaneous occurrence of smooth and sharp anomalies within the same model. We show that the application of the sparsity regularisation scheme with wavelet dictionaries provides the user with a number of different model classes that may explain the data to the same extent. For a real data example from the Dead Sea Transform, we show that the use of such a scheme can be beneficial to evaluate the geometries of conductivity anomalies and to understand the effect of regularisation on the model estimate.
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A method for classifying pre‐stack seismic data based on amplitude–frequency attributes and self‐organizing maps
ABSTRACTAnalysis of pre‐stack seismic data is important for seismic interpretation and geological features classification. However, most classification analyses are based on post‐stack data, which ignores pre‐stack information, and it may be disadvantageous for complex geological description. In this work, we propose a method to address the classification of pre‐stack seismic data decomposed using the wavelet transform to spread the amplitude and frequency seismic attributes at the same time, which are then classified by a self‐organizing map. The resulting classes constitute an attribute constructed by the joint amplitude–frequency components of the transformed pre‐stack seismic gathers, which create a multi‐dimensional set defined through a given metric. Tests on a real seismic cube revealed that the method can identify patterns observed on the seismic images, which agree with our current knowledge of the seismic data. The method can be used as a complementary tool to identify features and structures in seismic signals.
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Investigating a time‐shift extended imaging condition in a Kirchhoff pre‐stack depth migration algorithm
More LessABSTRACTExtracting true amplitude versus angle common image gathers is one of the key objectives in seismic processing and imaging. This is achievable to different degrees using different migration techniques (e.g., Kirchhoff, wavefield extrapolation, and reverse time migration techniques) and is a common tool in exploration, but the costs can vary depending on the selected migration algorithm and the desired accuracy. Here, we investigate the possibility of combining the local‐shift imaging condition, specifically the time‐shift extended imaging condition, for angle gathers with a Kirchhoff migration. The aims are not to replace the more accurate full‐wavefield migration but to offer a cheaper alternative where ray‐based methods are applicable and to use Kirchhoff time‐lag common image gathers to help bridge the gap between the traditional offset common image gathers and reverse time migration angle gathers; finally, given the higher level of summation inside the extended imaging migration, we wish to understand the impact on the amplitude versus angle response. The implementation of the time‐shift imaging condition along with the computational cost is discussed, and results of four different datasets are presented. The four example datasets, two synthetic, one land acquisition, and a marine dataset, have been migrated using a Kirchhoff offset method, a Kirchhoff time‐shift method, and, for comparison, a reverse time migration algorithm. The results show that the time‐shift imaging condition at zero time lag is equivalent to the full offset stack as expected. The output gathers are cleaner and more consistent in the time‐lag‐derived angle gathers, but the conversion from time lag to angle can be considered a post‐processing step. The main difference arises in the amplitude versus offset/angle distribution where the responses are different and dramatically so for the land data. The results from the synthetics and real data show that a Kirchhoff migration with an extended imaging condition is capable of generating subsurface angle gathers. The same disadvantages with a ray‐based approach will apply using the extended imaging condition relative to a wave equation angle gather solution. Nevertheless, using this approach allows one to explore the relationship between the velocity model and focusing of the reflected energy, to use the Radon transformation to remove noise and multiples, and to generate consistent products from a ray‐based migration and a full‐wave equation migration, which can then be interchanged depending on the process under study.
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An adaptive free‐surface expression for three‐dimensional finite‐difference frequency‐domain modelling of elastic wave
Authors Jian Cao, Jing‐Bo Chen and Meng‐Xue DaiABSTRACTFinite‐difference frequency‐domain modelling of seismic wave propagation is attractive for its efficient solution of multisource problems, and this is crucial for full‐waveform inversion and seismic imaging, especially in the three‐dimensional seismic problem. However, implementing the free surface in the finite‐difference method is nontrivial. Based on an average medium method and the limit theorem, we present an adaptive free‐surface expression to describe the behaviour of wavefields at the free surface, and no extra work for the free‐surface boundary condition is needed. Essentially, the proposed free‐surface expression is a modification of density and constitutive relation at the free surface. In comparison with a direct difference approximate method of the free‐surface boundary condition, this adaptive free‐surface expression can produce more accurate and stable results for a broad range of Poisson's ratio. In addition, this expression has a good performance in handling the lateral variation of Poisson's ratio adaptively and without instability.
