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, ...

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...

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...

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...

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...

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...

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...

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...

Over the years, there has been an ongoing struggle to relate well-log and seismic data due to the inherent bandwidth limitation of seismic data, the problem of seismic amplitudes, and the apparent inability to delineate and characterize the transitions that can be linked to and held responsible for major reflection events and their signatures. By shifting focus to a scale invariant sharpness ch...

Relating sedimentary records to seismic data is a major challenge. By shifting focus to a scale-invariant sharpness characterization for the reflectors, we develop an attribute that can capture and categorize the main reflector features, without being sensitive to amplitudes. Sharpness is defined by a scale exponent, which expresses singularity order and determines the reflection signature/wave...