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].

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.

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.

Seismic reservoir mapping from 3‐D AVO in a North Sea turbidite system

Geophysics ◽  
2001 ◽  
Vol 66 (4) ◽  
pp. 1157-1176 ◽  
Author(s):  
P. Avseth ◽  
T. Mukerji ◽  
A. Jørstad ◽  
G. Mavko ◽  
T. Veggeland
Keyword(s):  
Monte Carlo ◽  
North Sea ◽  
Seismic Data ◽  
Rock Physics ◽  
Well Log ◽  
Pore Fluids ◽  
Seismic Properties ◽  
Feeder Channel ◽  
Turbidite System ◽  
Seismic Amplitudes

We present a methodology for estimating uncertainties and mapping probabilities of occurrence of different lithofacies and pore fluids from seismic amplitudes, and apply it to a North Sea turbidite system. The methodology combines well log facies analysis, statistical rock physics, and prestack seismic inversion. The probability maps can be used as input data in exploration risk assessment and as constraints in reservoir modeling and performance forecasting. First, we define seismic‐scale sedimentary units which we refer to as seismic lithofacies. These facies represent populations of data (clusters) that have characteristic geologic and seismic properties. In the North Sea field presented in this paper, we find that unconsolidated thick‐bedded clean sands with water, plane laminated thick‐bedded sands with oil, and pure shales have very similar acoustic impedance distributions. However, the [Formula: see text] ratio helps resolve these ambiguities. We establish a statistically representative training database by identifying seismic lithofacies from thin sections, cores, and well log data for a type well. This procedure is guided by diagnostic rock physics modeling. Based on the training data, we perform multivariate classification of data from other wells in the area. From the classification results, we can create cumulative distribution functions of seismic properties for each facies. Pore fluid variations are accounted for by applying the Biot‐Gassmann theory. Next, we conduct amplitude‐variation‐with‐offset (AVO) analysis to predict seismic lithofacies from seismic data. We assess uncertainties in AVO responses related to the inherent natural variability of each seismic lithofacies using a Monte Carlo technique. Based on the Monte Carlo simulation, we generate bivariate probability density functions (pdfs) of zero‐offset reflectivity [R(0)] versus AVO gradient (G) for different facies combinations. By combining R(0) and G values estimated from 2‐D and 3‐D seismic data with the bivariate pdfs estimated from well logs, we use both discriminant analysis and Bayesian classification to predict lithofacies and pore fluids from seismic amplitudes. The final results are spatial maps of the most likely facies and pore fluids, and their occurrence probabilities. These maps show that the studied turbidite system is a point‐sourced submarine fan in which thick‐bedded clean sands are present in the feeder‐channel and in the lobe channels, interbedded sands and shales in marginal areas of the system, and shales outside the margins of the turbidite fan. Oil is most likely present in the central lobe channel and in parts of the feeder channel.

Probabilistic seismic inversion based on rock-physics models

Geophysics ◽  
2007 ◽  
Vol 72 (5) ◽  
pp. R87-R97 ◽  
Author(s):  
Kyle Spikes ◽  
Tapan Mukerji ◽  
Jack Dvorkin ◽  
Gary Mavko
Keyword(s):  
Seismic Data ◽  
Rock Physics ◽  
Clay Content ◽  
Real Data ◽  
Reservoir Properties ◽  
Site Specific ◽  
Earth Models ◽  
Complete Set ◽  
A Site ◽  
Seismic Models

A site-specific rock-physics transform from porosity, mineralogy, and pore fluid to elastic-wave velocities is used to invert seismic amplitude data for clay content, total porosity, and saturation. The implementation is Bayesian and produces probabilistic values of the reservoir properties from seismic measurements and well data. This method focuses on an exploration setting where minimal data exist. Two key assumptions reduce the problem and keep the prior information as noncommittal as possible. First, a prior interpretation of the seismic data is required that provides a geobody on which to perform the inversion. Second, the reservoir thickness is assumed to be constant, as are the rock properties within the reservoir. The prior distributions of the reservoir properties are assumed to be uncorrelated and independent, although this is not an essential assumption. Central to theinversion is the generation of a complete set of earth models derived from the prior distribution. A site-specific rock-physics model translates these properties (clay content, porosity, and saturation) into the elastic domain. A complete set of forward seismic models accompanies the earth models, and these seismic models are compared to the real data on a trace-by-trace basis. The reservoir properties corresponding to the seismic models that match the real data within predefined errors are used to construct the posterior. This method was tested on well and seismic data from offshore western South Africa. Initial results at calibration and test wells indicate an overprediction of porosity and uncertain predictions of clay content and saturation. This is a result of the constant-thickness assumption. However, a highly negative correlation between porosity and thickness is predicted, which manifests the success of this method.

