Problems In Seismic Exploration Research Articles

MAU-net: A multibranch attention U-net for full-waveform inversion

Data-driven velocity inversion has emerged as a prominent and challenging problem in seismic exploration. The complexity of the inversion problem and the limited data set make it difficult to ensure the stability and generalization of neural networks. To address these concerns, a novel approach called multibranch attention U-net (MAU-net) is proposed for velocity inversion. The key distinction of MAU-net from previous data-driven approaches lies in its ability to not only learn information from the data domain but also incorporate prior model domain information. MAU-net consists of two branches: one branch uses seismic records as input to effectively learn the mapping relationship between the data and model domains, whereas the other branch uses a prior geologic model as input to extract features from the model domain, thereby guiding MAU-net’s learning process. In addition, three major improvements are made to the model to enhance MAU-net’s utilization of seismic data and handle redundant information. The effectiveness of the improvements is verified through ablation experiments. The performance of MAU-net is demonstrated with the Marmousi model and the 2004 BP model, and it also can be combined with full-waveform inversion to further improve the quality of the inversion result. MAU-net exhibits robust performance on field data through the use of transfer learning techniques, further confirming its reliability and applicability.

Deep decomposition learning for reflectivity inversion

AbstractWe report a combination of classical regularization theory with a null space neural network approach based on deep decomposition learning, paying particular attention to the solution of one ubiquitous problem in seismic exploration: the recovery of full‐band reflectivity from band‐limited seismic traces. The method extends the popular post‐processing approach by learning how to improve an initial reconstruction with estimated missing components from the null space of the forward operator, which in our case, are the missing frequency components of the reflectivity. We integrate the null space element prediction to act in conjunction with convolutional neural network based denoising and a data‐consistent algorithm. The proposed framework honours the input measurements while enforcing generalization. Numerical experiments on synthetic and real datasets show that the proposed method naturally enforces a high‐resolution prediction consistent with the low‐resolution input seismic traces. We compare its performance with state‐of‐the‐art thin‐bed reflectivity estimation methods.

Seismic Periodic Noise Attenuation Based on Sparse Representation Using a Noise Dictionary

Periodic noise is a well-known problem in seismic exploration, caused by power lines, pump jacks, engine operation, or other interferences. It contaminates seismic data and affects subsequent processing and interpretation. The conventional methods to attenuate periodic noise are notch filtering and some model-based methods. However, these methods either simultaneously attenuate noise and seismic events around the same frequencies, or need expensive computation time. In this work, a new method is proposed to attenuate periodic noise based on sparse representation. We use a noise dictionary to sparsely represent periodic noise. The noise dictionary is constructed based on ambient noise. An advantage of our method is that it can automatically suppress monochromatic periodic noise, multitoned periodic noise and even periodic noise with complex waveforms without pre-known noise frequencies. In addition, the method does not result in any notches in the spectrum. Synthetic and field examples demonstrate that our method can effectively subtract periodic noise from raw seismic data without damaging the useful seismic signal.

Salt Structure Elastic Full Waveform Inversion Based on the Multiscale Signed Envelope

Building high-fidelity velocity models for salt structures is a valuable and difficult problem in seismic exploration. Acoustic-based full-waveform inversion (FWI) methods usually produce velocity artifacts around high-contrast interfaces due to the generation of converted waves. Therefore, elastic FWI (EFWI) should be used in salt model velocity building. Two problems that restrict EFWI are: lack of low-frequency seismic data and multiparameter coupling. For the first problem, envelope is a good choice because of its ability to reconstruct low-frequency components independent of the frequency range of seismic data. However, envelope is instantaneous energy flow and lacks polarity information, while the elastic waves are vectors. Thus, the direct use of envelope to reconstruct the low-frequency components of elastic waves causes serious artificial artifacts in envelope inversion. Therefore, we introduce signed demodulation and window average function to obtain the multiscale (MS) envelope with polarity, defined as the MS signed envelope to reconstruct low-frequency elastic data. The reconstructed low-frequency data are then used in EFWI, and an elastic MS signed direct envelope inversion algorithm is proposed. For the second problem, wave mode decomposition and hierarchical inversion strategies are integrated into the inversion to eliminate the multiparameter coupling effect. A salt layer model and BP model are used to verify the effectiveness of the algorithm. Finally, the deficiencies in the research of this article and further improvement plans are also discussed.

