Seismic screening of rock stiffness and fluid softening using rock-physics attributes

2015 ◽  
Vol 3 (4) ◽  
pp. SAE85-SAE93 ◽  
Author(s):  
Per Avseth ◽  
Tor Veggeland
Keyword(s):  
Rock Physics ◽  
Seismic Inversion ◽  
Well Log ◽  
Reservoir Properties ◽  
Empirical Relationships ◽  
Norwegian Sea ◽  
Reservoir Rocks ◽  
Fluid Saturation ◽  
Reservoir Sandstones ◽  
Elastic Impedance

We have developed a methodology to create easy-to-implement rock-physics attributes that can be used to screen for reservoir sandstones and hydrocarbon pore fill from seismic inversion data. Most seismic attributes are based on the empirical relationships between reservoir properties and seismic observables. We have honored the physical properties of the rocks by defining attributes that complied with calibrated rock-physics models. These attributes included the fluid saturation sensitive curved pseudo-elastic impedance (CPEI) and the rock stiffness/lithology attribute pseudo-elastic impedance for lithology (PEIL). We found that the CPEI attribute correlated nicely with saturation and resistivity, whereas the PEIL attribute in practice was a scaled version of the shear modulus and correlated nicely with porosity. We determined the use of these attributes on well log and seismic inversion data from the Norwegian Sea, and we successfully screened out reservoir rocks filled with either water or hydrocarbons.

scholarly journals Integrated Well Data And 3D Seismic Inversion Study For Reservoir Delineation And Description

2020 ◽  
Vol 70 (1) ◽  
pp. 209-220
Author(s):  
Qazi Sohail Imran ◽  
◽  
Numair Ahmad Siddiqui ◽  
Abdul Halim Abdul Latif ◽  
Yasir Bashir ◽  
...  
Keyword(s):  
Reservoir Characterization ◽  
Rock Physics ◽  
Seismic Inversion ◽  
Depositional Environments ◽  
Well Log ◽  
Reservoir Properties ◽  
Rock Physics Modeling ◽  
Physics Modeling ◽  
And Performance ◽  
Well Log Analysis

Offshore petroleum systems are often very complex and subtle because of a variety of depositional environments. Characterizing a reservoir based on conventional seismic and well-log stratigraphic analysis in intricate settings often leads to uncertainties. Drilling risks, as well as associated subsurface uncertainties can be minimized by accurate reservoir delineation. Moreover, a forecast can also be made about production and performance of a reservoir. This study is aimed to design a workflow in reservoir characterization by integrating seismic inversion, petrophysics and rock physics tools. Firstly, to define litho facies, rock physics modeling was carried out through well log analysis separately for each facies. Next, the available subsurface information is incorporated in a Bayesian engine which outputs several simulations of elastic reservoir properties, as well as their probabilities that were used for post-inversion analysis. Vast areal coverage of seismic and sparse vertical well log data was integrated by geostatistical inversion to produce acoustic impedance realizations of high-resolution. Porosity models were built later using the 3D impedance model. Lastly, reservoir bodies were identified and cross plot analysis discriminated the lithology and fluid within the bodies successfully.

Seismic data conditioning and orthotropic rock-physics-based inversion of wide-azimuth P-wave seismic data for fracture and total organic carbon characterization in a north Kuwait unconventional reservoir

Geophysics ◽  
2018 ◽  
Vol 83 (4) ◽  
pp. B229-B240 ◽  
Author(s):  
Rajive Kumar ◽  
Prashant Bansal ◽  
Bader S. Al-Mal ◽  
Sagnik Dasgupta ◽  
Colin Sayers ◽  
...  
Keyword(s):  
Organic Carbon ◽  
Total Organic Carbon ◽  
Seismic Data ◽  
Rock Physics ◽  
Seismic Inversion ◽  
P Wave ◽  
Natural Fracture ◽  
Reservoir Properties ◽  
Fluid Saturation ◽  
Fracture Intensity

