Integrated 3D seismic inversion and volume visualization for reservoir characterization and reserve estimation

2000 ◽  
Author(s):  
Jeff G.‐S. Pan
Keyword(s):  
Reservoir Characterization ◽  
Volume Visualization ◽  
Seismic Inversion ◽  
3D Seismic ◽  
Reserve Estimation

Multiattribute rotation scheme: A tool for reservoir property prediction from seismic inversion attributes

2015 ◽  
Vol 3 (4) ◽  
pp. SAE9-SAE18 ◽  
Author(s):  
Pedro Alvarez ◽  
Francisco Bolívar ◽  
Mario Di Luca ◽  
Trino Salinas
Keyword(s):  
Reservoir Characterization ◽  
Barents Sea ◽  
Water Saturation ◽  
Total Porosity ◽  
Seismic Inversion ◽  
Dimensional Euclidean Space ◽  
Petrophysical Properties ◽  
Reserve Estimation ◽  
Reservoir Property ◽  
Rotation Scheme

The multiattribute rotation scheme (MARS) is a methodology that uses a numerical solution to estimate a transform to predict petrophysical properties from elastic attributes. This is achieved by estimating a new attribute in the direction of maximum change of a target property in an [Formula: see text]-dimensional Euclidean space formed by an [Formula: see text] number of attributes and subsequent scaling of this attribute to the target unit properties. We have computed the transform from well-log-derived elastic attributes and petrophysical properties, and we have posteriorly applied it to seismically derived elastic attributes. Such transforms can be used to estimate reservoir property volumes for reservoir characterization and delineation in exploration and production settings and to estimate secondary variables in geostatistical workflows for static model generation and reserve estimation. To illustrate the methodology, we applied MARS to estimate a transform to predict the water saturation and total porosity from elastic attributes in a well located in the Barents Sea as well as to estimate a water-saturation volume in a mud-rich turbidite gas reservoir located onshore Colombia.

scholarly journals Porosity estimation in the Fort Worth Basin constrained by 3D seismic attributes integrated in a sequential Bayesian simulation framework

Geophysics ◽  
2017 ◽  
Vol 82 (4) ◽  
pp. M67-M80 ◽  
Author(s):  
Martin Blouin ◽  
Mickaele Le Ravalec ◽  
Erwan Gloaguen ◽  
Mathilde Adelinet
Keyword(s):  
Oil And Gas ◽  
Reservoir Characterization ◽  
Geophysical Methods ◽  
Seismic Attributes ◽  
Seismic Inversion ◽  
Fort Worth ◽  
3D Seismic ◽  
Reservoir Properties ◽  
Fort Worth Basin ◽  
Porosity Estimation

The accurate inference of reservoir properties such as porosity and permeability is crucial in reservoir characterization for oil and gas exploration and production as well as for other geologic applications. In most cases, direct measurements of those properties are done in wells that provide high vertical resolution but limited lateral coverage. To fill this gap, geophysical methods can often offer data with dense 3D coverage that can serve as proxy for the variable of interest. All the information available can then be integrated using multivariate geostatistical methods to provide stochastic or deterministic estimate of the reservoir properties. Our objective is to generate multiple scenarios of porosity at different scales, considering four formations of the Fort Worth Basin altogether and then restricting the process to the Marble Falls limestones. Under the hypothesis that a statistical relation between 3D seismic attributes and porosity can be inferred from well logs, a Bayesian sequential simulation (BSS) framework proved to be an efficient approach to infer reservoir porosity from an acoustic impedance cube. However, previous BBS approaches only took two variables upscaled at the resolution of the seismic data, which is not suitable for thin-bed reservoirs. We have developed three modified BSS algorithms that better adapt the BSS approach for unconventional reservoir petrophysical properties estimation from deterministic prestack seismic inversion. A methodology that includes a stochastic downscaling procedure is built and one that integrates two secondary downscaled constraints to the porosity estimation process. Results suggest that when working at resolution higher than surface seismic, it is better to execute the workflow for each geologic formation separately.

Application of geostatistical seismic inversion in reservoir characterization of Sapphire gas field, offshore Nile Delta, Egypt

2019 ◽  
Vol 38 (6) ◽  
pp. 474-479
Author(s):  
Mohamed G. El-Behiry ◽  
Said M. Dahroug ◽  
Mohamed Elattar
Keyword(s):  
Reservoir Characterization ◽  
Nile Delta ◽  
Seismic Inversion ◽  
Reservoir Modeling ◽  
Connectivity Analysis ◽  
Gas Field ◽  
Geostatistical Inversion ◽  
Well Data ◽  
Reservoir Connectivity ◽  
Inversion Techniques

Seismic reservoir characterization becomes challenging when reservoir thickness goes beyond the limits of seismic resolution. Geostatistical inversion techniques are being considered to overcome the resolution limitations of conventional inversion methods and to provide an intuitive understanding of subsurface uncertainty. Geostatistical inversion was applied on a highly compartmentalized area of Sapphire gas field, offshore Nile Delta, Egypt, with the aim of understanding the distribution of thin sands and their impact on reservoir connectivity. The integration of high-resolution well data with seismic partial-angle-stack volumes into geostatistical inversion has resulted in multiple elastic property realizations at the desired resolution. The multitude of inverted elastic properties are analyzed to improve reservoir characterization and reflect the inversion nonuniqueness. These property realizations are then classified into facies probability cubes and ranked based on pay sand volumes to quantify the volumetric uncertainty in static reservoir modeling. Stochastic connectivity analysis was also applied on facies models to assess the possible connected volumes. Sand connectivity analysis showed that the connected pay sand volume derived from the posterior mean of property realizations, which is analogous to deterministic inversion, is much smaller than the volumes generated by any high-frequency realization. This observation supports the role of thin interbed reservoirs in facilitating connectivity between the main sand units.

See the Unseen through Target-Oriented Dip-Steered Seismic Resolution

2021 ◽  
Author(s):  
Muhammad Sajid ◽  
Ahmad Riza Ghazali
Keyword(s):  
Reservoir Characterization ◽  
Resolution Enhancement ◽  
Dominant Frequency ◽  
Seismic Inversion ◽  
Seismic Resolution ◽  
Geological Features ◽  
Spectral Enhancement ◽  
Enhancement Method ◽  
Layer Velocity ◽  
Seismic Volumes

Abstract Seismic resolution plays an important role not only in interpretation and reservoir characterization but also in seismic inversion and seismic attributes analysis. The resolution depends on several factors, including seismic frequency bandwidth, dominant frequency, and layer velocity. This paper presents a spectral resolution enhancement approach that is based on Non-stationary Differential Resolution (NSDR) that honors the local structural dip, better preserves amplitude and improves target-oriented seismic interpretation. The proposed technology is applied to both 2D and 3D seismic volumes and findings are compared with the oil industry common spectral enhancement algorithms. We demonstrate the target-oriented dip steering spectral enhancement method on two 3D field datasets and compare the resulting outcome with those obtained by conventional techniques. It is found that thinly layered subsurface geological features with steeply dipping beds are better defined, with artifacts from the conflicting dips removed.

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