Application of the Grid-Characteristic Method to the Solution of Direct Problems in the Seismic Exploration of Fractured Formations (Review)

The papers dedicated to the procedures of solving direct problems in seismic exploration of fractured formations are considered in this review article. The fractured formations are known to be potential hydrocarbon reservoirs, which are being studied actively at the present time. Due to high cost of field prospecting works, the numerical simulation is an important part in such research, leading to a significant decrease in financial and time expenditures. The papers focusing on conventional popular practical modeling methods based on the use of effective models are considered. A significant part of this work also deals with the papers that use the procedures developed by the authors to solve the formulated range of problems. These procedures are based on a grid-characteristic numerical method with interpolation on unstructured triangular (in the 2D-case) and tetrahedral (in the 3D-case) meshes. The grid-characteristic method most accurately describes the dynamical processes in exploration seismology problems, because it considers the nature of wave phenomena. The used approach allows making the correct computational algorithms at the boundaries and contact boundaries of the integration domain. An important part of this article describes the different models of fracturing. The results of mathematical modeling by the developed procedure, which are presented in the authors’ papers, are also considered. The important practical conclusions made in the considered papers are presented.

Numerical modeling with high performance computing of seismic waves for complex marine environments: Benchmarking with laboratory experiments

Numerical simulations are widely used for forward and inverse problems in seismic exploration to investigate different wave propagation phenomena. However, the numerical results are hard to be compared to real seismic measurements as the subsurface is never exactly known. Using laboratory measurements for small-scale physical models can provide a valuable link between purely numerical and real seismic datasets. We present a case study for comparing ultrasonic data for a complex model with spectral-element and finite-difference synthetic results. The small-scale model was immersed in a water tank. Reflection data was recorded with piezoelectric transducers using a conventional pulse-echo technique. We paid special attention to the implementation of the real source signal—and radiation pattern—in the numerical domain. It involved a laboratory calibration measurement, followed by an inversion process. The model geometry was implemented using a non-structured mesh for the spectral-element simulations. The comparisons show a very good fit between synthetic and laboratory traces in general, and the small discrepancies can be assigned mostly to the noise present in the laboratory data.

Application of grid-characteristic method to some seismic exploration problems in the Arctic

The aim of this work is simulation of wave propagation in the Arctic with the presence of different ice structures, using high-performance computing. In the given paper grid-characteristic method is applied, which provides correctly describing the contact and boundary conditions.

О применении формулы Рэлея на основе интегральных выражений Кирхгофа к задачам георазведки

О применении формулы Рэлея на основе интегральных выражений Кирхгофа к задачам георазведки

Numerical solution of seismic exploration problems in the Arctic region by applying the grid-characteristic method

The goal of this paper is the numerical solution of direct problems concerning hydrocarbon seismic exploration on the Arctic shelf. The task is addressed by solving a complete system of linear elasticity equations and a system of acoustic field equations. Both systems are solved by applying the grid-characteristic method, which takes into account all wave processes in a detailed and physically correct manner and produces a solution near the boundaries and interfaces of the integration domain, including the interface between the acoustic and linear elastic media involved. The seismograms and wave patterns obtained by numerically solving these systems are compared. The effect of ice structures on the resulting wave patterns is examined.

Application of the grid-characteristic method on unstructured tetrahedral meshes to the solution of direct problems in seismic exploration of fractured layers

Seismic responses from fractured geological layers are mathematically simulated by applying the grid-characteristic method on unstructured tetrahedral meshes with the use of high-performance computer systems. The method is intended for computing complicated spatial dynamical processes in complex heterogeneous media and is characterized by exact formulation of contact conditions. As a result, it can be applied to the simulation of seismic exploration problems, including in regions with a large number of inhomogeneities, examples of which are fractured structures. The use of unstructured tetrahedral meshes makes it possible to specify geological cracks of various shapes and spatial orientations. As a result, problems are solved in a formulation maximally close to an actual situation. A cluster of computers is used to improve the accuracy of the computation by optimizing its duration.