Optimization of production from unconventional reservoirs requires estimates of reservoir properties such as porosity, total organic carbon (TOC) content, clay content, fluid saturation, and fracture intensity. The porosity and TOC content help to determine reservoir quality, and the natural fracture intensity provides information important for the completion strategy. Because shale reservoirs display intrinsic anisotropy due to layering and the partial alignment of clay minerals and kerogen with the bedding plane, the minimum acceptable representation of the anisotropy of naturally fractured shale-gas reservoirs is orthotropy, in which a set of vertical compliant fractures is embedded in a vertical transverse isotropic (VTI) background medium. Full-azimuth seismic data are required to characterize such reservoirs and to invert for the anisotropic elastic properties. Orthotropic inversion uses azimuthally sectored seismic data stacked according to the incident angle. Even for high-fold acquisition, this azimuth/angle grouping can result in low-fold angle stacks. Orthotropic amplitude-variation-with-offset-and-azimuth (AVOAz) inversion requires seismic preconditioning techniques that ensure proper primary amplitude preservation, noise attenuation, and data alignment, and a workflow implemented for the construction of an orthotropic rock-physics model. This model integrates well and core data to estimate reservoir properties using the results of the AVOAz inversion. The seismic inversion results include the P- and S-impedance and parameters quantifying the azimuthal anisotropy. The rock model assumes a VTI kerogen-rich layer, containing aligned vertical fractures, and it uses prestack orthotropic AVOAz inversion results to predict porosity, TOC, and fracture intensity.

Estimation of porosity and fluid saturation in carbonates from rock-physics templates based on seismic Q

Geophysics ◽  
2019 ◽  
Vol 84 (6) ◽  
pp. M25-M36 ◽  
Author(s):  
Mengqiang Pang ◽  
Jing Ba ◽  
José M. Carcione ◽  
Stefano Picotti ◽  
Jian Zhou ◽  
...  
Keyword(s):  
Seismic Data ◽  
Rock Physics ◽  
Clay Content ◽  
Spectral Ratio ◽  
Gas Production ◽  
Ratio Method ◽  
Well Log ◽  
Reservoir Properties ◽  
Seismic Properties ◽  
Fluid Saturation

Rock-physics templates establish a link between seismic properties (e.g., velocity, density, impedance, and attenuation) and reservoir properties such as porosity, fluid saturation, permeability, and clay content. We focus on templates based on attenuation (seismic [Formula: see text] or quality factor), which are highly affected by those properties, and we consider carbonate reservoirs that constitute 60% of the world oil reserves and a potential for additional gas reserves. The seismic properties are described with mesoscopic-loss models, such as the White model of patchy saturation and the double double-porosity model, which include frame and fluid heterogeneities. We have performed ultrasonic experiments, and we estimate the attenuation of the samples and the reservoir by using the spectral ratio method and the improved frequency-shift method. Then, multiscale calibrations of the templates are performed by using laboratory, well log, and seismic data. On this basis, reservoir porosity and fluid saturation are quantitatively evaluated. We first apply the templates to ultrasonic data of limestone using the White model. Then, we consider seismic data of a carbonate gas reservoir of MX work area in the Sichuan Basin, southwest China. A survey line in the area is selected to detect the reservoir by using the templates. The results indicate that the estimated porosity and saturation are consistent with well-log data and actual gas production results. The methodology indicates that the microstructural characteristics of a high-quality reservoir can effectively be predicted using seismic [Formula: see text].

Assessment of gas hydrate using pre-stack seismic inversion in Mahanadi Basin, offshore eastern India

2021 ◽  
pp. 1-42
Author(s):  
Maheswar Ojha ◽  
Ranjana Ghosh
Keyword(s):  
Gas Hydrate ◽  
Rock Physics ◽  
Type Equation ◽  
Seismic Inversion ◽  
Log Analysis ◽  
Well Log ◽  
Seismic Section ◽  
Bottom Simulating Reflector ◽  
Hydrate Saturation ◽  
Well Log Analysis

