... subdiscipline asia government reservoir characterization indication waveform classification coefficient matrix inversion compression-sensing dividedfrequency waveform indication equation geologist china government machine learning seismic waveform international exploration geophysicist american...

... data upstream oil & gas euclidean distance characteristic reservoir characterization applied geoscience som algorithm classification method artificial intelligence criterion waveform classification correntropy neuron amplitude exploration geophysicist 10 texture classification...

... scholars have proposed wave clustering methods. Among them, for waveform classification, the existing method usually uses equal-thickness time windows to select the target layer for waveform clustering analysis. For areas where the thickness of the reservoir varies greatly in vertical and horizontal...

... ABSTRACT Waveform classification is a useful method in seismic facies analysis and has been successfully applied to oil and gas reservoir prediction. In general, the problem can be solved by machine learning methods. However, the spatial continuity and similarity of adjacent traces...

... ABSTRACT Seismic waveform classification is an important technique for seismic facies analysis. The most existing methods use a fixed time window to extract seismic data along the interpretation horizon and then classify them. However, when the thickness of target layer has a large change...

... that have similar expressions, and supervised classification, where the computer attempts to mimic the skills of an experienced interpreter. In this study we compare several of the more well established machine learning techniques: waveform classification, principal component analysis (PCA), k-means...

... investigate a waveform classification and FB-picking method based on fully convolutional neural networks (FCNs) and transfer learning (TL). We consider FB-picking as a binary image segmentation problem of labelling a 2D seismic image with ones on signal and zeros on noise. Through FCNs, we achieve a fast...

... the deeper targets. In view of this limitation, an integrated approach had been adopted in relating the seismic data with hydrocarbon indications in wells and subsequent correlation through a combination of seismic attributes as well as waveform classification. A suitable geologic model has been postulated...

... ABSTRACT Conventional waveform clustering may be accomplished using single attribute and constant time window. To meet the demand of continental stratigraphic analysis, we present a method for waveform classification using multiple attributes and variable window. We first use PCA for dimension...

...References References Andersen , E. , and J. Boyd , 2004 , Seismic waveform classification: Techniques and benefits : CSEG Recorder , 29 . Chopra , S. , and K. J. Marfurt , 2005 , Seismic attributes—A historical perspective : Geophysics , 70...

... using a supervised artificial neural network (ANN) to classify and identify the seismic facies. Important lateral variations in reflector continuity is blended into the waveform classification map in order to improve the facies recognition. The predicted distribution of facies and lithology...

... ABSTRACT Waveform classification techniques is a powerful tool for seismic facies analysis by describing the heterogeneity and compartments within a reservoir. The interpretation of horizon is critical to the process of waveform classification. The error of horizon, which is inevitable...

... with hydrocarbon indications in wells and subsequent correlation through a combination of seismic attributes as well as waveform classification. A suitable geologic model has been postulated with seismic and well analysis which has resulted in identifying a target area for exploration. The exploratory well drilled...

... two applications of this technique one for waveform classification and the other for the classification of well data. In both these applications PSVM classification results showed strong agreement with structural and stratigraphic interpretation results. mangasarian seg denver 2014...

... anhydrite neural network classification amplitude artificial intelligence hith formation mutriba area seg denver 2014 kuwait thin carbonate tight reservoir reservoir characterization thickness magnitude waveform classification upstream oil & gas carbonate stringer impedance machine...

... spectral inversion to estimate thin bed reflectivity, followed by relative acoustic impedance and unconstrained waveform classification to map the reservoir heterogeneity. This is followed by generation of coherence and curvature attributes to detect minor faults and fractures. bandwidth curvature...

... that involve well log data as well as seismic data. shale gas complex reservoir thin-bed reflectivity inversion natural fracture horizon slice brittleness waveform classification shale formation permeability reservoir inversion relative acoustic impedance seismic data toc workflow...

... footprint som glcm upstream oil & gas seg seg denver 2010 waveform classification prototype vector machine learning classification red-fork formation anadarko basin projection depositional stage well control self-organizing map interpretation workflow Applying self-organizing maps...

... Summary Prediction and delineation of Late Jurassic Hanifa regional reservoir fairways in the Eastern Province of the Kingdom of Saudi Arabia has been achieved by integrating 3D seismic, cores, and well log data. Seismic mapping, attributes, inversion, waveform classification, petrophysical...

... of these zones is critical. In our experience, neural network based waveform classification has proven to be a successful tool to identify these zones. Qualitative analysis of seismic facies derived from the classification is a common practice. However, we demonstrate in this paper that the quantitative...