Pub Date : 2019-06-03DOI: 10.3997/2214-4609.201901405
J. Naranjo, D. Dieulangard, M. Pfister
Summary Carpet geometries, or equal spacing of either source or receiver positions in inline and crossline directions (e.g., 50 x 50 m) are often used in simultaneous source acquisition. By using carpet geometries, trace densities of simultaneous source data sets have increased to several million traces per sq km. In practice, however, carpets are never fully acquired in the field due to the presence of natural and man-made obstructions or environmental conditions of the survey area. Further, carpet geometries are not applicable for use in all areas when considering urban, steep mountainous terrains and forested areas. To date, carpet geometries have been used in areas of open access with surface sources, such as vibroseis on land and in marine environments, primarily for ocean bottom sensor surveys and 3D VSPs. Applying this geometry in the field requires different approaches to traditional methods. Focusing field operations on high survey efficiency to balance source and receiver movement while maximizing the trace density that can be acquired amidst obstacles has produced the best results. This paper focuses on operational aspects of applying the carpet acquisition geometries with a discussion on future uses including conceivable carpet receiver geometries.
地毯几何形状，或在直线和交叉方向上的源或接收器位置等间距(例如，50 x 50 m)通常用于同时获取源。通过使用地毯几何形状，同时源数据集的迹密度增加到每平方公里数百万条迹。然而，在实践中，由于存在自然和人为障碍或调查区域的环境条件，地毯从未在现场完全获得。此外，当考虑到城市、陡峭的山区和森林地区时，地毯几何形状并不适用于所有地区。到目前为止，地毯式几何形状已被用于具有地面震源的开放区域，例如陆地和海洋环境中的可控震源，主要用于海底传感器调查和3D vsp。在油田中应用这种几何结构需要采用不同于传统方法的方法。将现场作业重点放在高测量效率上，以平衡源和接收器的运动，同时最大限度地提高在障碍物中可以获得的迹线密度，从而产生了最佳效果。本文侧重于应用地毯采集几何形状的操作方面，并讨论了未来的用途，包括可能的地毯接收器几何形状。
{"title":"Using Carpet Geometries in Simultaneous Source Acquisition","authors":"J. Naranjo, D. Dieulangard, M. Pfister","doi":"10.3997/2214-4609.201901405","DOIUrl":"https://doi.org/10.3997/2214-4609.201901405","url":null,"abstract":"Summary Carpet geometries, or equal spacing of either source or receiver positions in inline and crossline directions (e.g., 50 x 50 m) are often used in simultaneous source acquisition. By using carpet geometries, trace densities of simultaneous source data sets have increased to several million traces per sq km. In practice, however, carpets are never fully acquired in the field due to the presence of natural and man-made obstructions or environmental conditions of the survey area. Further, carpet geometries are not applicable for use in all areas when considering urban, steep mountainous terrains and forested areas. To date, carpet geometries have been used in areas of open access with surface sources, such as vibroseis on land and in marine environments, primarily for ocean bottom sensor surveys and 3D VSPs. Applying this geometry in the field requires different approaches to traditional methods. Focusing field operations on high survey efficiency to balance source and receiver movement while maximizing the trace density that can be acquired amidst obstacles has produced the best results. This paper focuses on operational aspects of applying the carpet acquisition geometries with a discussion on future uses including conceivable carpet receiver geometries.","PeriodicalId":6840,"journal":{"name":"81st EAGE Conference and Exhibition 2019","volume":"3 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2019-06-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"90050484","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2019-06-03DOI: 10.3997/2214-4609.201900852
M. Zhang, Y. Liu, M. Bai, Y. Chen, Y. Zhang
Summary Suppressing random noise is very important to improve the signal-to-noise ratio of seismic data. We propose a novel method to attenuate random noise using deep convolutional autoencoder, which belongs to the unsupervised feature learning. We directly use the noisy data rather than a relatively noise-free data as the training target to construct the cost function and design a robust convolutional autoencoder network that can achieve random noise attenuation. Therefore, we always have an available input dataset to train the neural network, which can save us the trouble of seeking a relatively clean data. We use normalization and patch sampling to build training dataset and test dataset from raw seismic data. The back-propagation algorithm is used to optimize the cost function. The optimized parameters of convolution filters can be obtained after a stable optimization. The final denoised result can be reconstructed via the optimized convolutional autoencoder. Real data test proves the effectiveness of the proposed method.
