Inversion of multicomponent 3D vertical seismic profile data for porosity and CO2 saturation at the Cranfield injection site, Cranfield, MS

2014 ◽  
Vol 2 (2) ◽  
pp. SE77-SE89 ◽  
Author(s):  
Russell W. Carter ◽  
Kyle T. Spikes ◽  
Thomas Hess
Keyword(s):  
Rock Physics ◽  
Seismic Profile ◽  
Pore Fluid ◽  
Well Logs ◽  
Fluid Composition ◽  
Vertical Seismic Profile ◽  
Fluid Saturation ◽  
Vsp Data ◽  
Physics Model ◽  
Rock Physics Model

Studying how injected [Formula: see text] affects the seismic response of reservoir rocks is important because it can improve subsurface characterization where [Formula: see text] injection is taking place. This study uses multicomponent data from a 3D vertical seismic profile (VSP) and well logs to model and invert probabilistically for the porosity and [Formula: see text] saturation at the Cranfield reservoir. The well logs were used to calibrate a rock-physics model. Once the accuracy of the model was verified, P-impedance and [Formula: see text]/[Formula: see text] from inverted multicomponent VSP data were used to estimate the porosity and fluid saturation. This inversion generated probabilistic estimates of porosity and fluid saturation for the area of the reservoir sampled by PP- and PS-waves. Inversion results using the measured well log data for calibration indicated that the model was able to estimate porosity with a relatively high degree of accuracy, with the root-mean-square (rms) error being less than 3% for all calibration tests. Pore-fluid composition was estimated, however, with reduced accuracy, with rms errors ranging from 6% to 22% depending on the composition of the calibration fluid. Results from integrating the multicomponent VSP data with the rock-physics model indicated that estimated reservoir porosities are quite close to measured values at an observation well. Pore-fluid composition estimates indicated that this method can differentiate between areas containing [Formula: see text] and those that do not.

Seismic Reflections of Rock Properties in a Clastic Environment

2021 ◽  
Author(s):  
Vagif Suleymanov ◽  
Abdulhamid Almumtin ◽  
Guenther Glatz ◽  
Jack Dvorkin
Keyword(s):  
Rock Physics ◽  
Pore Fluid ◽  
Rock Properties ◽  
Petrophysical Properties ◽  
Sound Waves ◽  
Reservoir Properties ◽  
Field Guide ◽  
Physics Model ◽  
Rock Physics Model ◽  
Seismic Reflections

Abstract Generated by the propagation of sound waves, seismic reflections are essentially the reflections at the interface between various subsurface formations. Traditionally, these reflections are interpreted in a qualitative way by mapping subsurface geology without quantifying the rock properties inside the strata, namely the porosity, mineralogy, and pore fluid. This study aims to conduct the needed quantitative interpretation by the means of rock physics to establish the relation between rock elastic and petrophysical properties for reservoir characterization. We conduct rock physics diagnostics to find a theoretical rock physics model relevant to the data by examining the wireline data from a clastic depositional environment associated with a tight gas sandstone in the Continental US. First, we conduct the rock physics diagnostics by using theoretical fluid substitution to establish the relevant rock physics models. Once these models are determined, we theoretically vary the thickness of the intervals, the pore fluid, as well as the porosity and mineralogy to generate geologically plausible pseudo-scenarios. Finally, Zoeppritz (1919) equations are exploited to obtain the expected amplitude versus offset (AVO) and the gradient versus intercept curves of these scenarios. The relationship between elastic and petrophysical properties was established using forward seismic modeling. Several theoretical rock physics models, namely Raymer-Dvorkin, soft-sand, stiff-sand, and constant-cement models were applied to the wireline data under examination. The modeling assumes that only two minerals are present: quartz and clay. The appropriate rock physics model appears to be constant-cement model with a high coordination number. The result is a seismic reflection catalogue that can serve as a field guide for interpreting real seismic reflections, as well as to determine the seismic visibility of the variations in the reservoir geometry, the pore fluid, and the porosity. The obtained reservoir properties may be extrapolated to prospects away from the well control to consider certain what-if scenarios like plausible lithology or fluid variations. This enables building of a catalogue of synthetic seismic reflections of rock properties to be used by the interpreter as a field guide relating seismic data to volumetric reservoir properties.

