Pub Date : 1900-01-01DOI: 10.3997/2214-4609.202112756
J. Chigbo, M. Smith, A. Onojete, P. Ukerun, J. Mascomère, E. Ekut, M. Esotu, S. P. Palome
The first depth velocity model over the field was created in 2011, using data acquired in 2008 as part of a high definition (HD) survey collected on a 6.25 x 12.5 binning grid with relatively shallow streamer and gun depths (5 m and 6 m respectively) aimed at maximizing the signal bandwidth and spatial resolution of the faulted sandstone reservoir. Here we present further work updating the 2011 model by combining the 2008 HD survey with an earlier 1997 regional survey to achieve a dual azimuth reprocessing.
该油田的第一个深度速度模型是在2011年创建的，使用的数据是2008年在6.25 x 12.5 bin网格上收集的高清(HD)调查数据的一部分，该网格的拖缆和枪的深度相对较浅(分别为5米和6米)，旨在最大限度地提高断层砂岩储层的信号带宽和空间分辨率。在这里，我们提出了进一步的工作，通过结合2008年HD测量和1997年早期的区域测量来更新2011年模型，以实现双方位角再处理。
{"title":"Multi Azimuth Imaging of an Oil-bearing Faulted Sandstone Reservoir: A Nigeria deep offshore Case study","authors":"J. Chigbo, M. Smith, A. Onojete, P. Ukerun, J. Mascomère, E. Ekut, M. Esotu, S. P. Palome","doi":"10.3997/2214-4609.202112756","DOIUrl":"https://doi.org/10.3997/2214-4609.202112756","url":null,"abstract":"The first depth velocity model over the field was created in 2011, using data acquired in 2008 as part of a high definition (HD) survey collected on a 6.25 x 12.5 binning grid with relatively shallow streamer and gun depths (5 m and 6 m respectively) aimed at maximizing the signal bandwidth and spatial resolution of the faulted sandstone reservoir. Here we present further work updating the 2011 model by combining the 2008 HD survey with an earlier 1997 regional survey to achieve a dual azimuth reprocessing.","PeriodicalId":143998,"journal":{"name":"82nd EAGE Annual Conference & Exhibition","volume":"74 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134085366","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 : 1900-01-01DOI: 10.3997/2214-4609.202112711
W. Zhonghua, Z. Kai, J. Ping, L. Zhenchun, L. Honghui, X. Wang
Compared with acoustic data tomography, the elastic vector wave tomography can more effectively reflect the propagation law of elastic waves in underground media. S-wave and P-wave imaging can be combined to obtain a more accurate description of the medium. There are two problems in the conventional multi-component seismic data processing. One is that the Z and X components of the multi-component seismic data are simply treated as P and S waves respectively, and this kind of approximate processing of different wave shapes will produce a strong illusion. Secondly, PP-wave and PS-wave are processed separately. In this method, P-wave and S-wave components are obtained by wave field separation based on acoustic wave equation, which strongly depends on the precision of wave field separation. In addition, the construction process of scalar wave field ignores the vector characteristics of elastic wave propagation, so it is urgent to process and interpret multi-component seismic data based on elastic vector wave framework.
{"title":"Travel time tomography in elastic wave imaging domain based on ADCIGs","authors":"W. Zhonghua, Z. Kai, J. Ping, L. Zhenchun, L. Honghui, X. Wang","doi":"10.3997/2214-4609.202112711","DOIUrl":"https://doi.org/10.3997/2214-4609.202112711","url":null,"abstract":"Compared with acoustic data tomography, the elastic vector wave tomography can more effectively reflect the propagation law of elastic waves in underground media. S-wave and P-wave imaging can be combined to obtain a more accurate description of the medium. There are two problems in the conventional multi-component seismic data processing. One is that the Z and X components of the multi-component seismic data are simply treated as P and S waves respectively, and this kind of approximate processing of different wave shapes will produce a strong illusion. Secondly, PP-wave and PS-wave are processed separately. In this method, P-wave and S-wave components are obtained by wave field separation based on acoustic wave equation, which strongly depends on the precision of wave field separation. In addition, the construction process of scalar wave field ignores the vector characteristics of elastic wave propagation, so it is urgent to process and interpret multi-component seismic data based on elastic vector wave framework.","PeriodicalId":143998,"journal":{"name":"82nd EAGE Annual Conference & Exhibition","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129311359","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 : 1900-01-01DOI: 10.3997/2214-4609.202112759
C. Jestin, C. Huynh, C. Hibert
{"title":"Machine Learning integrated to pipeline monitoring with Distributed Acoustic Sensing","authors":"C. Jestin, C. Huynh, C. Hibert","doi":"10.3997/2214-4609.202112759","DOIUrl":"https://doi.org/10.3997/2214-4609.202112759","url":null,"abstract":"","PeriodicalId":143998,"journal":{"name":"82nd EAGE Annual Conference & Exhibition","volume":"51 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123162910","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 : 1900-01-01DOI: 10.3997/2214-4609.202112789
