Data and model dual-driven seismic deconvolution via error-constrained joint sparse representation

High Resolution, Simultaneous VSP and Land Seismic Acquisition

Björn Paulsson, Martin Karrenbach, Paul Milligan, Alex Goertz, and Alan Hardin of Paulsson Geophysical Services, with John O'Brien and Don McGuire of Anadarko Petroleum Corporation explain why recording multi-component seismic data using receivers positioned deep in the earth, and closer to the target-zone, can overcome many of the limitations experienced by surface 3D seismic methods. Borehole seismic surveys, commonly known as Vertical Seismic Profiling (VSP), have been an industry standard technique for several decades. In the past, however, these data have been used primarily for check-shot type velocity surveys and for reflection mapping at the well location in a one-dimensional fashion. This 1D measurement can be extended to 2D by using one or more walk-away lines of surface source points. The 2D method works well enough for imaging simple layered stratigraphy, but in a complex reservoir a full 3D data acquisition and imaging solution needs to be pursued. Inserting seismic sensors deep into oil and gas wells, as shown in Figure 1, allows the recording of much higher frequencies as compared to placing sensors at the Earth’s surface. The reason for this is simple: seismic waves have to propagate only once through the weathered layer in a confined zone near the source. In contrast, during surface seismic surveys, waves must travel through the weathered layer twice. Each traversal of the weathered layer attenuates high frequencies much more than the low frequencies, thus reducing the image resolution. The frequency content of borehole seismic data is typically more than twice that of surface seismic data, which provides an increase in subsurface resolution. In addition to recording higher frequency data, borehole seismic sensors provide a number of other advantages: borehole seismic data typically achieve a much higher signal-tonoise ratio than surface seismic data. The combination of a quiet borehole environment and strong sensor coupling to the borehole wall enables such high signal-to-noise ratio. Surface geophones, on the other hand, are generally poorly coupled in weathered rock and exposed to cultural and environmental noise at the surface. Good sensor coupling in the borehole enables three-component (3C) seismic data to be recorded with high vector fidelity. This ultimately allows shear and converted-wave imaging as well as the determination of anisotropy by shear wave splitting analysis (see, e.g., Maultzsch, 2003). Combining P and S wave images allows for attribute inversions of rock properties, such as fluid content, pore pressure, stress direction and fracture patterns. O’Brien et al. (2004b) use time lapse borehole seismic to map changes in such critical attributes for production monitoring purposes. Another advantage of borehole seismic surveys is a favourable geometry to illuminate complex structures such as sub-salt targets, salt flanks or steeply dipping faults. The 3D image volume that can be generated from a large downhole seismic array data is shown in Figure 1. The typical 3D borehole seismic image volume is cone shaped with the top of the cone coincident with the top receiver in the borehole array. The size of the base of the cone is determined by the depth of the image volume and the offset of the sources.

A description of reservoir heterogeneities in all scales is crucial for improvements in reservoir characterization. In this work a multi-scale approach was developed to integrate seismic intermediate-scale data and the conventional short and large scale data, represented by logs and surface seismic data respectively. Intermediate-scale data obtained by short and far-offset crosswell surveys, vertical seismic profiles and high resolution seismic lines can be geostatiscally incorporated in this approach in order to provide more complete reservoir descriptions. The approach employs the available seismic data as reference data in two post-matching steps. An interwell model is the final product of the first step using crosswell data. Such upscale and postmatching is then repeated to the larger-scale seismic traces, using logs and the interwell image as hard data to feed simulations. The final product is an optimal acoustic property model constrained by all logs and seismic surveys. This multi-scale incorporation was applied using field and synthetic data, showing that the main impact in modeling is caused by the incorporation of crosswell images obtained by shooting short distance surveys. Since such data provide a tool to map and recover a very fine layered lateral framework, which can be extrapolated under the constraint of conventional seismic data, the integration must prioritize data with higher frequency content, i.e., should follow two steps: only short-crosswell data are used in the first post-matching, and additional seismic data during the second.