Seismic-scale dependence of the effective bulk modulus of pore fluid upon water saturation

Geophysics ◽  
2018 ◽  
Vol 83 (2) ◽  
pp. MR81-MR91 ◽  
Author(s):  
Uri Wollner ◽  
Jack Dvorkin
Keyword(s):  
Bulk Modulus ◽  
Water Saturation ◽  
Rock Physics ◽  
Clay Content ◽  
Pore Fluid ◽  
Arithmetic Average ◽  
Physics Model ◽  
Rock Physics Model ◽  
The Individual ◽  
Seismic Scale

We apply a rock-physics model established from fine-scale data (well or laboratory) to the seismically derived elastic variables (the impedances and bulk density) to arrive at the seismic-scale total porosity, clay content, and water saturation. These three outputs are defined as the volume-averaged porosity, clay content, and porosity-weighted water saturation, respectively. To use the rock-physics model, we need to know how to relate the bulk modulus of the pore fluid to water saturation in the presence of hydrocarbons. At the wellbore-measurement scale, this relation is typically the saturation-weighted harmonic average of the bulk moduli of the water and hydrocarbon. The question posed here is what this relation is at the seismic scale. The method of solution is based on the wellbore-scale data. Specifically, we seek the seismic-scale bulk modulus of the pore fluid that, if used in the rock-physics model, will yield the Backus-upscaled elastic constants at the well from the above-defined seismic-scale petrophysical variables. The answer depends on the vertical distribution of all these variables. By using examples of synthetic and real wells and assuming the lack of hydraulic communication between adjacent rock bodies, we find that this relation trends toward the arithmetic average of the individual bulk moduli of the pore-fluid phases. In fact, it falls in between the arithmetic average and the linear combination of 0.75 arithmetic and 0.25 harmonic averages. We also develop an approximate analytical solution under the assumption of weak elastic and porosity contrasts and for medium-to-high porosity sediment that indicates that the seismic-scale bulk modulus of the pore fluid is close to the arithmetic average of those in the individual layers.

Hydrate quantification: Integrating full-waveform inversion, seismic attributes, and rock physics

2016 ◽  
Vol 4 (1) ◽  
pp. SA55-SA71 ◽  
Author(s):  
P. Jaiswal
Keyword(s):  
Velocity Field ◽  
Waveform Inversion ◽  
Rock Physics ◽  
Well Logs ◽  
Full Waveform Inversion ◽  
Secondary Porosity ◽  
Full Waveform ◽  
Hydrate Saturation ◽  
Physics Model ◽  
Rock Physics Model

Hydrate quantification from seismic data is a two-pronged challenge. The first is creating a velocity field with high enough resolution and accuracy such that it is a meaningful representation of hydrate variability in the host sediments. The second is constructing a rock-physics model that accounts for the appropriate growth of the hydrate and allows for the interpretation of the velocity field in terms of hydrate saturation. In this paper, both challenges are addressed in a quantification workflow that uses 2D seismic and colocated well logs. The study area is situated in the Krishna-Godavari Basin, offshore eastern Indian coast, where hydrate was discovered in the National Gas Hydrate Program Expedition 01 (NGHP-01). The workflow hinges on a rock-physics model that expresses total hydrate saturation in terms of primary (matrix) and secondary (fractures, faults, voids, etc.) porosities and their respective primary and secondary saturations and incorporates hydrate-filled secondary porosity into the rock as an additional grain type using the Hashin-Shtrikman bounds. The model is first applied to a set of well logs at a colocated site, NGHP-01-10, following which the application is extended into the seismic domain by (1) the incoherency attribute as a proxy for secondary porosity and (2) a full-waveform inversion-based P-wave velocity ([Formula: see text]) model as a proxy for primary saturation. The remaining — the primary porosity and secondary saturation — are assumed to remain the same across the seismic profile as at the site NGHP-01-10. The resulting, seismically estimated, hydrate saturation compares well with saturations from core depressurization at colocated sites NGHP-01-10 and NGHP-01-13. The quantification workflow presented here is potentially adaptable to other geographical areas with the caveat that empirical relations between porosity, saturation, and seismic attributes may have to be locally established.