The development and testing of a 2D laboratory seismic modelling system for heterogeneous structure investigations

Lateral velocity variations and low velocity near-surface layers can produce strong scattered and guided waves which interfere with reflections and lead to severe imaging problems in seismic exploration. In order to investigate these specific problems by laboratory seismic modelling, a simple 2D ultrasonic model facility has been recently assembled within the Wave Propagation Lab at ETH Zurich. The simulated geological structures are constructed from 2mm thick metal and plastic sheets, cut and bonded together. The experiments entail the use of a piezoelectric source driven by a pulse amplifier at ultrasonic frequencies to generate Lamb waves in the plate, which are detected by piezoelectric receivers and recorded digitally on a National Instruments recording system, under LabVIEW software control.The 2D models employed were constructed in-house in full recognition of the similitude relations. The first heterogeneous model features a flat uniform low velocity near-surface layer and deeper dipping and flat interfaces separating different materials. The second model is comparable but also incorporates two rectangular shaped inserts, one of low velocity, the other of high velocity. The third model is identical to the second other than it has an irregular low velocity surface layer of variable thickness. Reflection as well as transmission experiments (crosshole & vertical seismic profiling) were performed on each model. The two dominant Lamb waves recorded are the fundamental symmetric mode (non-dispersive) and the fundamental antisymmetric (flexural) dispersive mode, the latter normally being absent when the source transducer is located on a model edge but dominant when it is on the flat planar surface of the plate.Experimental group and phase velocity dispersion curves were determined and plotted for both modes in a uniform aluminium plate. For the reflection seismic data, various processing techniques were applied, as far as pre-stack Kirchhoff migration. The irregular surface layer and the anomalous velocity block inserts can destroy the coherence of the reflections. Migration was able to resolve the two main buried interfaces when the surface layer was flat but for the variable irregular surface layer the imaging result is inferior. First-arrival tomography was applied to the crosshole seismic data set and yielded the correct velocity distributions.Numerical modelling was also carried out to replicate the laboratory data and to identify the arrivals. The numerical seismograms are of superior quality to the physical model data and yield improved images of the structures.

Time-Arrival Location of Seismic P-Wave Based on Wavelet Transform

The automatic pick of seismic first arrivals is a foundational problem in Seismic Exploration. Picking the first arrival of P-wave is an important problem in the seismic research field. The modulus maxima of wavelet transform is a useful method for picking up the singularities of function. For applying the modulus maxima method to investigate the arrival time of P-wave, it is necessary to eliminate the influence of random factors. Based on standard deviation, we present a method to reduce the influence of random factors. Then we get an approach to detect the arrival time of P-wave by means of window energy ratio factors. The results of data analysis indicate that our method is more effective.

The Seismic Acquisition Method Researching for the Complex Mountainous Terrain in YXL Area Qaidam Basin

YXL area is the concentration area of exploration activity with classic complicate surface feature in Qaidam Basin. So, its interference wave is development and the seismic data is in low signal-to-noise ratio (SNR) in the area. Through multiple seismic exploration collecting means, Acquisition techniques has obtained great breakthrough, and array technique has showed great affection. The geological tasks and seismic exploration difficulties of target area is aimed in the paper. The remained problems in the past seismic exploration is dissected, studying the noise interference feature and the effects for the array noise attenuation. And the positive roles of the stack response for the noise attenuation is discussed and to supply the high quality and the high precision data for the seismic in this area. Key words : Shot-receiving array; Stack array response; Geometry; Direction effect; Array weighted average effect; Signal-to-noise ratio

Preconditioning non-monotone gradient methods for retrieval of seismic reflection signals

The core problem in seismic exploration is to invert the subsurface reflectivity from the surface recorded seismic data. However, most of the seismic inverse problems are ill-posed by nature. To overcome the ill-posedness, different regularized least squares methods are introduced in the literature. In this paper, we developed a preconditioning non-monotone gradient method, proved it converges with R-superlinear rate and applied it to seismic deconvolution and imaging. Numerical examples demonstrate that the method is efficient. It helps to improve the resolution of the seismic inversions.