J. Cao, G. Blacquière
{"title":"Integrated source and receiver deghosting using sparse inversion","authors":"J. Cao, G. Blacquière","doi":"10.3997/2214-4609.202112789","DOIUrl":"https://doi.org/10.3997/2214-4609.202112789","url":null,"abstract":"","PeriodicalId":143998,"journal":{"name":"82nd EAGE Annual Conference & Exhibition","volume":"64 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121517827","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 : 1900-01-01DOI: 10.3997/2214-4609.202112719
C. Jiang, L. Han, Z. Hu, Z. Xu, G. Wang
The main reservoir of lower Miocene in X area of South China Sea is sandstone in Zhujiang Formation, and the fluid property is water saturated or gas-water same layer. At present, numerical simulation is often used to analyze the seismic response characteristics of reservoir and fluid in exploration. Based on the results of numerical simulation and seismic technology, fluid exploration has been carried out, and some results have been achieved. However, the actual seismic data is affected by many factors, such as formation conditions, acquisition, processing, etc, and the reservoir change and fluid response are easy to be destroyed. Therefore, the analysis of the seismic response characteristics of the reservoir and fluid in the actual seismic data is much more complicated than the numerical simulation analysis [Li Genyong 2008]. In order to get closer to the real seismic data and further clarify the seismic response characteristics of reservoir and fluid, we make a 3D seismic physical model which simulates real stratum and fluid bearing sand bodies in X area of South China Sea, use the actual field acquisition parameters to acquire physical modeling data, then use these data to analyze and compare the sandstone of water saturated layer and gas-water same layer in lower Miocene Zhujiang formation. Finally we summarize the seismic response characteristics of the reservoir and fluid in the lower Miocene Pearl River formation in X area of South China Sea and provide an effective method and favorable basis for the next exploration.
{"title":"Study on the Response Characteristics of Gas Reservoir in X Area by 3D Seismic Physical Simulation","authors":"C. Jiang, L. Han, Z. Hu, Z. Xu, G. Wang","doi":"10.3997/2214-4609.202112719","DOIUrl":"https://doi.org/10.3997/2214-4609.202112719","url":null,"abstract":"The main reservoir of lower Miocene in X area of South China Sea is sandstone in Zhujiang Formation, and the fluid property is water saturated or gas-water same layer. At present, numerical simulation is often used to analyze the seismic response characteristics of reservoir and fluid in exploration. Based on the results of numerical simulation and seismic technology, fluid exploration has been carried out, and some results have been achieved. However, the actual seismic data is affected by many factors, such as formation conditions, acquisition, processing, etc, and the reservoir change and fluid response are easy to be destroyed. Therefore, the analysis of the seismic response characteristics of the reservoir and fluid in the actual seismic data is much more complicated than the numerical simulation analysis [Li Genyong 2008]. In order to get closer to the real seismic data and further clarify the seismic response characteristics of reservoir and fluid, we make a 3D seismic physical model which simulates real stratum and fluid bearing sand bodies in X area of South China Sea, use the actual field acquisition parameters to acquire physical modeling data, then use these data to analyze and compare the sandstone of water saturated layer and gas-water same layer in lower Miocene Zhujiang formation. Finally we summarize the seismic response characteristics of the reservoir and fluid in the lower Miocene Pearl River formation in X area of South China Sea and provide an effective method and favorable basis for the next exploration.","PeriodicalId":143998,"journal":{"name":"82nd EAGE Annual Conference & Exhibition","volume":"90 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124615207","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 : 1900-01-01DOI: 10.3997/2214-4609.202112790
N. Wang, T. Lin, X. Wang, C. Ning, Z. Lyu, N. Li, P. Yang, B. Luo
The southeast Iraq (SE) occupies a significant role in the oil and gas industry of the world, which was ramp sedimentary environment in the foreland basin of Mesopotamia during the Late Cretaceous. Massive porous bioclastic limestone reservoirs were developed in the Khasib, Sadi and Hartha Formation of the Upper Cretaceous, while the complex porosity and strong heterogeneity in the study area severely restrict the further development.