Geostatistical Inversion in Carbonate Reservoirs to Map Reservoir Quality With High Predictability – A Case Study From Onshore Abu Dhabi

2021 ◽  
Author(s):  
S Al Naqbi ◽  
J Ahmed ◽  
J Vargas Rios ◽  
Y Utami ◽  
A Elila ◽  
...  
Keyword(s):  
High Resolution ◽  
Seismic Data ◽  
Pore Volume ◽  
Rock Physics ◽  
Static Model ◽  
Reservoir Quality ◽  
Reservoir Properties ◽  
Geostatistical Inversion ◽  
High Predictability ◽  
The Impact

Abstract The Thamama group of reservoirs consist of porous carbonates laminated with tight carbonates, with pronounced lateral heterogeneities in porosity, permeability, and reservoir thickness. The main objective of our study was mapping variations and reservoir quality prediction away from well control. As the reservoirs were thin and beyond seismic resolution, it was vital that the facies and porosity be mapped in high resolution, with a high predictability, for successful placement of horizontal wells for future development of the field. We established a unified workflow of geostatistical inversion and rock physics to characterize the reservoirs. Geostatistical inversion was run in static models that were converted from depth to time domain. A robust two-way velocity model was built to map the depth grid and its zones on the time seismic data. This ensured correct placement of the predicted high-resolution elastic attributes in the depth static model. Rock physics modeling and Bayesian classification were used to convert the elastic properties into porosity and lithology (static rock-type (SRT)), which were validated in blind wells and used to rank the multiple realizations. In the geostatistical pre-stack inversion, the elastic property prediction was constrained by the seismic data and controlled by variograms, probability distributions and a guide model. The deterministic inversion was used as a guide or prior model and served as a laterally varying mean. Initially, unconstrained inversion was tested by keeping all wells as blind and the predictions were optimized by updating the input parameters. The stochastic inversion results were also frequency filtered in several frequency bands, to understand the impact of seismic data and variograms on the prediction. Finally, 30 wells were used as input, to generate 80 realizations of P-impedance, S-impedance, Vp/Vs, and density. After converting back to depth, 30 additional blind wells were used to validate the predicted porosity, with a high correlation of more than 0.8. The realizations were ranked based on the porosity predictability in blind wells combined with the pore volume histograms. Realizations with high predictability and close to the P10, P50 and P90 cases (of pore volume) were selected for further use. Based on the rock physics analysis, the predicted lithology classes were associated with the geological rock-types (SRT) for incorporation in the static model. The study presents an innovative approach to successfully integrate geostatistical inversion and rock physics with static modeling. This workflow will generate seismically constrained high-resolution reservoir properties for thin reservoirs, such as porosity and lithology, which are seamlessly mapped in the depth domain for optimized development of the field. It will also account for the uncertainties in the reservoir model through the generation of multiple equiprobable realizations or scenarios.

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.

An experimental investigation of factors influencing compressional‐ and shear‐wave velocities and attenuations in tight gas sandstones

Geophysics ◽  
1994 ◽  
Vol 59 (1) ◽  
pp. 77-86 ◽  
Author(s):  
Azra N. Tutuncu ◽  
Augusto L. Podio ◽  
Mukul M. Sharma
Keyword(s):  
Shear Wave ◽  
Correlation Method ◽  
Clay Content ◽  
Spectral Ratio ◽  
Peak Frequency ◽  
Ratio Method ◽  
Tight Gas ◽  
S Waves ◽  
Amplitude Spectra ◽  
Tight Gas Sandstones

Results are presented for compressional and shear velocities and attenuations in fully brine‐saturated tight gas cores with porosities from 3 to 11.9 percent and clay contents from 1 to 38 percent. The influence of porosity, clay content, frequency, and stress on velocities and attenuations were examined using the amplitude spectra of P‐ and S‐waves in the frequency domain. Attenuations of samples were obtained using the spectral ratio method. For a few selected samples the attenuations were also measured using the length correlation method and these results were compared with the spectral ratio results. In tight gas sandstones, the attenuations obtained were 2 to 5 times greater than the attenuation obtained for Berea sandstone. In general, the presence of clay softens the rock grain contacts causing smaller values of compressional ([Formula: see text] and shear ([Formula: see text]) velocities as the clay content increases. However, the [Formula: see text] ratio was found to increase with clay content. Compressional‐and shear‐wave amplitude spectra exhibited a shift in peak frequency toward lower frequencies for samples with higher clay content when compared to clean samples. Velocities and attenuations were found to be frequency dependent, but the positive slope of both compressional and shear attenuations indicate that scattering starts to dominate at the lower frequency end of the ultrasonic measurements. Both [Formula: see text] and [Formula: see text] increased while both compressional and shear attenuations decreased when stress was increased.

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