PEMODELAN SEISMIK PADA STRUKTUR GEOLOGI KOMPLEKS MENGGUNAKAN METODE COMMON REFLECTION SURFACE (CRS)

Pemodelan seismik merupakan tahap penting untuk memahami respon bawah permukaan bumi terhadap gelombang seismik yang digambarkan dalam bentuk energi seismik refleksi. Walaupun saat ini teknologi pengolahan data seismik telah meningkat dengan pesat, ketidakakuratan posisi reflektor dalam penampang seismik yang dihasilkan tetap saja sering ditemukan, terutama pada daerah dengan struktur geologi kompleks. Model geologi struktur kompleks pada penelitian ini mengacu pada arsitektur glasiotektonik di daerah Fur Knudeklint, Denmark yang memiliki banyak patahan dan lipatan dengan skala kecil. Hasil simulasi perambatan gelombang dengan metode penjalaran sinar dilakukan dari dua arah akuisisi berbeda menggunakan perangkat lunak Norsar 2D untuk mendapatkan seismogram sintetik. Data yang dihasilkan kemudian digunakan sebagai masukan untuk pengolahan data seismik secara konvensional maupun menggunakan metode Common Reflector Surface (CRS) Stack. Hasilnya menunjukkan bahwa akuisisi data dari arah foot wall memberikan citra reflektor yang lebih representatif dibandingkan dari arah sebaliknya. Penegasan kualitas reflektor terlihat jelas di tiga area utama, yaitu CDP 20-100, CDP 120-180 dan CDP 160-330. Dengan demikian, metode CRS Stack berhasil merekonstruksi reflektor-reflektor berupa lipatan kecil dan perlapisan tipis pada struktur geologi kompleks dengan kualitas lebih baik dibandingkan metode konvensional.

Efficient spreading strategy for global solution search using a trust-region optimization method: an application to CRS stacking problem

Some processes in seismic imaging can be formulated as a coherence-based problem, such as common reflection surface (CRS) stacking.The approach consists of obtaining the CRS attributes that provide the best fitting CRS surface in the multi-coverage data. The problem can be described as an optimization problem and solved by an optimization algorithm. Generally, quick convergent optimization algorithms are local solvers. To obtain the global solution, an efficient strategy is proposed to be used combined with a trust-region local optimization method. This strategy can be divided into two features: sequential parameters search and spreading solution.The idea is to first find solutions on a coarse output grid by sequential parameter search. This feature is based on constructing splines to estimate the maxima of the objective function in one dimension. These estimated maxima are the initial approximations to the local solver.The optimization algorithm obtains the parameters by sequentially solving one, two, and three-dimensional problems. Once the solutions are found on the coarse grid, useful information is propagated in the neighborhood to obtain the solutions on all output grid. Although the idea of spreading solution seems easy, its implementation is complex. It is essential to consider the properties of the problem as well as the properties of the optimization algorithm. Through some numerical experiments, the results using this strategy are shown. The use of sequential parameter search and spreading solution provides an improvement not only in the parameters but also in computational time.

Extending the usage of graphics processing units on the cloud for cost savings on seismic data regularization

ABSTRACT. The usage of graphics processing units is already known as an alternative to traditional multi-core CPU processing, offering faster performance in the order of dozens of times in parallel tasks. Another new computing paradigm is cloud computing usage as a replacement to traditional in-house clusters, enabling seemingly unlimited computation power, no maintenance costs, and cutting-edge technology, dynamically on user demand. Previously those two tools were used to accelerate the estimation of Common Reflection Surface (CRS) traveltime parameters, both in zero-offset and finite-offset domain, delivering very satisfactory results with large time savings from GPU devices alongside cost savings on the cloud. This work extends those results by using GPUs on the cloud to accelerate the Offset Continuation Trajectory (OCT) traveltime parameter estimation. The results have shown that the time and cost savings from GPU devices’ usage are even larger than those seen in the CRS results, being up to fifty times faster and sixty times cheaper. This analysis reaffirms that it is possible to save both time and money when using GPU devices on the cloud and concludes that the larger the data sets are and the more computationally intensive the traveltime operators are, we can see larger improvements.Keywords: cloud computing, GPU, seismic processing. Estendendo o uso de placas gráficas na nuvem para economias em regularização de dados sísmicosRESUMO. O uso de aceleradores gráficos para processamento já é uma alternativa conhecida ao uso de CPUs multi-cores, oferecendo um desempenho na ordem de dezenas de vezes mais rápido em tarefas paralelas. Outro novo paradigma de computação é o uso da nuvem computacional como substituta para os tradicionais clusters internos, possibilitando o uso de um poder computacional aparentemente infinito sem custo de manutenção e com tecnologia de ponta, dinamicamente sob demanda de usuário. Anteriormente essas duas ferramentas foram utilizadas para acelerar a estimação de parâmetros do tempo de trânsito de Common Reflection Surface (CRS), tanto em zero-offset quanto em offsets finitos, obtendo resultados satisfatórios com amplas economias tanto de tempo quanto de dinheiro na nuvem. Este trabalho estende os resultados obtidos anteriormente, desta vez utilizando GPUs na nuvem para acelerar a estimação de parâmetros do tempo de trânsito em Offset Continuation Trajectory (OCT). Os resultados obtidos mostraram que as economias de tempo e dinheiro foram ainda maiores do que aquelas obtidas no CRS, sendo até cinquenta vezes mais rápido e sessenta vezes mais barato. Esta análise reafirma que é possível economizar tanto tempo quanto dinheiro usando GPUs na nuvem, e conclui que quanto maior for o dado e quanto mais computacionalmente intenso for o operador, maiores serão os ganhos de desempenho observados e economias.Palavras-chave: computação em nuvem, GPU, processamento sísmico.