{"title":"Random Noise Attenuation Using Deep Convolutional Autoencoder","authors":"M. Zhang, Y. Liu, M. Bai, Y. Chen, Y. Zhang","doi":"10.3997/2214-4609.201900852","DOIUrl":"https://doi.org/10.3997/2214-4609.201900852","url":null,"abstract":"Summary Suppressing random noise is very important to improve the signal-to-noise ratio of seismic data. We propose a novel method to attenuate random noise using deep convolutional autoencoder, which belongs to the unsupervised feature learning. We directly use the noisy data rather than a relatively noise-free data as the training target to construct the cost function and design a robust convolutional autoencoder network that can achieve random noise attenuation. Therefore, we always have an available input dataset to train the neural network, which can save us the trouble of seeking a relatively clean data. We use normalization and patch sampling to build training dataset and test dataset from raw seismic data. The back-propagation algorithm is used to optimize the cost function. The optimized parameters of convolution filters can be obtained after a stable optimization. The final denoised result can be reconstructed via the optimized convolutional autoencoder. Real data test proves the effectiveness of the proposed method.","PeriodicalId":6840,"journal":{"name":"81st EAGE Conference and Exhibition 2019","volume":"7 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2019-06-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"90180990","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2019-06-03DOI: 10.3997/2214-4609.201901335
M. Janas, T. Podhalańska, A. Głuszyński, J. Roszkowska-Remin, R. Pachytel
Summary The results have shown that the Baltic Basin (both onshore and offshore) is the most promising area for the future shale gas and shale oil exploration in Poland. The area is prospective in the oil, wet and dry gas thermal maturity regimes and Sasino Fm out of three mentioned lower Paleozoic shale formations is considered to have the greatest potential for future shale gas and shale oil production due to its favourable reservoir quality. From the petroleum geochemical point of view, Piasnica Fm, an equivalent of the Alum Shale (upper Cambrian-lower Ordovician) and Jantar Fm (lower Silurian) shales are the best source rocks across the Baltic Basin.
{"title":"How Did the Baltic Basin Source Rocks Become the Shale Gas Exploration Targets in Poland?","authors":"M. Janas, T. Podhalańska, A. Głuszyński, J. Roszkowska-Remin, R. Pachytel","doi":"10.3997/2214-4609.201901335","DOIUrl":"https://doi.org/10.3997/2214-4609.201901335","url":null,"abstract":"Summary The results have shown that the Baltic Basin (both onshore and offshore) is the most promising area for the future shale gas and shale oil exploration in Poland. The area is prospective in the oil, wet and dry gas thermal maturity regimes and Sasino Fm out of three mentioned lower Paleozoic shale formations is considered to have the greatest potential for future shale gas and shale oil production due to its favourable reservoir quality. From the petroleum geochemical point of view, Piasnica Fm, an equivalent of the Alum Shale (upper Cambrian-lower Ordovician) and Jantar Fm (lower Silurian) shales are the best source rocks across the Baltic Basin.","PeriodicalId":6840,"journal":{"name":"81st EAGE Conference and Exhibition 2019","volume":"76 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2019-06-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"90382905","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2019-06-03DOI: 10.3997/2214-4609.201901253
T. Dreyer, F. Tillmans, R. Gawthorpe
