Seismic Attribute Analysis - An Aid in Fracture Play Mapping

2007 ◽  
Author(s):  
Srinivasa Rao Narhari ◽  
Nikhil Banik ◽  
Sunil Kumar Singh ◽  
Talal Fahad Al-Adwani
Keyword(s):  
Seismic Attribute ◽  
Attribute Analysis

Predict Channel Sand Body Distribution Characteristics of South Eighth District Based on RMS Amplitude Attributes & Frequency Division

2013 ◽  
Vol 734-737 ◽  
pp. 404-407 ◽  
Author(s):  
Yu Shuang Hu ◽  
Si Miao Zhu
Keyword(s):  
Seismic Data ◽  
Physical Property ◽  
Sedimentary Facies ◽  
Distribution Area ◽  
Frequency Division ◽  
Root Mean Square Amplitude ◽  
Seismic Attribute ◽  
Body Distribution ◽  
Attribute Analysis ◽  
Sand Body

A big tendency in oil industry is underestimating the heterogeneity of the reservoir and overestimating the connectivity, which results in overly optimistic estimates of the capacity. With the development of seismic attributes, we could pick up hidden reservoir lithology and physical property information from the actual seismic data, strengthen seismic data application in actual work, to ensure the objectivity of the results. In this paper, the channel sand body distribution in south eighth district of oilfield Saertu is predicted through seismic data root-mean-square amplitude and frequency division to identify sand body boundaries, predict the distribution area channel sand body characteristics successfully, which consistent with the sedimentary facies distribution. The result proves that seismic attribute analysis has good practicability in channel sand body prediction and sedimentary facies description.

scholarly journals APPLICATION OF DIRECT HYDROCARBON INDICATORS FOR OIL AND GAS PROSPECTING IN THE DNIPRO-DONETS DEPRESSION

2021 ◽  
pp. 99-108
Author(s):  
Sergiy VYZHVA ◽  
Ihor SOLOVYOV ◽  
Ihor МYKHALEVYCH ◽  
Viktoriia KRUHLYK ◽  
Georgiy LISNY
Keyword(s):  
Acoustic Impedance ◽  
Oil And Gas ◽  
Practical Importance ◽  
Seismic Attributes ◽  
Limited Range ◽  
Seismic Attribute ◽  
Tectonic Model ◽  
Hydrocarbon Traps ◽  
Attribute Analysis ◽  
Volumetric Images

Based on the results of numerous seismic studies carried out in the areas and fields of the Dnipro-Donets depression, the strategy to identify hydrocarbon traps in this region has been developed taking into account modern requirements for prospecting and exploration of gas and oil fields. The studies are designed to determine the favorable zones of hydrocarbon accumulations based on the analysis of the structural-tectonic model. A necessary element for solving such a problem is to aaply direct indicators of hydrocarbons to predict traps of the structural, lithological or combined type. It was determined that an effective approach to identify hydrocarbon traps in the region is attribute analysis employing seismic attributes such as seismic envelope, acoustic impedance or relative acoustic impedance. In most cases of practical importance, the analysis of the distribution of the values of these attributes turned out to be sufficient for performing the geological tasks. It is given an example of extracting additional useful information on the spatial distribution of hydrocarbon traps from volumetric images obtained from seismograms of common sources with a limited range of ray angles inclinations. To analyze the distributions of seismic attribute values, it is recommended to use the Geobody technology for detecting geological bodies as the most effective when using volumetric seismic data. The distributions of various properties of rocks, including zones of increased porosity or zones of presence of hydrocarbons are determined depending on the types of seismic attributes used in the analysis,. The use of several seismic attributes makes it possible to identify geological bodies saturated with hydrocarbons with increased porosity and the like. The paper provides examples of hydrocarbon traps recognition in the areas and fields of the Dnipro-Donets depression practically proved by wells. A generalization on the distribution of promising hydrocarbon areas on the Northern flank of the Dnipro-Donets depression and the relationship of this distribution with the identified structural elements of the geological subsoil is made. 

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