To acquire refined seismic targets, the use of more accurate and more precise methods of seismic signal processing is crucial. Novel seismic processing approach is even more important in case of the complex geology of mountainous regions (e.g., Carpathians, Carpathian Foredeep) where sub-vertical layering of varying rock complex can be found, but also in case of old seismic data reprocessing (especially when the signal-to-noise ratio and general quality are low). Regardless of many research papers and significant progress in seismic processing techniques, a properly processed and interpreted seismic image is still hardly affordable for this region. Obtaining a new value in seismic data processing is a core function of the presented research. The use of dip-guided filtering combined with beam partitioned analysis and Z-domain dip analysis for reprocessing of 3D and 2D seismic data from the Carpathians region has been studied.

Relevance of the work. The paper considers challenging problems related with outlining of intervals with oil and gas presence in the mature Khylly field by use of latest 3D seismic survey techniques in order to gain larger crude resources base. The purpose of this research is to discover the most promising intervals of target horizons with relatively high reservoir properties outlined by 3D seismic data. The subjects of research are 3D seismic survey data, downhole seismic survey – Vertical Seismic Profiling (VSP) and well logging diagrams. The object of research is the Khylly deposit. The paper describes in brief geological and geophysical characteristics, stratigraphic and lithological features of rocks making the section. It is noted that despite repeated surveys by use of various geological and geophysical techniques, the field setting is not thoroughly studied and it has been covered by 3D seismic survey in 2012. Research results. 3D seismic survey applied across Khylly area is resulted in drawing of 4 structural maps for III and I horizons of Productive Series (PS), Akchagyl and Lower Absheron suites. Taking into account the relevance of structural planes of various stratigraphic levels and III horizon of PS being one of the major reference horizons the paper gives description of structural map drawn for this horizon. The detailed velocity model is designed based on VSP data with wide use of velocity analysis data. It has been made clear that Khylly area has block structure and each block has been described in detail. Based on acquired data it has been recommended to drill exploratory well R-1. Conclusion. Processing and interpretation of seismic data are aimed at solving some geological problems; the main task was to obtain results that ensure the study of the geological structure in the seismic survey area, including tracing of seismic horizons, faults and outlining the areas and section intervals which may be of interest due to possible oil and gas presence. VSP data acquired in well 2012 and velocity analysis made it possible to design velocity model of the section under the study, with the use of which the temporary 3D cube was transformed into a depth cube. The quality of seismic data is good and made it possible to solve the tasks set for this research.

Seismic data interpolation and denoising play vital roles in obtaining complete and clean data in seismic data processing. Seismic data usually misses along various spatial axes and always mix with random noise. In order to obtain complete and clean seismic data, reconstruction technology can interpolate missing data and attenuate random noise. Nonsubsampled contourlet transform is an effective transform to obtain multi-scale and multi-direction sparse domain data for compression sensing interpolation and denoising. However, conventional iterative shrinkage/thresholding cannot handle ill-posed and ill-conditioned equations for solving linear inverse problem. We present a two-step iterative log thresholding method to overcome ill-posed and ill-conditioned problems and improve the convergence rate and solution accuracy, which can interpolate and denoise seismic data simultaneously in the nonsubsampled contourlet transform framework. First, we use nonsubsampled contourlet transform to convert the seismic missing data with random noise to sparse domain. Then, we apply two-step iterative log thresholding algorithm to interpolate and denoise data in sparse domain. The result of each iteration is based on the results of the previous two iterations, which can accelerate convergence rate. In addition, log thresholding can further improve convergence rate and solution accuracy. Finally, we use inverse nonsubsampled contourlet transform to obtain the interpolated and denoised seismic data. The new method can reconstruct the irregularly missing data and attenuate random noise to obtain complete and clean seismic data with high accuracy, which is crucial for seismic imaging and inversion. We demonstrate the applicability and effectiveness of this simultaneous interpolation and denoising technique with successful applications to both synthetic and field data examples.