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Increasing resolution of reverse‐time migration using time‐shift gathers
Authors Zhiguang Xue, Sergey Fomel and Junzhe SunABSTRACTReverse‐time migration has become an industry standard for imaging in complex geological areas. We present an approach for increasing its imaging resolution by employing time‐shift gathers. The method consists of two steps: (i) migrating seismic data with the extended imaging condition to get time‐shift gathers and (ii) accumulating the information from time‐shift gathers after they are transformed to zero‐lag time‐shift by a post‐stack depth migration on a finer grid. The final image is generated on a grid, which is denser than that of the original image, thus improving the resolution of the migrated images. Our method is based on the observation that non‐zero‐lag time‐shift images recorded on the regular computing grid contain the information of zero‐lag time‐shift image on a denser grid, and such information can be continued to zero‐lag time‐shift and refocused at the correct locations on the denser grid. The extra computational cost of the proposed method amounts to the computational cost of zero‐offset migration and is almost negligible compared with the cost of pre‐stack shot‐record reverse‐time migration. Numerical tests on synthetic models demonstrate that the method can effectively improve reverse‐time migration resolution. It can also be regarded as an approach to improve the efficiency of reverse‐time migration by performing wavefield extrapolation on a coarse grid and by generating the final image on the desired fine grid.
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Application of spectral decomposition and neural networks to characterise deep turbidite systems in the outer fold and thrust belt of the Niger Delta
Authors Muslim B. Aminu and Samuel B. OjoABSTRACTWe have applied a wavelet‐based spectral decomposition scheme and a multi‐layered feed‐forward neural network to interpret turbidite depositional systems from three‐dimensional reflection seismic data and well logs for a prospective hydrocarbon zone in the outer fold and thrust belt of the Niger Delta. The goal was to overcome difficulties in interpreting depositional systems from deep sections of the Field, occasioned by loss of seismic resolution with depth and the sparse distribution of wells.
The decomposition scheme allowed us to delineate multiple depositional systems not apparent on the conventional seismic amplitude display. These systems include linear channel systems with terminal splay lobes, a sinuous channel system and its abandoned meander loops, and sediment wave features in overbank areas. Delineated channel morphologies and transport directions varied both laterally and vertically and were possibly dependent upon the disposition of the pre‐thrusting paleo‐seafloor. Terminal splay lobes are fragmented and coincident with the locations of topographic lows, which are possibly related to the initial configurations of the oceanic basement below. Predicted porosity and resistivity distributions have morphologies that correlate well with the mapping provided by the spectral decomposition scheme. The property distributions indicate that reservoir prone systems in the Field and possibly within the outer fold and thrust belt are composed primarily of channel systems, both linear and sinuous, and their associated splay lobes. The channel systems appear vertically stacked, and this situation possibly increases the potential success rate for exploration wells in the region. Beyond channel limits, redistributive bottom currents varying rapidly in speed and direction apparently encouraged the dispersal of sand‐rich sediments to form sediment waves.
Despite the limited well control, the methodology significantly aided our interpretation. It proved effective at revealing the distribution of reservoir prone facies within the Field and provided insight into the dominant factors that controlled deposition within the Field.
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A fractal model for streaming potential coefficient in porous media
Authors Luong Duy Thanh, Phan Van Do, Nguyen Van Nghia and Nguyen Xuan CaABSTRACTStreaming potential is the result of coupling between a fluid flow and an electric current in porous rocks. The modified Helmholtz–Smoluchowski equation derived for capillary tubes is mostly used to determine the streaming potential coefficient of porous media. However, to the best of our knowledge, the fractal geometry theory is not yet applied to analyse the streaming potential in porous media. In this article, a fractal model for the streaming potential coefficient in porous media is developed based on the fractal theory of porous media and on the streaming potential in a capillary. The proposed model is expressed in terms of the zeta potential at the solid−liquid interface, the minimum and maximum pore/capillary radii, the fractal dimension, and the porosity of porous media. The model is also examined by using another capillary size distribution available in published articles. The results obtained from the model using two different capillary size distributions are in good agreement with each other. The model predictions are then compared with experimental data in the literature and those based on the modified Helmholtz–Smoluchowski equation. It is shown that the predictions from the proposed fractal model are in good agreement with experimental data. In addition, the proposed model is able to reproduce the same result as the Helmholtz–Smoluchowski equation, particularly for high fluid conductivity or large grain diameters. Other factors influencing the streaming potential coefficient in porous media are also analysed.
