The Study of Well Logging Sedimentary Microfacies in Tengge’er Formation Baiyinchagan Depression

2017 ◽  
pp. 71-79
Author(s):  
Xinhu Li ◽  
Qiuling Wang ◽  
Wenhui Ma
Keyword(s):  
Well Logging ◽  
Sedimentary Microfacies

Delta Front Depositional System Study Based on Seismic Attributes and Well Logging Facies

2012 ◽  
Vol 170-173 ◽  
pp. 1285-1289 ◽  
Author(s):  
Xu Tao Li ◽  
Chang Song Lin
Keyword(s):  
River Mouth ◽  
Well Logging ◽  
Seismic Attributes ◽  
Delta Front ◽  
Seismic Attribute ◽  
The North ◽  
Depositional System ◽  
Sedimentary Microfacies ◽  
Mouth Bars ◽  
Bottom To Top

Along with analysis of logging facies characteristics of drilled wells, isometric strata slicing technique for seismic attribute is applied to interpret the distribution of the depositional systems in the study area. It is understood that Nenjiang3 Formation in Xinbei area of Xinli field consists of water regressive and sand progressive delta front depositional system from bottom to top. Combined with analogue analysis of well logging facies and planar seismic attributes, it is learned that sediments generally came from the north area, and main sedimentary microfacies include underwater distributary channels, river mouth bars, sheet sands body and interdistributary bays of delta front. With isometric slicing for the extraction of seismic attributes and logging operation, the distribution rules for sedimentary systems could analyzed, thereby providing a feasible method that could be referenced by the study on sedimentary system distribution of other areas.

Study on Artificial Neural Networks to Identify Sedimentary Microfacies

2014 ◽  
Vol 912-914 ◽  
pp. 1395-1398
Author(s):  
Wei Fu Liu ◽  
Shuang Long Liu ◽  
Li Xin Sun
Keyword(s):  
Neural Network ◽  
Artificial Neural Network ◽  
Ordos Basin ◽  
Well Logging ◽  
Effective Parameters ◽  
Geological Interpretation ◽  
Artificial Neural ◽  
Sedimentary Microfacies ◽  
Local Geology ◽  
Network Pattern

Based on a number of stratigraphic sedimentary information included in log data, application of the Artificial Neural Network to identify sedimentary microfacies from well logging data can complete the series auto-interpreting. The application can improve the auto-interpreting accuracy and make us get more satisfied results. Ten parameters from the well logging curves are selected for to describing their shape characteristics when the deposition patterns of 8 in gas-bearing formation of Upper Paleozoic group, Ordos basin are studied. Effective parameters were selected on the basis of cores, and based on artificial neural network pattern recognition technique; the sedimentary microfacies of well cross section were auto-interpreted. About 300 wells and the results were interpreted by using the software. The software will be fit for the researchers who have the experiences of geological interpretation and some backgrounds of local geology.

Sedimentary Microfacies Study of Putaohua Oil Layer in the East of Pubei Oilfield

2014 ◽  
Vol 962-965 ◽  
pp. 642-645
Author(s):  
Ze Han Hao ◽  
Yun Feng Zhang
Keyword(s):  
Well Logging ◽  
Oil Field ◽  
Fault Segmentation ◽  
Stratigraphic Framework ◽  
Development Area ◽  
Sedimentary Microfacies ◽  
Sand Sheet ◽  
Channel Edge ◽  
Distributary Channel ◽  
Exploration And Development

The fault segmentation of blank area in the east of Pubei Oilfield is strong, and the distribution of oil and water is complex. In view of this kind of situation, we did sedimentary microfacies research in study area. First, we established isochronous stratigraphic framework of the east of Putaohua oil layer by core and logging data ,we also established six well logging facies models, including main underwater distributary channel,underwater distributary channel,edge of underwater distributary channel,main sand sheet,sand sheet and bay mud between distributary channels;Secondly, we described the sedimentary microfacies of development area, summarized the evolution of sand and sedimentary microfacies characteristics of Putaohua oil layer; Finally, on the basis of the above work, we drew the sedimentary microfacies of study area. The study provides geological basis for the next step of exploration and development in oil field.

Applications of cross section data for nuclear geochemical well logging

1986 ◽  
Vol 94 (1-4) ◽  
pp. 49-52 ◽  
Author(s):  
R. C. Hertzog ◽  
P. D. Soran ◽  
J. S. Schweitzer
Keyword(s):  
Cross Section ◽  
Well Logging ◽  
Cross Section Data ◽  
Section Data ◽  
Geochemical Well Logging

Study on Sedimentary Characteristics of Zhang Jia Po Group, Gushi Hollow of Weihe Basin

2013 ◽  
Vol 772 ◽  
pp. 844-848
Author(s):  
Lin Zhang ◽  
Jian Chao Liu ◽  
Xing Yun Wang ◽  
Jian Feng Bai
Keyword(s):  
Shallow Lake ◽  
Facies Analysis ◽  
Sedimentary Facies ◽  
Sedimentary Structure ◽  
Deep Lake ◽  
Sedimentary Characteristics ◽  
Rock Types ◽  
Single Well ◽  
Weihe Basin ◽  
Sedimentary Microfacies

Through the paleontology, lithology combination data,For Weihe basin Gushi hollow Tertiary the Zhangjiapo group unified hierarchical total divided into seven sections. According to coring, logging data to study the rock types and sedimentary structure,Summed up the logging of various sedimentary microfacies facies, clear in the study area is a shallow lake - a deeper lake - deep lake - deeper lake - shallow lake cyclic sedimentation.For single well facies analysis of typical wells in the region, the establishment of even well profile, determine the small layer of sedimentary facies the planar distribution concluded sedimentary facies model.

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