Modelling of local velocity anomalies: a cookbook

The determination of small‐scale velocity anomalies (from tens to a few hundreds of metres) is a major problem in seismic exploration. The impact of such anomalies on a structural interpretation can be dramatic and conventional techniques such as tomographic inversion or migration velocity analysis are powerless to resolve the ambiguity between structural and velocity origins of anomalies. We propose an alternative approach based on stochastic modelling of numerous anomalies until a set of models is found which can explain the real data. This technique attempts to include as much a priori geological information as possible. It aims at providing the interpreter with a set of velocity anomalies which could possibly be responsible for the structural response. The interpreter can then choose one or several preferred models and pursue a more sophisticated analysis. The class of retained models are all equivalent in terms of data and therefore represent the uncertainty in the model space.The procedure emulates the real processing sequence using a simplified scheme. Essentially, the technique consists of five steps: 1 Interpretation of a structural anomaly in terms of a velocity anomaly with its possible variations in terms of position, size and amplitude. 2 Drawing a model by choosing the parameters of the anomaly within the acceptable range. 3 Modelling the traveltimes in this model and producing the imaging of the reflected interface. 4 Comparing the synthetic data with the real data and keeping the model if it lies within the data uncertainty range. 5 Iterate from step 2.In order to avoid the high computational cost inherent in using statistical determinations, simplistic assumptions have been made:• The anomaly is embedded in a homogeneous medium: we assume that the refraction and the time shift due to the anomaly have a first‐order effect compared with ray bending in the intermediate layers.• We model only the zero‐offset rays and therefore we restrict ourselves to structural problems.• We simulate time migration and so address only models of limited structural complexity.These approximations are justified in a synthetic model which includes strong lateral velocity variations, by comparing the result of a full processing sequence (prestack modelling, stack and depth migration) with the simplified processing. This model is then used in a blind test on the inversion scheme.

LINEARIZED INVERSION OF SEISMIC REFLECTION DATA*

AbstractThis is the first of a series of papers giving the solution of the inverse problem in seismic exploration. The acoustic approximation is used together with the assumption that the velocity field has the form image . The forward problem is then linearized (thus neglecting multiple reflected waves) and the inverse problem of estimating δ is set up. Its rigorous solution can be obtained using an iterative algorithm, each step consisting of a classical Kirchhoff migration (hyperbola summation) plus a classical forward modeling step (circle summation).

Wavelet estimation

An important problem in seismic exploration is the estimation of and correction for the seismic wavelet. A seismic signal may be modeled as a convolutional model with the wavelet as one component. The wavelet propagated by the seismic energy source is complicated by transmission and recording filters. Some filters in the system can be deterministically defined while others are more conjectural. The estimation of the wavelet is useful in two major ways. Borehole measurements are used to model the surface seismograms. The wavelet used in the model needs to match that of the seismogram to correlate the two measurements. Conversely, the estimated wavelet can be used to design inverse filters which make the seismogram approach the borehole measures. Some well-known methods for estimation of the wavelet are based on assumptions about the wavelet or the earth reflectivity. Examples of the methods indicate success on some data even though each makes different assumptions. The methods serve to point out basic problems in reliably estimating the wavelet from the seismogram. Basic problems include noise, band-limiting, nonstationarity, uncertain theoretical models, assumption failure, and widely diverse geological sequences of the earth. Quality control or evaluation of the performance of an estimation algorithm is a nontrivial problem. The estimation of the wavelet from a seismic recording remains an area of challenging research and importance in exploration for hydrocarbons.