{"title":"Late Jurassic Syn-Rift Turbidite Fairways in the Northern Viking Graben – From Seismic to Reservoir Scale","authors":"T. Dreyer, F. Tillmans, R. Gawthorpe","doi":"10.3997/2214-4609.201901253","DOIUrl":"https://doi.org/10.3997/2214-4609.201901253","url":null,"abstract":"","PeriodicalId":6840,"journal":{"name":"81st EAGE Conference and Exhibition 2019","volume":"1 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2019-06-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"88824744","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2019-06-03DOI: 10.3997/2214-4609.201901205
A. Alfaraj, M. Almubarak, F. Herrmann
{"title":"Correcting for Short-Wavelength Statics with Low Rank Approximation","authors":"A. Alfaraj, M. Almubarak, F. Herrmann","doi":"10.3997/2214-4609.201901205","DOIUrl":"https://doi.org/10.3997/2214-4609.201901205","url":null,"abstract":"","PeriodicalId":6840,"journal":{"name":"81st EAGE Conference and Exhibition 2019","volume":"40 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2019-06-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"88871461","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2019-06-03DOI: 10.3997/2214-4609.201901206
M. Gloeckner, J. Walda, D. Gajewski, T. Roth, C. Berndt, Dirk Klaeschen
{"title":"Challenges in Velocity-Model Building With 3D P-Cable Data","authors":"M. Gloeckner, J. Walda, D. Gajewski, T. Roth, C. Berndt, Dirk Klaeschen","doi":"10.3997/2214-4609.201901206","DOIUrl":"https://doi.org/10.3997/2214-4609.201901206","url":null,"abstract":"","PeriodicalId":6840,"journal":{"name":"81st EAGE Conference and Exhibition 2019","volume":"1 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2019-06-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"83004881","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2019-06-03DOI: 10.3997/2214-4609.201901364
H. Li, S. Greenhalgh, B. Zhang, X. Liu
{"title":"A Robust Q Estimation Scheme Based on an Improved Centroid-Frequency Shift Method for Strongly Attenuating Media","authors":"H. Li, S. Greenhalgh, B. Zhang, X. Liu","doi":"10.3997/2214-4609.201901364","DOIUrl":"https://doi.org/10.3997/2214-4609.201901364","url":null,"abstract":"","PeriodicalId":6840,"journal":{"name":"81st EAGE Conference and Exhibition 2019","volume":"46 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2019-06-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"79057902","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2019-06-03DOI: 10.3997/2214-4609.201901185
L. Leon, M. Hegazy, O. Zdraveva, M. Majdoub, Charles Inyang, K. Hargrove, K. Pasch, John Hollins
Summary A combination of complex geology and limitations imposed by the surface seismic acquisition geometry results in seismic images contaminated by variabilities in wave propagation effects such as illumination. Consequently, imprints of variable illumination compromise the reliability of the amplitude and phase within the seismic image. Additionally, today's conventional methods of amplitude inversion assume that the seismic amplitudes are representative of the earth's acoustic and elastic properties and do not compensate for variable illumination effects. We present a subsalt case study from the Gulf of Mexico demonstrating least-squares migration in the image domain with point-spread functions (PSF) ability to simultaneously correct for illumination effects and produce a higher-resolution image of thin sand beds located in close proximity to base of salt. We discuss our approach for mitigating scattering effects present in the PSFs arising from high-contrast impedance boundaries within the earth model. Finally, we show the results from a poststack depth-domain inversion, providing true amplitude images and acoustic impedance volumes and allowing reliable assessment of the viability of previously identified drilling targets and enabling corresponding augmentation of prospect interpretation.