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Application of alternative digital rock physics methods in a real case study: a challenge between clean and cemented samples
More LessABSTRACTHigh‐resolution three‐dimensional images are used in digital rock physics to numerically compute rock physical properties such as permeability and elastic moduli. These images are not widely available, and their preparation is both expensive and time consuming. All of these issues highlight the importance of alternative digital rock physics methods that are based on two‐dimensional images and use different approaches to compute effective properties of three‐dimensional samples. In addition, the scale of study in both standard and alternative digital rock physics is very small, which applications of its results are questionable at wells or reservoir scale. The aim of this study is to use two‐dimensional images and alternative digital rock physics techniques for computing seismic wave velocity and permeability, which are compared with well and laboratory data. For this purpose, data from one well in a reservoir located in the southwestern part of Iran are used. First, two clean (carbonate) and two cemented (limy sandstone) samples were collected from well cores at different depths. Then, two‐dimensional images by scanning electron microscope and conventional microscope were captured. In the next step, two alternative digital rock physics methods, namely, empirical relations and conditional reconstruction, have been employed to compute P‐wave velocity and permeability of a three‐dimensional medium. Results showed that, in clean (mono‐mineral) samples, velocity values were reasonably close to well data. However, permeability values are underestimated compared with laboratory data because laboratory data were obtained at ambient pressure, whereas alternative digital rock physics results are more representative of reservoir pressure conditions. Nevertheless, permeability–porosity trends are valid for both samples. In the case of cemented samples, a two‐scale procedure, along with a method for two‐scale computation and grain‐cement segmentation, is presented and developed. Results showed that P‐wave velocity is overestimated probably due to random sampling in this method. However, velocity–porosity trends are in agreement with well data. Moreover, permeability results obtained for cemented samples were also similar to those obtained for the clean samples.
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Forward modelling and imaging of ground‐penetrating radar in tunnel ahead geological prospecting
Authors Bin Liu, Fengkai Zhang, Shucai Li, Yao Li, Shan Xu, Lichao Nie, Chongmin Zhang and Qingsong ZhangABSTRACTAdverse geologies are often encountered during tunnel construction, which could seriously endanger the construction. To ensure the safety, it is essential to detect adverse geologies and their water‐bearing situation ahead the tunnel face. Ground‐penetrating radar is a suitable instrument, but the accurate interpretation of its detection results is difficult. In this paper, at first, an improved back projection imaging algorithm is proposed, which can make reflection waves closer to the real geological boundaries with few artificial clutters. And then, forward modelling of ground‐penetrating radar is carried out for typical adverse geologies, such as karst caves, faults, fractured rock masses, fracture network, and water‐bearing body. Their corresponding response features are obtained, accumulating experience for geological interpretation. The above two methods provide the basis for target identification and geological interpretation. In the last part, the application of the above two methods in several engineering cases are given, and their effectiveness is verified.
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Complex resistivity of mineral rocks in the context of the generalised effective‐medium theory of the induced polarisation effect
Authors Michael S. Zhdanov, Vlad Burtman, Masashi Endo and Wei LinABSTRACTThis paper develops the generalised effective‐medium theory of induced polarisation for rock models with elliptical grains and applies this theory to studying the complex resistivity of typical mineral rocks. We first demonstrate that the developed generalised effective‐medium theory of induced polarisation model can correctly represent the induced polarisation phenomenon in multiphase artificial rock samples manufactured using pyrite and magnetite particles. We have also collected representative rock samples from the Cu–Au deposit in Mongolia and subjected them to mineralogical analysis using Quantitative Evaluation of Minerals by Scanning Electron Microscopy technology. The electrical properties of the same samples were determined using laboratory complex resistivity measurements. As a result, we have established relationships between the mineral composition of the rocks, determined using Quantitative Evaluation of Minerals by Scanning Electron Microscopy analysis, and the parameters of the generalised effective‐medium theory of induced polarisation model defined from the laboratory measurements of the electrical properties of the rocks. These relationships open the possibility for remote estimation of types of mineralisation and for mineral discrimination using spectral induced polarization data.
