82nd EAGE Annual Conference & Exhibition最新文献_第5页

Deep Probabilistic Neural Networks for Geoscience 用于地球科学的深度概率神经网络

82nd EAGE Annual Conference & Exhibition Pub Date : 1900-01-01 DOI: 10.3997/2214-4609.202112782

L. Mosser, E. Naeini

引用次数: 0

Multi Azimuth Imaging of an Oil-bearing Faulted Sandstone Reservoir: A Nigeria deep offshore Case study 含油断陷砂岩储层的多方位成像:尼日利亚深海案例研究

82nd EAGE Annual Conference & Exhibition Pub Date : 1900-01-01 DOI: 10.3997/2214-4609.202112756

J. Chigbo, M. Smith, A. Onojete, P. Ukerun, J. Mascomère, E. Ekut, M. Esotu, S. P. Palome

引用次数: 0

Travel time tomography in elastic wave imaging domain based on ADCIGs 基于ADCIGs的弹性波成像域走时层析成像

82nd EAGE Annual Conference & Exhibition Pub Date : 1900-01-01 DOI: 10.3997/2214-4609.202112711

W. Zhonghua, Z. Kai, J. Ping, L. Zhenchun, L. Honghui, X. Wang

引用次数: 0

Machine Learning integrated to pipeline monitoring with Distributed Acoustic Sensing 机器学习集成到管道监测与分布式声学传感

82nd EAGE Annual Conference & Exhibition Pub Date : 1900-01-01 DOI: 10.3997/2214-4609.202112759

C. Jestin, C. Huynh, C. Hibert

引用次数: 0

Integrated source and receiver deghosting using sparse inversion 利用稀疏反演综合源接收机去重影

82nd EAGE Annual Conference & Exhibition Pub Date : 1900-01-01 DOI: 10.3997/2214-4609.202112789

J. Cao, G. Blacquière

引用次数: 1

Study on the Response Characteristics of Gas Reservoir in X Area by 3D Seismic Physical Simulation X地区气藏三维地震物理模拟响应特征研究

82nd EAGE Annual Conference & Exhibition Pub Date : 1900-01-01 DOI: 10.3997/2214-4609.202112719

C. Jiang, L. Han, Z. Hu, Z. Xu, G. Wang

{"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":null,"pages":null},"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}

引用次数: 0

Evolution of Paleogeomorphy and sedimentary of the Late Cretaceous on the H oilfield, Iraq 伊拉克H油田晚白垩世古地貌与沉积演化

82nd EAGE Annual Conference & Exhibition Pub Date : 1900-01-01 DOI: 10.3997/2214-4609.202112790

N. Wang, T. Lin, X. Wang, C. Ning, Z. Lyu, N. Li, P. Yang, B. Luo

引用次数: 0

Relevance Based Transfer Learning for Reservoir Parameters Prediction with Logs 基于关联迁移学习的测井储层参数预测

82nd EAGE Annual Conference & Exhibition Pub Date : 1900-01-01 DOI: 10.3997/2214-4609.202112716

R. Shao, L. Xiao, G. Liao

{"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":null,"pages":null},"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}

引用次数: 0

Integration of mechanical stratigraphy with lithofacies in Goldwyer shale for selecting producible and hydraulic fracturing layers Goldwyer页岩力学地层学与岩相结合选择可压裂层和水力压裂层

82nd EAGE Annual Conference & Exhibition Pub Date : 1900-01-01 DOI: 10.3997/2214-4609.202112730

M. A. Iqbal, P. Mandal, R. Rezaee, J. Sarout, G. Smith

引用次数: 0

A Young’s modulus inversion and fracture prediction method and application for offshore wide azimuthal OBC data 杨氏模量反演裂缝预测方法及其在海上宽方位角OBC数据中的应用

82nd EAGE Annual Conference & Exhibition Pub Date : 1900-01-01 DOI: 10.3997/2214-4609.202112757

J. Wang, J. Zhang, G. Wu, Y. Wang, Q. Wang

引用次数: 0

82nd EAGE Annual Conference &amp; Exhibition最新文献

82nd EAGE Annual Conference & Exhibition最新文献