The Indian National Gas Hydrate Program Expedition-01 in 2006 has discovered gas hydrate in Mahanadi offshore basin along the eastern Indian margin. However, well log analysis, pressure core measurements and Infra-Red (IR) anomalies reveal that gas hydrates are distributed as disseminated within the fine-grained sediment, unlike massive gas hydrate deposits in the Krishna-Godavari basin. 2D multi-channel seismic section, which crosses the Holes NGHP-01-9A and 19B located at about 24 km apart shows a continuous bottom-simulating reflector (BSR) along it. We aim to investigate the prospect of gas hydrate accumulation in this area by integrating well log analysis and seismic methods with rock physics modeling. First, we estimate gas hydrate saturation at these two Holes from the observed impedance using the three-phase Biot-type equation (TPBE). Then we establish a linear relationship between gas hydrate saturation and impedance contrast with respect to the water-saturated sediment. Using this established relation and impedance obtained from pre-stack inversion of seismic data, we produce a 2D gas hydrate-distribution image over the entire seismic section. Gas hydrate saturation estimated from resistivity and sonic data at well locations varies within 0-15%, which agrees well with the available pressure core measurements at Hole 19. However, the 2D map of gas hydrate distribution obtained from our method shows maximum gas hydrate saturation is about 40% just above the BSR between the CDP (common depth point) 1450 and 2850. The presence of gas-charged sediments below the BSR is one of the reasons for the strong BSR observed in the seismic section, which is depicted as low impedance in the inverted impedance section. Closed sedimentary structures above the BSR are probably obstructing the movements of free-gas upslope, for which we do not see the presence of gas hydrate throughout the seismic section above the BSR.

Introduction to this special section: Rock physics

2019 ◽  
Vol 38 (5) ◽  
pp. 332-332
Author(s):  
Yongyi Li ◽  
Lev Vernik ◽  
Mark Chapman ◽  
Joel Sarout
Keyword(s):  
Reservoir Characterization ◽  
Model Building ◽  
Seismic Analysis ◽  
Focal Point ◽  
Special Section ◽  
Rock Physics ◽  
Seismic Inversion ◽  
Reservoir Properties ◽  
Model Studies ◽  
Experimental Rock

Rock physics links the physical properties of rocks to geophysical and petrophysical observations and, in the process, serves as a focal point in many exploration and reservoir characterization studies. Today, the field of rock physics and seismic petrophysics embraces new directions with diverse applications in estimating static and dynamic reservoir properties through time-variant mechanical, thermal, chemical, and geologic processes. Integration with new digital and computing technologies is gradually gaining traction. The use of rock physics in seismic imaging, prestack seismic analysis, seismic inversion, and geomechanical model building also contributes to the increase in rock-physics influence. This special section highlights current rock-physics research and practices in several key areas, namely experimental rock physics, rock-physics theory and model studies, and the use of rock physics in reservoir characterizations.

THE INTEGRATED USE OF PETROPHYSICAL, AVO, SEISMIC INVERSION AND 3D VISUALISATION TOOLS FOR RESERVOIR CHARACTERISATION

2001 ◽  
Vol 41 (2) ◽  
pp. 131
Author(s):  
A.G. Sena ◽  
T.M. Smith
Keyword(s):  
Seismic Data ◽  
New Technology ◽  
Seismic Inversion ◽  
Well Log ◽  
Reservoir Properties ◽  
Gas Field ◽  
Geological Interpretation ◽  
3D Visualisation ◽  
Quantitative Understanding ◽  
Inversion Techniques

The successful exploration for new reservoirs in mature areas, as well as the optimal development of existing fields, requires the integration of unconventional geological and geophysical techniques. In particular, the calibration of 3D seismic data to well log information is crucial to obtain a quantitative understanding of reservoir properties. The advent of new technology for prestack seismic data analysis and 3D visualisation has resulted in improved fluid and lithology predictions prior to expensive drilling. Increased reservoir resolution has been achieved by combining seismic inversion with AVO analysis to minimise exploration risk.In this paper we present an integrated and systematic approach to prospect evaluation in an oil/gas field. We will show how petrophysical analysis of well log data can be used as a feasibility tool to determine the fluid and lithology discrimination capabilities of AVO and inversion techniques. Then, a description of effective AVO and prestack inversion tools for reservoir property quantification will be discussed. Finally, the incorporation of the geological interpretation and the use of 3D visualisation will be presented as a key integration tool for the discovery of new plays.