In some of Australia?s underground coal mining areas, near-surface basalt layers create problems for seismic reflection surveying. Affected mines have less confidence in their geological conditions and mine safety and productivity may be compromised. In order to gain insights and obtain potential solutions to this important problem, we have investigated seismic reflection and borehole vertical seismic profiling data from surveys at the North Goonyella Mine and the Moranbah South coal mine lease, which are both located in the Bowen Basin of Queensland. At North Goonyella, seismic velocities determined from the VSP survey indicate that the basalt is not fresh and up-going reflections from layers below the basalt are clearly seen. For the seismic reflection survey, advanced seismic data processing techniques such as pre-stack depth migration were able to improve the continuity of the coal seam reflections across the zone affected by the basalt. No special acquisition parameters were required. At Moranbah South, the problem with the basalts proved to be intractable. The basalts are hard and fresh, their total thickness is up 40 m, their width reaches 360 m and unconsolidated sediments lie between individual flows. The target coal seams are at depths less than 310 m and neither long-offset data acquisition nor prestack depth migration were able to produce satisfactory results. In general, the main issues for seismic surveying in basalt covered areas are (i) the generation of complex downgoing and up-going wavefields which are due to the strong impedance contrasts between the basalt and the surrounding strata, and (ii) the generation of incoherent scattered waves from inhomogeneities within the basalts and their rough margins. We have studied and confirmed these seismic phenomena through computer modelling.

Mathematical and computational challenges involved in seismic data processing presents an opportunity for early adoption of quantum computation methods for end-to-end seismic data processing. Existing methods of seismic data processing involve processes with exponential complexities that result in approximations as well as conversion of some of the continuous phenomena into a stochastic one. In the classical computation methods, the mentioned approximations and assumptions enable us to obtain acceptable results in commercially viable time. This paper proposes alternatives of the classical computations that exist in the quantum computation ecosystem along with the computational advantages it holds. The paper also presents potential contributions of the petroleum industry towards sustaining the quantum computation technologies. Fundamentally seismic data processing involves solutions for systems of linear equations and its derivatives. Quantum computation ecosystem holds efficient solutions for systems of linear equations. In the frequency domain, Finite-Difference modelling reduces seismic-wave equations to systems of linear equations. In the classical computational setup the seismic acquisition involves treatment of the recorded waves as rays and has limited summation provision for recreating the natural reflection or refraction phenomena that is continuous instead of being a stochastic process. The algorithms in the quantum ecosystem allow us to consider summation of signals from all possible paths between the source and the receiver, by amplitude-probability. In addition to the systems of linear equations and their solution with corresponding methods in the quantum ecosystem the fourier transformation and partial differential equations enable us to decompose the waves and apply the physics equation to obtain the desired objective. Quantum-algorithms facilitate exponential speed-up in seismic data processing. The PDE-constrained optimization inverts subsurface P-wave velocity. While going through the seismic data processing steps it is found that the fourier transformation algorithms are derived as a decomposition of the diagonal matrix. The key difference between the fast fourier transform and the quantum fourier transform is that the quantum fourier transformation is used as the building block of several quantum algorithms. Seismic inversion involves laws of physics and calculation that are guided by the ordinary differential equations. In the quantum computation ecosystem these algorithms for linear ordinary differential equations for linear partial differential equations have the complexity of (1/e), where ‘e’ is the tolerance. The insights brought by successful implementation of end-to-end seismic data processing with algorithms in the quantum computation domain enables us to drill most optimally located wells and hence facilitate cost saving. Even with a reduction of 10% in the total number of wells that we drill, we can possibly fund development of one quantum computer hence ensuring economic sustainability of the technology. The novelty of the presented paper lies in the comparative analysis of the classical methods with its counterparts in the quantum ecosystem. It explains the technological and economical aspects of the technology such that extensive knowledge of quantum technology is not compulsory for grasping its contents.