Application of common reflection surface (CRS) to velocity variation with azimuth (VVAz) inversion of the relatively narrow azimuth 3D seismic land data

The fracture direction and its intensity are critical properties related to hydrocarbon characterization and identification. Both these properties have an essential role in identifying the direction of hydrocarbon migration, determining the sweet spot area, and optimizing the drilling design. The velocity variation with azimuth (VVAz) is a well-known method to estimate the fracture direction and its intensity. This method is of widespread interest because it predicts the properties based on seismic data without any practical constraints. Despite this interest, the technique requires rich azimuth 3D seismic data in our case, which is rare. This study aims to apply regularization and interpolation by including the wave front attributes based on the Common Reflection Surface (CRS) method before the VVAz inversion. The motivation of using the CRS method is to enrich the current azimuth of the 3D seismic data and improve the S/N ratio. The synthetic and the real 3D seismic data are evaluated to examine the interpolation scheme of the proposed CRS method’s performance. Based on the evaluation of the 3D seismic data after regularization, the amplitude versus offset (AVO) phenomena, and the VVAz inversion results are relatively consistent (or matched) with the model. A similar result is found for the case of real 3D seismic data. A significant positive correlation between the fracture intensity of FMI and the real seismic data of about 0.9 is obtained. Therefore, CRS can be used as a regularization and interpolation method before the VVAz inversion of the relatively narrow azimuth 3D seismic data.

Nonlinear beamforming for enhancement of 3D prestack land seismic data

We have developed nonlinear beamforming (NLBF), a method for enhancing modern 3D prestack seismic data acquired onshore with small field arrays or single sensors in which weak reflected signals are buried beneath the strong scattered noise induced by a complex near surface. The method is based on the ideas of multidimensional stacking techniques, such as the common-reflection-surface stack and multifocusing, but it is designed specifically to improve the prestack signal-to-noise ratio of modern 3D land seismic data. Essentially, NLBF searches for coherent local events in the prestack data and then performs beamforming along the estimated surfaces. Comparing different gathers that can be extracted from modern 3D data acquired with orthogonal acquisition geometries, we determine that the cross-spread domain (CSD) is typically the most convenient and efficient. Conventional noise removal applied to modern data from small arrays or single sensors does not adequately reveal the underlying reflection signal. Instead, NLBF supplements these conventional tools and performs final aggregation of weak and still broken reflection signals, where the strength is controlled by the summation aperture. We have developed the details of the NLBF algorithm in CSD and determined the capabilities of the method on real 3D land data with the focus on enhancing reflections and early arrivals. We expect NLBF to help streamline seismic processing of modern high-channel-count and single-sensor data, leading to improved images as well as better prestack data for estimation of reservoir properties.

Appication of ZO-CRS Stack on Residual PP Removal of PS Component in Converted-Wave Sesimic Reflection Processing

A high-quality image of the PS component is needed since applying the converted-wave seismic method has increased significantly in hydrocarbon exploration, especially in interpreting the detail and complexity of structure or reservoir zones. The incident P-wave on a surface produces a reflected and converted P-S wave. Converted-wave seismic uses the multicomponent receiver that records both vertical and horizontal components. The vertical component is assumed to correspond to the compressional PP wave, and the horizontal corresponds to the PS converted-wave. To better understand how to image better the PS component, synthetic seismic data with the shallow gas and relatively complex model are constructed by the full-waveform modeling. This study aims to improve the imaging quality in the PS section to remove the residual PP events on the horizontal data refer to our previous study. In this study, to obtain the more reliable PS data, the residual PP reflections have been removed by applying the Zero Offset Common Reflection Surface (ZO CRS) Stack of the PS component. The results of this study, the imaging quality is better than that in the previous study.