Seismic Reservoir Prediction Technologies for Re-exploration

2018 ◽  
pp. 417-457
Author(s):  
Xianzheng Zhao ◽  
Fengming Jin ◽  
Lihong Zhou ◽  
Quan Wang ◽  
Xiugang Pu
Keyword(s):  
Reservoir Prediction ◽  
Seismic Reservoir

Application of cloud transforms in seismic reservoir prediction

2013 ◽  
Author(s):  
Liu Leisong ◽  
Gao Jun ◽  
Dai Shuanghe ◽  
Yang Yu
Keyword(s):  
Reservoir Prediction ◽  
Seismic Reservoir

Rock physics based seismic reservoir prediction in the presence of thin coal beds

2017 ◽  
Author(s):  
Alexey Shubin ◽  
Dmitriy Klyazhnikov ◽  
Yuriy Varov ◽  
Valeriy Ryzhkov
Keyword(s):  
Rock Physics ◽  
Reservoir Prediction ◽  
Coal Beds ◽  
Seismic Reservoir

Application of Structural Properties of Seismic Data to Prediction of Hydrocarbon Distribution

2018 ◽  
Vol 10 (3) ◽  
pp. 41-52
Author(s):  
Zhou Wei ◽  
Guo Haimin ◽  
Yaoting Lin
Keyword(s):  
Structural Properties ◽  
Seismic Data ◽  
Oil And Gas ◽  
Reservoir Prediction ◽  
Dispersed Oil ◽  
Rock Formations ◽  
Seismic Reservoir ◽  
Oil Concentration ◽  
Hydrocarbon Distribution ◽  
Seismic Data Structure

This article describes how under the influence of traps and trap ranges in size, final moisture content in oil production and changes in the reservoir is very large. Due to this, thin and dispersed oil concentration, facies changes and oil complexes, and strong segmentation, results in poor comparability between wells and conventional methods of seismic reservoir prediction has been more difficult to meet the development needs of the block. Therefore, the introduction of methods of seismic data structure characteristics, with a method based on sequence structure of underground rock formations, rock and petroleum allows the prediction for oil and gas purposes. Through the application of seismic structural properties, the result has been verified in practice and achieved a good application effect.

The Research of Reservoir Earthquake Prediction Based on the Design of Horizontal Well of Thin Carbonate Reservoir of J2 Gas Reservoir in Lingyinsi Structure

2016 ◽  
Vol 13 (10) ◽  
pp. 7513-7518
Author(s):  
Sang Qin ◽  
Qing Ke Yu ◽  
Wu Chang Long ◽  
Yang Tong Shui
Keyword(s):  
Earthquake Prediction ◽  
Horizontal Well ◽  
Carbonate Reservoir ◽  
Reservoir Prediction ◽  
Velocity Inversion ◽  
Clastic Rocks ◽  
Natural Gamma ◽  
Seismic Reservoir ◽  
Reservoir Earthquake ◽  
Thin Reservoir

Compared to clastic rocks, the exploration and development of thin carbonate reservoir are 1more complex. Especially, the thin reservoir demands high resolution of seismic data. So the conventional methods are difficult to good exploration at the present time. According to the complexity of thin carbonate reservoir, we comprehensively analyze reservoir geology, logging and seismic response, combine natural gamma inversion, velocity inversion with porosity inversion for prediction of reservoir and obtain precise quantitative earthquake prediction. The analysis demonstrates the reliability of seismic reservoir prediction applied to design for horizontal well. On the basis of understanding the basic geological characteristics of the reservoir, this thesis takes the design for horizontal well of J21 for example, completes two sets of designs for horizontal wells group by combining prediction technology for reservoir seismic with geologic steering technique and greatly improve the drilling rate for thin reservoir.

Seismic reservoir prediction using Bayesian integration of rock physics and Markov random fields: A North Sea example

2002 ◽  
Vol 21 (3) ◽  
pp. 290-294 ◽  
Author(s):  
Jo Eidsvik ◽  
Henning Omre ◽  
Tapan Mukerji ◽  
Gary Mavko ◽  
Per Avseth ◽  
...  
Keyword(s):  
North Sea ◽  
Random Fields ◽  
Markov Random Fields ◽  
Rock Physics ◽  
Reservoir Prediction ◽  
Markov Random ◽  
Bayesian Integration ◽  
Seismic Reservoir

Seismic Reservoir Prediction in Lengjia-Leijia Area

2013 ◽  
Vol 318 ◽  
pp. 428-431
Author(s):  
Qi Zhou ◽  
Wen Long Ding
Keyword(s):  
Good Condition ◽  
Inversion Method ◽  
Reservoir Prediction ◽  
Reservoir Evaluation ◽  
Seismic Reservoir ◽  
Shahejie Formation ◽  
Detailed Interpretation ◽  
Deep Exploration ◽  
Oil Gas ◽  
Fourth Member

Through the deep exploration in Lengjia-Leijia area, four reservoirs were found: the lower sub-section of the third member of Shahejie formation, the fourth member of Shahejie formation, Mesozoic, and Archean. The fourth member of Shahejie formation and the layer below it had fewer drilling reach; its reservoir stratums are different. Seismic reservoir prediction has become the major means of oil-gas reservoir evaluation. The logging-constrained inversion method was applied in this study. A geologic model was established based on the detailed interpretation of seismic data; then, inversion and prediction were performed to describe and evaluate the distribution, thickness, and physical characteristics of the reservoirs. The results showed that the reservoir in the fourth member of Shahejie formation, Mesozoic, and Archean are well developed, and that oil-gas accumulation is in good condition. Therefore, the deep layer in this area is an important exploration direction. This study also provided the preliminary prediction that a favorable trap area exists.

scholarly journals Application of well-seismic reservoir prediction technology in oilfield

2021 ◽  
Vol 329 ◽  
pp. 01032
Author(s):  
Xiaona Zhang
Keyword(s):  
Spatial Configuration ◽  
Longitudinal Direction ◽  
Oil Fields ◽  
Fluvial Sediments ◽  
Reservoir Prediction ◽  
Sand Body ◽  
Seismic Reservoir ◽  
Single Well ◽  
Sedimentary Microfacies ◽  
Sand Bodies

This study mainly takes the thick oil layer in Lamadian Oilfield as an example. This oil layer is mainly developed in the area dominated by fluvial sediments, and the reservoir sand body space changes frequently. If we only rely on the traditional single well logging data, it is difficult to directly and effectively predict the changes of the whole sedimentary sand body, and the spatial configuration relationship between river boundary and other sedimentary microfacies can not be effectively predicted. In order to effectively improve the understanding of cross-well sand bodies, it is necessary to effectively combine well seismic with reservoir prediction technology, give full play to the advantage of high resolution of well seismic in the longitudinal direction, and predict its specific adaptability and application according to different situations, so as to better improve the prediction accuracy of reservoir sand bodies and provide important information data for the rational adjustment of cross-well encryption and the formulation of effective measures to tap potential. Based on this, this article deeply analyzes the application value of well-seismic combined reservoir prediction technology in oil fields.

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