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Feasibility of signal enhancement with multiple grounded‐wire sources for a frequency‐domain electromagnetic survey
Authors Haigen Zhou, Yao Yao, Changsheng Liu, Jun Lin, Lili Kang, Gang Li and Xinsen ZengABSTRACTFrequency‐domain electromagnetic methods with a grounded‐wire source are powerful tools in geophysical exploration. However, the signal may be too weak to guarantee the quality of survey data in complex electromagnetic environments, especially when the receiver is located in the air for the newly developed grounded‐source airborne frequency‐domain electromagnetic method. In this paper, a signal enhancement method with multiple sources is proposed to solve this problem. To evaluate the signal enhancement effect, we compared the signals generated by a single source and multiple sources with equal electric moment. The signal differences caused by synchronisation error and separation distance between source elements were analysed, and the methods to achieve maximum signal were introduced. Besides, we discussed the interaction between adjacent source elements to ensure the system safety, including the changes in output current and the safe distance between two sources using a dual‐source model. Lastly, a comprehensive field experiment was designed and conducted to test the multiple‐source method. The data processing results are comparable for single and dual sources, and the signal‐to‐noise ratio of dual source is higher in the field test. The subsurface resistivity structure at the test site is consistent with the previous controlled‐source audio‐frequency magnetotellurics method. These results show that signal enhancement with multiple sources is feasible. This study provides guidance to the application of multiple sources in field surveys when the survey environment is complex and rigorous.
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Internet of Things‐based wireless networking for seismic applications
Authors Hadi Jamali‐Rad and Xander CampmanABSTRACTThere is growing pressure from regulators on operators to adhere to increasingly stricter regulations related to the environment and safety. Hence, operators are required to predict and contain risks related to hydrocarbon production and their infrastructure in order to maintain their licence to operate. A deeper understanding of production optimisation and production‐related risk requires strengthened knowledge of reservoir behaviour and overburden dynamics. To accomplish this, sufficient temporal and spatial resolution is required as well as an integration of various sources of measurements. At the same time, tremendous developments are taking place in sensors, networks, and data analysis technologies. Sensors and accompanying channels are getting smaller and cheaper, and yet they offer high fidelity. New ecosystems of ubiquitous wireless communications including Internet of Things nowadays allow anyone to affordably connect to the Internet at any time and anywhere. Recent advances in cloud storage and computing combined with data analytics allow fast and efficient solutions to handle considerable amounts of data. This paper is an effort to pave the way for exploiting these three fundamental advances to create Internet of Things‐based wireless networks of seismic sensors.
To this aim, we propose to employ a recently developed Internet of Things‐based wireless technology, so‐called low‐power wide‐area networks, to exploit their long range, low power, and inherent compatibility to cloud storage and computing. We create a remotely operated minimum‐maintenance wireless solution for four major seismic applications of interest. By proposing appropriate network architecture and data coordination (aggregation and transmission) designs, we show that neither the low data rate nor the low duty cycle of low‐power wide‐area networks imposes fundamental issues in handling a considerable amount of data created by complex seismic scenarios as long as the application is delay tolerant. In order to confirm this claim, we cast our ideas into a practical large‐scale networking design for simultaneous seismic monitoring and interferometry and carry out an analysis on the data generation and transmission rates. Finally, we present some results from a small‐scale field test in which we have employed our Internet of Things‐based wireless nodes for real‐time seismic quality control over clouds.
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Volumes & issues
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Volume 72 (2023 - 2024)
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Volume 71 (2022 - 2023)
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Volume 70 (2021 - 2022)
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Volume 69 (2021)
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Volume 68 (2020)
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Volume 67 (2019)
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Volume 66 (2018)
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Volume 65 (2017)
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Volume 64 (2015 - 2016)
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Volume 63 (2015)
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Volume 62 (2014)
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Volume 61 (2013)
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Volume 60 (2012)
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Volume 53 (2005)
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