Seismic data processing is essential in hydrocarbon exploration, with normal moveout (NMO) correction being a pivotal step in enhancing seismic signal quality. However, conventional NMO correction often suffers from the stretch effect, which distorts seismic reflections and degrades data quality, especially in long-offset data. This study addresses the issue by analyzing synthetic models and proposing a nonhyperbolic stretch-free NMO correction technique. The proposed method significantly improves seismic data quality by preserving up to 90% of the original amplitude, maintaining frequency content stability at 30 Hz, and achieving a high reduction of stretch-related distortions. Compared to conventional NMO, our technique results in clearer seismic gathers, enhanced temporal resolution, and more accurate velocity models. These improvements have substantial implications for high-resolution subsurface imaging and precise reservoir characterization.This work offers a robust and computationally efficient solution to a longstanding limitation in seismic processing, advancing the reliability of exploration in geologically complex environments.

The application of the seismic reflection method to detect stratigraphic changes away from well locations is beginning to gain acceptance among Reservoir Engineers. Unfortunately one of the limitations of this method is the inherent low resolution of seismic data as compared to well log data. Several approaches have been proposed to produce well log-like or pseudo log traces from seismic reflection data. Although there is no improvement in the resolution, the pseudo log traces provide a more convenient way of visually corelating well data to seismic data. A new stratigraphic extrapolation method designed to overcome some of the drawbacks of low resolution is presented. This method consists of relating a model trace (initially derived from well information) to an actual seismic trace by varying the parameters of the model trace within well defined constraints until best match is achieved between them. Extrapolation of the stratigraphy away from the well is performed from trace to trace, the starting model for each trace being determined either from the final model for the previous trace or from an independently postulated model. An interactive computer program is employed for this purpose which allows the incorporation of additional information to the initial model. In this way the final stratigraphic model of the reservoir is the one which best matches the seismic data. Several examples showing the application of the method will be discussed.

As a kind of supergene geological phenomenon, ground fissure has brought great inconvenience to human life. In addition, it also has a close relationship with earthquake. However, it is very difficult to ascertain the extension depth of ground fissure since its concealment and uncertainty. In this paper, 3D seismic exploration is used to detect ground fissure in Shanxi Province of China. Specific parameters for seismic data acquisition, processing and interpretation are analysed. Firstly, seismic data acquisition method and its corresponding parameters are discussed. Small dose explosive sources and high frequency geophones are used. Small trace interval and appropriate fold are also adopted. Secondly, seismic data processing is processed from shot record to seismic profile. Multi-domain loop iteration de-noising is used to get high signal-to-noise ratio data. Accurate near surface model, interactive iteration and residual static correction are used to eliminate the impact of low velocity zone and the static correction problem. Large common middle point bin and small velocity analysis interval are used for high accuracy velocity spectrum analysis. The mute parameter of stretching distortion and the migration aperture are researched for shallow ground fissure detection. Thirdly, seismic data interpretation is processed to get ground fissure distribution. Fault enhanced filter is used to improve the signal-to-noise ratio effectively and the chimney cube is used to identify ground fissure automatically. Thus, the specific 3D seismic exploration method used in this paper is suitable for ground fissure detection. Cited as : Shi, S., Liu, Z., Feng, J., Feng, G., Li, M. Using 3D seismic exploration to detect ground fissure. Advances in Geo-Energy Research, 2020, 4(1): 13-19, doi: 10.26804/ager.2020.01.02

High-amplitude noise could interfere with useful seismic signals, affecting our ability in processing and interpreting seismic data. Thus, attenuating seismic noise is an important task in seismic processing. Total variation (TV) has played an important role in many steps of seismic data processing but always neglected the seismic structural information. Directional TV (DTV), however, considers the structural direction of seismic events but tends to cause the staircasing effect on seismic records based on the first-order formulation. Here, we develop a high-order DTV (HDTV) method for seismic denoising. It considers the local structural direction of the seismic data and calculates the higher order derivatives of seismic images to avoid the staircasing effect. We design several synthetic models that are contaminated by various types of random noise to test the denoising ability. The denoising performance of our new method is compared with the first-order DTV, conventional high-order TV, and TV regularization methods from two aspects, i.e., the signal-to-noise ratio and the effective signal leakage degree. Then, the advantages of the proposed method are further validated via several field seismic data sets.

