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Seismic Attributes for Prospect Identification and Reservoir Characterization

2007 Science
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Release : 2007
Genre : Science
Kind : eBook
Book Rating : 417/5 ( reviews)

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Book Synopsis Seismic Attributes for Prospect Identification and Reservoir Characterization by : Satinder Chopra

Download or read book Seismic Attributes for Prospect Identification and Reservoir Characterization written by Satinder Chopra. This book was released on 2007. Available in PDF, EPUB and Kindle. Book excerpt: Introducing the physical basis, mathematical implementation, and geologic expression of modern volumetric attributes including coherence, dip/azimuth, curvature, amplitude gradients, seismic textures, and spectral decomposition, the authors demonstrate the importance of effective colour display and sensitivity to seismic acquisition and processing.

3D Seismic Attributes Analysis in Reservoir Characterization

2016
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Release : 2016
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Book Synopsis 3D Seismic Attributes Analysis in Reservoir Characterization by : Andrew B. Vohs

Download or read book 3D Seismic Attributes Analysis in Reservoir Characterization written by Andrew B. Vohs. This book was released on 2016. Available in PDF, EPUB and Kindle. Book excerpt: Seismic reservoir characterization and prospect evaluation based 3D seismic attributes analysis in Kansas has been successful in contributing to the tasks of building static and dynamic reservoir models and in identifying commercial hydrocarbon prospects. In some areas, reservoir heterogeneities introduce challenges, resulting in some wells with poor economics. Analysis of seismic attributes gives insight into hydrocarbon presence, fluid movement (in time lapse mode), porosity, and other factors used in evaluating reservoir potential. This study evaluates a producing lease using seismic attributes analysis of an area covered by a 2010 3D seismic survey in the Morrison Northeast field and Morrison field of Clark County, KS. The target horizon is the Viola Limestone, which continues to produce from seven of twelve wells completed within the survey area. In order to understand reservoir heterogeneities, hydrocarbon entrapment settings and the implications for future development plans, a seismic attributes extraction and analysis, guided with geophysical well-logs, was conducted with emphasis on instantaneous attributes and amplitude anomalies. Investigations into tuning effects were conducted in light of amplitude anomalies to gain insight into what seismic results led to the completion of the twelve wells in the area drilled based on the seismic survey results. Further analysis was conducted to determine if the unsuccessful wells completed could have been avoided. Finally the study attempts to present a set of 3D seismic attributes associated with the successful wells, which will assist in placing new wells in other locations within the two fields, as well as promote a consistent understanding of entrapment controls in this field.

3D Seismic Attribute Analysis and Machine Learning for Reservoir Characterization in Taranaki Basin, New Zealand

2018
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Release : 2018
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Book Synopsis 3D Seismic Attribute Analysis and Machine Learning for Reservoir Characterization in Taranaki Basin, New Zealand by : Aamer Ali AlHakeem

Download or read book 3D Seismic Attribute Analysis and Machine Learning for Reservoir Characterization in Taranaki Basin, New Zealand written by Aamer Ali AlHakeem. This book was released on 2018. Available in PDF, EPUB and Kindle. Book excerpt: "The Kapuni group within the Taranaki Basin in New Zealand is a potential petroleum reservoir. The objective of the study includes building a sequential approach to identify different geological features and facies sequences within the strata, through visualizing the targeted formations by interpreting and correlating the regional geological data, 3D seismic, and well data by following a sequential workflow. First, seismic interpretation is performed targeting the Kapuni group formations, mainly, the Mangahewa C-sand and Kaimiro D-sand. Synthetic seismograms and well ties are conducted for structural maps, horizon slices, isopach, and velocity maps. Well log and morphological analyses are performed for formation sequence and petrophysics identification. Attribute analyses including RMS, dip, azimuth, and eigenstructure coherence are implemented to identify discontinuities, unconformities, lithology, and bright spots. Algorithmic analyses are conducted using Python programming to generate and overlay the attributes which are displayed in 3D view. Integrating all of the attributes in a single 3D view significantly strengthens the summation of the outputs and enhances seismic interpretation. The attribute measurements are utilized to characterize the subsurface structure and depositional system such as fluvial dominated channels, point bars, and nearshore sandstone. The study follows a consecutive workflow that leads to several attribute maps for identifying potential prospects"--Abstract, page iv.

