نتایج جستجو برای: seismic facies

تعداد نتایج: 42007  

2011
Mei Han Yong Zhao Gaoming Li Albert C. Reynolds

Identification of the geological facies and their distribution from seismic and other available geological information is important during the early stage of reservoir development (e.g. decision on initial well locations). Traditionally, this is done by manually inspecting the signatures of the seismic attribute maps, which is very time-consuming. This paper proposes an application of the Expec...

2008
Sebastian Ng Pål Dahle Ragnar Hauge

We have done a geostatistical inversion of seismic data to facies probabilities. As a first step, we invert the seismic data for elastic parameters using the Bayesian AVA inversion method of Buland et. al. (2003). Next, we use an analysis of the uncertainty in the posterior distribution to filter the elastic parameters given in well logs. By comparing these filtered well logs with facies logs, ...

Journal: :CoRR 2017
Feng Qian Miao Yin Ming-Jun Su Yaojun Wang Guangmin Hu

Prestack seismic data carries much useful information that can help us find more complex atypical reservoirs. Therefore, we are increasingly inclined to use prestack seismic data for seismic facies recognition. However, due to the inclusion of excessive redundancy, effective feature extraction from prestack seismic data becomes critical. In this paper, we consider seismic facies recognition bas...

Abdorrahim Javaherian Mojtaba Mohammadoo Khorasani Shabnam Shahbazi

Geological facies interpretation is essential for reservoir studying. The method of classification and identification seismic traces is a powerful approach for geological facies classification and distinction. Use of neural networks as classifiers is increasing in different sciences like seismic. They are computer efficient and ideal for patterns identification. They can simply learn new algori...

Journal: :نشریه دانشکده فنی 0
شبنم شهبازی دانشگاه صنعتی امیرکبیر عبدالرحیم جواهریان موسسه ژئوفیزیک مجتبی محمدو خراسانی شرکت ملی نفت

geological facies interpretation is essential for reservoir studying. the method of classification and identification seismic traces is a powerful approach for geological facies classification and distinction. use of neural networks as classifiers is increasing in different sciences like seismic. they are computer efficient and ideal for patterns identification. they can simply learn new algori...

2001
S. K. Addy

A new technology of classifying a seismic interval parallel to a horizon in a 3D volume based on the shape of the wiggle traces and its geologic use will be presented here. Since the seismic traces contain all relevant information, such as, reflection patterns, phase, frequency, amplitude etc., the trace shape is a fundamental property of the seismic data. A map showing the distribution of simi...

2011
Dario Grana Jack Dvorkin Tapan Mukerji

The main objective of this work is to present a new methodology for seismic reservoir characterization that provides fine-scaled reservoir models of facies and reservoir properties, such as porosity, net-to-gross, and, possibly, fluid saturation. The proposed iterative methodology is based on sequential simulations of discrete variables, namely sequential indicator simulation, and a stochastic ...

2001
Jef Caers Tapan Mukerji

Turbidite systems are complex heterogeneous siliciclastic deposits calling for a new approach to geophysical and geostatistical reservoir characterization. The aim of this paper is to demonstrate the integration of seismic amplitude and rock physics data into realistic geological scenarios using a novel geostatistical approach. Avseth (2000, 2001 with others) presented an integrated rock physic...

Journal: Geopersia 2018

Pattern recognition on seismic data is a useful technique for generating seismic facies maps that capture changes in the geological depositional setting. Seismic facies analysis can be performed using the supervised and unsupervised pattern recognition methods. Each of these methods has its own advantages and disadvantages. In this paper, we compared and evaluated the capability of two unsuperv...

2017
Jeremy Gallop

Identifying facies for classification for a seismic inversion project is an important step where one balances computational effort and the quality of the results. We propose a new measure to quantify the suitability of a given facies partition based on information theory. The results depend on a user-selected cutoff, and we propose a reasonable value for this constant. We also show the analysis...

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