While seismic data contains an abundance of useful information about the subsurface, it is also contaminated with disturbing recorded energy, coherent and random noise. A crucial step in seismic data processing, therefore, is denoising. In this work, we use a U-Net-based encoder-decoder network that uses ResNeXt blocks rather than traditional convolutions as a denoising tool. Furthermore, we add self-attention to the ResNext blocks in the deeper part of the neural network architecture. We compare the results with those obtained with the same network, but without attention, in order to investigate, whether self-attention improves machine-learning-based processing of seismic data. The supervised training with the implemented attention mechanism leads to improved denoising results than without attention. The deleted noise contains less primary energy and thus leads to a better conservation of the desired seismic signal.

The collection of a range of different seismic data types has greatly improved our understanding of the crustal architecture of Australia's Archaean Yilgarn Craton over the last few years. These seismic data include broadband seismic studies, seismic receiver functions, wide-angle recordings and mine-scale to deep seismic reflection transects. Each data set provides information on the three-dimensional (3D) tectonic model of the Yilgarn Craton from the craton scale through to the mine scale. This paper demonstrates that the integration and rationalisation of these different seismic data sets into a multi-scale 3D geological/seismic model, that can be visualised at once in a single software package, and incorporating all available data sets, significantly enhances this understanding. This enhanced understanding occurred because the integrated 3D model allowed easy and accurate comparison of one result against another, and facilitated the integrated questioning and interrogation across scales and seismic method. As a result, there are feedback questions regarding understanding of the individual seismic data sets themselves, as well as the Yilgarn Craton as a whole. The methodology used, including all the data sets in the model range, had to allow for the wide range of data sets, frequencies and seismic modes. At the craton scale, P-wave, S-wave and surface wave variations constrained the 3D lithospheric velocity model, revealing noticeable large-scale velocity variations within and across the craton. An interesting feature of the data, easily identified in 3D, is the presence of a fast S-wave velocity anomaly (> 4.8 km s − 1 ) within the upper mantle. This velocity anomaly dips east and has a series of step-down offsets that coincide approximately with province and terrane boundaries of the Yilgarn Craton. One-dimensional receiver function profiles show variations in their crustal velocity across the craton. These crustal velocity variations are consistent with the larger-scale geological subdivision of the craton, and provide characteristic profiles for provinces and terranes. The receiver function results and the deep seismic reflection data both agree on the depth to the Moho, and both indicate an increase in Moho depth to the east. The 2D seismic refraction results in the south-west of the craton provide crustal thickness information, an indication of middle and lower crustal compositions, and information regarding the broad-scale architectural framework. At the province- and terrane-scale, the deep seismic reflection data and the mine-scale seismic data provide geometric constraints on crustal architecture, in particular the orientation of the region's fault systems as well as variations in the thickness of the granite–greenstone succession. Integration of the results from wide-angle seismic refraction data coincident with the deep seismic reflection data provided additional constraints on likely upper crustal lithologies. The integrated 3D seismic model implies the dominant geodynamic process involved the development of an orogenic belt that developed with a series of contractional (folding and thrusting) events, separated by equally important extensional events. The seismic reflection data in particular suggests that extensional movement on many shear zones was more common than previously thought. The seismic reflection data suggest that the dominant mineral systems involved deeply sourced fluid flowing up crustal-penetrating shear zones. These deeply sourced fluids were further focussed into sites located above fault-breached domal regions in the upper crust.

Volcanic reservoir exploration is quite challenging due to its rapid inherent velocity variation. The paper presents a case study of a gas-bearing volcanic reservoir, where zero-offset VSP, Walkaway VSP with eight azimuths, simultaneous 3D VSP and full-azimuth surface seismic data were acquired. A VSP-driven surface seismic data processing workflow was introduced to obtain a better image of the reservoir. Rather than conventional way of using VSP data for geologic body delineation, this workflow utilized VSP data to estimate parameters for surface seismic processing. Based on this workflow, the surface seismic data were processed and then used to estimate Poisson's ratio cube and fracture maps amenable for prediction of gas distribution in the reservoir. We demonstrated that the newly-processed surface seismic data with VSP-driven workflow are more reliable than that without assistance of VSP data, which can also be applied to other gas-bearing unconventional reservoirs.