{"title":"Image-Domain Least-Squares Migration and Depth-Domain Inversion for Subsalt Sand Reservoirs","authors":"L. Leon, M. Hegazy, O. Zdraveva, M. Majdoub, Charles Inyang, K. Hargrove, K. Pasch, John Hollins","doi":"10.3997/2214-4609.201901185","DOIUrl":"https://doi.org/10.3997/2214-4609.201901185","url":null,"abstract":"Summary A combination of complex geology and limitations imposed by the surface seismic acquisition geometry results in seismic images contaminated by variabilities in wave propagation effects such as illumination. Consequently, imprints of variable illumination compromise the reliability of the amplitude and phase within the seismic image. Additionally, today's conventional methods of amplitude inversion assume that the seismic amplitudes are representative of the earth's acoustic and elastic properties and do not compensate for variable illumination effects. We present a subsalt case study from the Gulf of Mexico demonstrating least-squares migration in the image domain with point-spread functions (PSF) ability to simultaneously correct for illumination effects and produce a higher-resolution image of thin sand beds located in close proximity to base of salt. We discuss our approach for mitigating scattering effects present in the PSFs arising from high-contrast impedance boundaries within the earth model. Finally, we show the results from a poststack depth-domain inversion, providing true amplitude images and acoustic impedance volumes and allowing reliable assessment of the viability of previously identified drilling targets and enabling corresponding augmentation of prospect interpretation.","PeriodicalId":6840,"journal":{"name":"81st EAGE Conference and Exhibition 2019","volume":"92 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2019-06-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"83356219","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2019-06-03DOI: 10.3997/2214-4609.201901339
M. Aleardi, A. Salusti
Summary We implement a transdimensional Bayesian approach to solve the 1D elastic full-waveform inversion (FWI) in which the reflectivity algorithm constitutes the forward modelling. In this approach the number of model parameters (i.e. the number of layers) is treated as an unknown, and a reversible jump Markov Chain Monte Carlo algorithm is used to sample the variable-dimension model space. We also treat the noise standard deviation as an unknown parameter to be solved for, thus letting the algorithm infer the appropriate level of data-fitting. A Parallel tempering strategy and a delayed rejection updating scheme are used to improve the efficiency of the probabilistic sampling. We focus the attention to synthetic data inversions, with the aim to draw general conclusions about the suitability of our approach for pre-stack inversion of reflection seismic data. Our tests prove that the implemented inversion algorithm provides a parsimonious solution and successfully estimates model uncertainty, noise level, model dimensionality and elastic parameters. Our experiments also demonstrate that there is a trade-off between property uncertainty and location uncertainty: A strong elastic contrast determines high uncertainty in the model property values, but low uncertainty in the location of the elastic discontinuity.
{"title":"1D Elastic Full-Waveform Inversion Through a Reversible Jump MCMC Algorithm","authors":"M. Aleardi, A. Salusti","doi":"10.3997/2214-4609.201901339","DOIUrl":"https://doi.org/10.3997/2214-4609.201901339","url":null,"abstract":"Summary We implement a transdimensional Bayesian approach to solve the 1D elastic full-waveform inversion (FWI) in which the reflectivity algorithm constitutes the forward modelling. In this approach the number of model parameters (i.e. the number of layers) is treated as an unknown, and a reversible jump Markov Chain Monte Carlo algorithm is used to sample the variable-dimension model space. We also treat the noise standard deviation as an unknown parameter to be solved for, thus letting the algorithm infer the appropriate level of data-fitting. A Parallel tempering strategy and a delayed rejection updating scheme are used to improve the efficiency of the probabilistic sampling. We focus the attention to synthetic data inversions, with the aim to draw general conclusions about the suitability of our approach for pre-stack inversion of reflection seismic data. Our tests prove that the implemented inversion algorithm provides a parsimonious solution and successfully estimates model uncertainty, noise level, model dimensionality and elastic parameters. Our experiments also demonstrate that there is a trade-off between property uncertainty and location uncertainty: A strong elastic contrast determines high uncertainty in the model property values, but low uncertainty in the location of the elastic discontinuity.","PeriodicalId":6840,"journal":{"name":"81st EAGE Conference and Exhibition 2019","volume":"18 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2019-06-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"83493490","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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