Quantifying reservoir properties of the East Texas Woodbine through rock physics and multiattribute seismic inversion

2005 ◽  
Author(s):  
Ron McWhorter ◽  
Duane Pierce ◽  
Niranjan Banik ◽  
Haibin Xu ◽  
George Bunge ◽  
...  
Keyword(s):  
Rock Physics ◽  
Seismic Inversion ◽  
East Texas ◽  
Reservoir Properties

Seismic inversion for reservoir properties combining statistical rock physics and geostatistics: A review

Geophysics ◽  
2010 ◽  
Vol 75 (5) ◽  
pp. 75A165-75A176 ◽  
Author(s):  
Miguel Bosch ◽  
Tapan Mukerji ◽  
Ezequiel F. Gonzalez
Keyword(s):  
Elastic Properties ◽  
Quantitative Estimation ◽  
Rock Physics ◽  
Seismic Inversion ◽  
Elastic Parameters ◽  
Reservoir Properties ◽  
Sequential Approach ◽  
Geostatistical Methods ◽  
Bayesian Formulation ◽  
Statistical Rock Physics

There are various approaches for quantitative estimation of reservoir properties from seismic inversion. A general Bayesian formulation for the inverse problem can be implemented in two different work flows. In the sequential approach, first seismic data are inverted, deterministically or stochastically, into elastic properties; then rock-physics models transform those elastic properties to the reservoir property of interest. The joint or simultaneous work flow accounts for the elastic parameters and the reservoir properties, often in a Bayesian formulation, guaranteeing consistency between the elastic and reservoir properties. Rock physics plays the important role of linking elastic parameters such as impedances and velocities to reservoir properties of interest such as lithologies, porosity, and pore fluids. Geostatistical methods help add constraints of spatial correlation, conditioning to different kinds of data and incorporating subseismic scales of heterogeneities.

Probabilistic petrophysical-properties estimation integrating statistical rock physics with seismic inversion

Geophysics ◽  
2010 ◽  
Vol 75 (3) ◽  
pp. O21-O37 ◽  
Author(s):  
Dario Grana ◽  
Ernesto Della Rossa
Keyword(s):  
Seismic Data ◽  
Measurement Errors ◽  
Rock Physics ◽  
Seismic Inversion ◽  
Joint Estimation ◽  
Physical Models ◽  
Inversion Method ◽  
Petrophysical Properties ◽  
Reservoir Properties ◽  
Statistical Rock Physics

A joint estimation of petrophysical properties is proposed that combines statistical rock physics and Bayesian seismic inversion. Because elastic attributes are correlated with petrophysical variables (effective porosity, clay content, and water saturation) and this physical link is associated with uncertainties, the petrophysical-properties estimation from seismic data can be seen as a Bayesian inversion problem. The purpose of this work was to develop a strategy for estimating the probability distributions of petrophysical parameters and litho-fluid classes from seismics. Estimation of reservoir properties and the associated uncertainty was performed in three steps: linearized seismic inversion to estimate the probabilities of elastic parameters, probabilistic upscaling to include the scale-changes effect, and petrophysical inversion to estimate the probabilities of petrophysical variables andlitho-fluid classes. Rock-physics equations provide the linkbetween reservoir properties and velocities, and linearized seismic modeling connects velocities and density to seismic amplitude. A full Bayesian approach was adopted to propagate uncertainty from seismics to petrophysics in an integrated framework that takes into account different sources of uncertainty: heterogeneity of the real data, approximation of physical models, measurement errors, and scale changes. The method has been tested, as a feasibility step, on real well data and synthetic seismic data to show reliable propagation of the uncertainty through the three different steps and to compare two statistical approaches: parametric and nonparametric. Application to a real reservoir study (including data from two wells and partially stacked seismic volumes) has provided as a main result the probability densities of petrophysical properties and litho-fluid classes. It demonstrated the applicability of the proposed inversion method.

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