Rock-physics transforms and scale of investigation

Geophysics ◽  
2017 ◽  
Vol 82 (3) ◽  
pp. MR75-MR88 ◽  
Author(s):  
Jack Dvorkin ◽  
Uri Wollner
Keyword(s):  
Elastic Properties ◽  
Rock Physics ◽  
Clay Content ◽  
Pore Fluid ◽  
Petrophysical Properties ◽  
Reflection Seismology ◽  
Physics Model ◽  
Well Data ◽  
Rock Physics Model ◽  
Seismic Scale

Rock-physics “velocity-porosity” transforms are usually established on sets of laboratory and/or well data with the latter data source being dominant in recent practice. The purpose of establishing such transforms is to (1) conduct forward modeling of the seismic response for various geologically plausible “what if” scenarios in the subsurface and (2) interpret seismic data for petrophysical properties and conditions, such as porosity, clay content, and pore fluid. Because the scale of investigation in the well is considerably smaller than that in reflection seismology, an important question is whether the rock-physics model established in the well can be used at the seismic scale. We use synthetic examples and well data to show that a rock-physics model established at the well approximately holds at the seismic scale, suggest a reason for this scale independence, and explore where it may be violated. The same question can be addressed as an inverse problem: Assume that we have a rock-physics transform and know that it works at the scale of investigation at which the elastic properties are seismically measured. What are the upscaled (smeared) petrophysical properties and conditions that these elastic properties point to? It appears that they are approximately the arithmetically volume-averaged porosity and clay content (in a simple quartz/clay setting) and are close to the arithmetically volume-averaged bulk modulus of the pore fluid (rather than averaged saturation).

Rock-physics-based double-difference inversion for CO2 saturation and porosity at the Cranfield CO2 injection site

2015 ◽  
Vol 3 (2) ◽  
pp. SM23-SM35
Author(s):  
Russell W. Carter ◽  
Kyle T. Spikes
Keyword(s):  
Seismic Data ◽  
Rock Physics ◽  
Time Lapse ◽  
Reservoir Rock ◽  
Well Logs ◽  
Double Difference ◽  
Co2 Injection ◽  
Text Data ◽  
Physics Model ◽  
Rock Physics Model

Large-scale subsurface injection of [Formula: see text] has the potential to reduce emissions of atmospheric [Formula: see text] and improve oil recovery. Studying the effects of injected [Formula: see text] on the elastic properties of the saturated reservoir rock can help to improve long-term monitoring effectiveness and accuracy at locations undergoing [Formula: see text] injection. We used two vintages of existing 3D surface seismic data and well logs to probabilistically invert for the [Formula: see text] saturation and porosity at the Cranfield reservoir using a double-difference approach. The first step of this work was to calibrate the rock-physics model to the well-log data. Next, the baseline and time-lapse seismic data sets were inverted for acoustic impedance [Formula: see text] using a high-resolution basis pursuit inversion technique. The reservoir porosity was derived statistically from the rock-physics model based on the [Formula: see text] estimates inverted from the baseline survey. The porosity estimates were used in the double-difference routine as the fixed initial model from which [Formula: see text] saturation was then estimated from the time-lapse [Formula: see text] data. Porosity was assumed to remain constant between survey vintages; therefore, the changes between the baseline and time-lapse [Formula: see text] data may be inverted for [Formula: see text] saturation from the injection activities using the calibrated rock-physics model. Comparisons of inverted and measured porosity from well logs indicated quite accurate results. Estimates of [Formula: see text] saturation found less accuracy than the porosity estimates.