Multiple reflections as an additive noise limitation in seismic reflection work

A principal problem in seismic exploration is the heterogeneous partially reflecting medium that makes up the transmission zone to the target reflectors of interest. Multiple reflection between the free surface and the shallower reflectors produces additive noise that interferes with our view of the bedding plane geometry and rock properties in the target zone. Residual multiple energy on the interpreter's record section display can easily be mistaken for signal. Because the magnitude of multiples is dependent on reflectivity products, and because subsurface reflectivities are normally small, the importance of multiples is highly variable. The complementary combination of predictive deconvolution and common depth point stack is routinely used for the reduction of multiple reflections. Predictive deconvolution achieves a temporal prediction and subtraction of that class of short-period multiples that is most predictable, and common depth point stack reduces that class of multiples distinguishable from primaries on the basis of local horizontal phase velocity in the x, t observational space. Each of these methods can be justified in terms of a simplified one-dimensional model of the earth. However, a major reason for their success is that they are employed with an empirical, statistical approach. As a result, these two processes are particularly robust and forgiving and respond imperfectly, but often constructively, to real-world deviations from the simplified models. Both processes are capable of distorting or destroying the desired signal, and their noise-reduction effectiveness is dependent on the manner of application. Quality control methods are imperfect, and there is an element of human artistry in seismic data processing. Predictive deconvolution employs a one-dimensional (t) filter designed on a purely statistical basis. Seismic data represent observations in (x 1 , x 2 , t), a four-dimensional space, and multiple reflections are deterministically predictable (in principle) from the shallower primary reflection data. Common depth point stack operates in (x 1 , t) as an array steered for the arrival of the roughly spherical target reflection wavefront. Multidimensional filter design aimed at coherent noise rejection, based on the nonrandom noise structure in (x 1 , t) is often used in problem areas. More effective reduction of multiple reflections is one of many potentially useful improvements in the seismic method.

Applications of median filtering to deconvolution, pulse estimation, and statistical editing of seismic data

Seismic exploration problems frequently require analysis of noisy data. Traditional processing removes or reduces noise effects by linear statistical filtering. This filtering process can be viewed as a weighted averaging with coefficients chosen to enhance the data information content. When the signal and noise components occupy separate spectral windows, or when the statistical properties of the noise are sufficiently understood, linear statistical filtering is an effective tool for data enhancement. When the noise properties are not well understood, or when the noise and signal occupy the same spectral window, linear or weighted averaging performs poorly as a signal enhancement process. One must look for alternative procedures to extract the desired information. As a nonlinear operation which is statistically similar to averaging, median filtering represents one potential alternative. This paper investigates the application of median filtering to several seismic data enhancement problems. A methodology for using median filtering as one step in cepstral deconvolution or seismic signature estimation is presented. The median filtering process is applied to statistical editing of acoustic impedance data and the removal of noise bursts from reflection data. The most surprising conclusion obtained from the empirical studies on synthetic data is that, in high‐noise situations, cepstral‐based median filtering appears to perform exceptionally well as a deconvolver but poorly as a signature estimator. For real data, the process is stable and, to the extent that the data follow the convolutional model, does a reasonable job at both pulse estimation and deconvolution.

Seismic exploration problems in the Bass region – some recent results

The diversity of geological regimes in the Bass region, the location of a recent Bureau of Mineral Resources (BMR) seismic survey (Fig. 1), is paralleled by a diversity of seismic exploration problems. Within the Bass Basin the economically significant lower part of the Eastern View Coal Measures, and deeper undrilled strata, have historically been difficult to explore seismically due to acoustic shadowing by, and multiple generation within, the coal-bearing upper part. Furthermore, the overlying section is host to volcanogenic complexes which can be efficient acoustic scatterers. The seismic response of sedimentary sequences in the two continental slopes that were traversed, the upper parts of which are potentially of economic significance, can be partly degraded by a strong water-layer multiple, and by processing flows which fail to compensate for departure from Common Depth Point (CDP) ray path geometry below the rough submarine topography. Limitations of resolution (loss of high frequencies and low signal to noise ratios) in some older seismic data can be related to the practice of summing adjacent traces or consecutive shot records, and to an inadequate energy source (Figs 2 and 3).