Stratigraphic Reservoir Characterization for Petroleum Geologists, Geophysicists, and Engineers

2013-11-21 Technology & Engineering
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Release : 2013-11-21
Genre : Technology & Engineering
Kind : eBook
Book Rating : 704/5 ( reviews)

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Book Synopsis Stratigraphic Reservoir Characterization for Petroleum Geologists, Geophysicists, and Engineers by : Roger M. Slatt

Download or read book Stratigraphic Reservoir Characterization for Petroleum Geologists, Geophysicists, and Engineers written by Roger M. Slatt. This book was released on 2013-11-21. Available in PDF, EPUB and Kindle. Book excerpt: There are many tools and techniques for characterizing oil and gas reservoirs. Seismic-reflection techniques include conventional 2D and 3D seismic, 4D time-lapse seismic, multicomponent seismic, crosswell seismic, seismic inversion, and seismic attribute analysis, all designed to enhance stratigraphy/structure detection, resolution, and characterization. These techniques are constantly being improved. Drilling and coring a well provides the “ground truth” for seismic interpretation. Rock formations are directly sampled by cuttings and by core and indirectly characterized with a variety of conventional and specialized well logs. To maximize characterization and optimize production, many of these tools as possible should be employed. It is often less expensive to utilize a wide variety of tools that directly image or measure reservoir properties at different scales than to drill one or two dry holes.

3D Seismic Attributes Analysis and Inversions for Prospect Evaluation and Characterization of Cherokee Sandstone Reservoir in the Wierman Field, Ness County, Kansas

2017
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Release : 2017
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Book Synopsis 3D Seismic Attributes Analysis and Inversions for Prospect Evaluation and Characterization of Cherokee Sandstone Reservoir in the Wierman Field, Ness County, Kansas by : Bouharket Boumaaza

Download or read book 3D Seismic Attributes Analysis and Inversions for Prospect Evaluation and Characterization of Cherokee Sandstone Reservoir in the Wierman Field, Ness County, Kansas written by Bouharket Boumaaza. This book was released on 2017. Available in PDF, EPUB and Kindle. Book excerpt: This work focuses on the use of advanced seismically driven technologies to estimate the distribution of key reservoir properties which mainly includes porosity and hydrocarbon reservoir pay. These reservoir properties were estimated by using a multitude of seismic attributes derived from post-stack high resolution inversions, spectral imaging and volumetric curvature. A pay model of the reservoir in the Wierman field in Ness County, Kansas is proposed. The proposed geological model is validated based on comparison with findings of one blind well. The model will be useful in determining future drilling prospects, which should improve the drilling success over previous efforts, which resulted in only few of the 14 wells in the area being productive. The rock properties that were modeled were porosity and Gamma ray. Water saturation and permeability were considered, but the data needed were not available. Sequential geological modeling approach uses multiple seismic attributes as a building block to estimate in a sequential manner dependent petrophysical properties such as gamma ray, and porosity. The sequential modelling first determines the reservoir property that has the ability to be the primary property controlling most of the other subsequent reservoir properties. In this study, the gamma ray was chosen as the primary reservoir property. Hence, the first geologic model built using neural networks was a volume of gamma ray constrained by all the available seismic attributes. The geological modeling included post-stack seismic data and the five wells with available well logs. The post-stack seismic data was enhanced by spectral whitening to gain as much resolution as possible. Volumetric curvature was then calculated to determine where major faults were located. Several inversions for acoustic impedance were then applied to the post-stack seismic data to gain as much information as possible about the acoustic impedance. Spectral attributes were also extracted from the post-stack seismic data. After the most appropriate gamma ray and porosity models were chosen, pay zone maps were constructed, which were based on the overlap of a certain range of gamma ray values with a certain range of porosity values. These pay zone maps coupled with the porosity and gamma ray models explain the performance of previously drilled wells.

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