{"title":"Evolution of Paleogeomorphy and sedimentary of the Late Cretaceous on the H oilfield, Iraq","authors":"N. Wang, T. Lin, X. Wang, C. Ning, Z. Lyu, N. Li, P. Yang, B. Luo","doi":"10.3997/2214-4609.202112790","DOIUrl":"https://doi.org/10.3997/2214-4609.202112790","url":null,"abstract":"The southeast Iraq (SE) occupies a significant role in the oil and gas industry of the world, which was ramp sedimentary environment in the foreland basin of Mesopotamia during the Late Cretaceous. Massive porous bioclastic limestone reservoirs were developed in the Khasib, Sadi and Hartha Formation of the Upper Cretaceous, while the complex porosity and strong heterogeneity in the study area severely restrict the further development.","PeriodicalId":143998,"journal":{"name":"82nd EAGE Annual Conference & Exhibition","volume":"27 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122168035","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 : 1900-01-01DOI: 10.3997/2214-4609.202112716
R. Shao, L. Xiao, G. Liao
Traditional methods for reservoir parameters prediction with logs are based on petrophysics knowledge, such as volumetric models and response functions (Darwin and Julian, 2007). The advantage of those methods is that the relationship between the logs and reservoir parameters is clear, there is a theoretical basis, and it can be explained; the disadvantage is that the response functions can only be constructed for the known physical relationship, and the unknown physical relationship may be ignored. Whereas using neural network to predict reservoir parameters, we can map the relationship between logs and reservoir parameters as long as building a suitable model and have a large number of training data. With the help of neural network, we can map the unknown physical relationship without much geological expertise. The existing research of reservoir parameter prediction neural network with logs only focuses on one kind of reservoir parameter prediction modeling, ignoring the relationship between reservoir parameters. In this paper, relevance transfer learning is introduced, which using the knowledge of petrophysics to improve the performance of neural network reservoir parameters prediction.
利用测井资料预测储层参数的传统方法是基于岩石物理学知识，如体积模型和响应函数(Darwin and Julian, 2007)。这些方法的优点是测井曲线与储层参数之间的关系清晰，有理论依据，可以解释;缺点是只能针对已知的物理关系构造响应函数，而可能忽略未知的物理关系。而利用神经网络进行储层参数预测，只要建立合适的模型，并有大量的训练数据，就可以映射出测井曲线与储层参数之间的关系。在神经网络的帮助下，我们可以在没有太多地质专业知识的情况下绘制未知的物理关系。现有的利用测井资料进行储层参数预测的神经网络研究只集中在一种储层参数预测建模上，忽略了储层参数之间的关系。本文介绍了关联迁移学习方法，利用岩石物理学知识提高神经网络储层参数预测的性能。
{"title":"Relevance Based Transfer Learning for Reservoir Parameters Prediction with Logs","authors":"R. Shao, L. Xiao, G. Liao","doi":"10.3997/2214-4609.202112716","DOIUrl":"https://doi.org/10.3997/2214-4609.202112716","url":null,"abstract":"Traditional methods for reservoir parameters prediction with logs are based on petrophysics knowledge, such as volumetric models and response functions (Darwin and Julian, 2007). The advantage of those methods is that the relationship between the logs and reservoir parameters is clear, there is a theoretical basis, and it can be explained; the disadvantage is that the response functions can only be constructed for the known physical relationship, and the unknown physical relationship may be ignored. Whereas using neural network to predict reservoir parameters, we can map the relationship between logs and reservoir parameters as long as building a suitable model and have a large number of training data. With the help of neural network, we can map the unknown physical relationship without much geological expertise. The existing research of reservoir parameter prediction neural network with logs only focuses on one kind of reservoir parameter prediction modeling, ignoring the relationship between reservoir parameters. In this paper, relevance transfer learning is introduced, which using the knowledge of petrophysics to improve the performance of neural network reservoir parameters prediction.","PeriodicalId":143998,"journal":{"name":"82nd EAGE Annual Conference & Exhibition","volume":"43 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132111519","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 : 1900-01-01DOI: 10.3997/2214-4609.202112730
M. A. Iqbal, P. Mandal, R. Rezaee, J. Sarout, G. Smith
{"title":"Integration of mechanical stratigraphy with lithofacies in Goldwyer shale for selecting producible and hydraulic fracturing layers","authors":"M. A. Iqbal, P. Mandal, R. Rezaee, J. Sarout, G. Smith","doi":"10.3997/2214-4609.202112730","DOIUrl":"https://doi.org/10.3997/2214-4609.202112730","url":null,"abstract":"","PeriodicalId":143998,"journal":{"name":"82nd EAGE Annual Conference & Exhibition","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124345269","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 : 1900-01-01DOI: 10.3997/2214-4609.202112757
J. Wang, J. Zhang, G. Wu, Y. Wang, Q. Wang
{"title":"A Young’s modulus inversion and fracture prediction method and application for offshore wide azimuthal OBC data","authors":"J. Wang, J. Zhang, G. Wu, Y. Wang, Q. Wang","doi":"10.3997/2214-4609.202112757","DOIUrl":"https://doi.org/10.3997/2214-4609.202112757","url":null,"abstract":"","PeriodicalId":143998,"journal":{"name":"82nd EAGE Annual Conference & Exhibition","volume":"12 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128110441","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}
京公网安备 11010802042870号
京ICP备2023020795号-1
扫码关注我们
求助内容：
应助结果提醒方式：