Q estimation from vertical seismic profile data and anomalous variations in the central North Sea

Geophysics ◽  
1985 ◽  
Vol 50 (4) ◽  
pp. 615-626 ◽  
Author(s):  
S. D. Stainsby ◽  
M. H. Worthington
Keyword(s):  
North Sea ◽  
Pulse Width ◽  
Spectral Ratio ◽  
Seismic Profile ◽  
Seismic Attenuation ◽  
Recording Equipment ◽  
Vertical Seismic Profile ◽  
High Attenuation ◽  
Vsp Data ◽  
Central North Sea

Four different methods of estimating Q from vertical seismic profile (VSP) data based on measurements of spectral ratios, pulse amplitude, pulse width, and zeroth lag autocorrelation of the attenuated impulse are described. The last procedure is referred to as the pulse‐power method. Practical problems concerning nonlinearity in the estimating procedures, uncertainties in the gain setting of the recording equipment, and the influence of structure are considered in detail. VSP data recorded in a well in the central North Sea were processed to obtain estimates of seismic attenuation. These data revealed a zone of high attenuation from approximately 4 900 ft to [Formula: see text] ft with a value of [Formula: see text] Results of the spectral‐ratio analysis show that the data conform to a linear constant Q model. In addition, since the pulse‐width measurement is dependent upon the dispersive model adopted, it is shown that a nondispersive model cannot possibly provide a match to the real data. No unambiguous evidence is presented that explains the cause of this low Q zone. However, it is tentatively concluded that the seismic attenuation may be associated with the degree of compaction of the sediments and the presence of deabsorbed gases.

Multivariate probabilistic rock physics models using Kumaraswamy distributions

Geophysics ◽  
2021 ◽  
pp. 1-43
Author(s):  
Dario Grana
Keyword(s):  
Probability Density Function ◽  
Probability Density ◽  
Density Function ◽  
Random Variables ◽  
Rock Physics ◽  
Petrophysical Properties ◽  
Kumaraswamy Distribution ◽  
Model Predictions ◽  
Physics Model ◽  
Rock Physics Model

Rock physics models are physical equations that map petrophysical properties into geophysical variables, such as elastic properties and density. These equations are generally used in quantitative log and seismic interpretation to estimate the properties of interest from measured well logs and seismic data. Such models are generally calibrated using core samples and well log data and result in accurate predictions of the unknown properties. Because the input data are often affected by measurement errors, the model predictions are often uncertain. Instead of applying rock physics models to deterministic measurements, I propose to apply the models to the probability density function of the measurements. This approach has been previously adopted in literature using Gaussian distributions, but for petrophysical properties of porous rocks, such as volumetric fractions of solid and fluid components, the standard probabilistic formulation based on Gaussian assumptions is not applicable due to the bounded nature of the properties, the multimodality, and the non-symmetric behavior. The proposed approach is based on the Kumaraswamy probability density function for continuous random variables, which allows modeling double bounded non-symmetric distributions and is analytically tractable, unlike the Beta or Dirichtlet distributions. I present a probabilistic rock physics model applied to double bounded continuous random variables distributed according to a Kumaraswamy distribution and derive the analytical solution of the posterior distribution of the rock physics model predictions. The method is illustrated for three rock physics models: Raymer’s equation, Dvorkin’s stiff sand model, and Kuster-Toksoz inclusion model.

Porosity estimation based on rock skeleton general formula and comprehensive pore structure parameter – An application to a tight-sand reservoir

2021 ◽  
pp. 1-59
Author(s):  
Kai Lin ◽  
Xilei He ◽  
Bo Zhang ◽  
Xiaotao Wen ◽  
Zhenhua He ◽  
...  
Keyword(s):  
Aspect Ratio ◽  
Pore Structure ◽  
Seismic Data ◽  
Rock Physics ◽  
Structure Parameters ◽  
Pore Structure Parameter ◽  
Elastic Parameters ◽  
Physics Model ◽  
Rock Physics Model ◽  
Porosity Estimation

Most of current 3D reservoir’s porosity estimation methods are based on analyzing the elastic parameters inverted from seismic data. It is well-known that elastic parameters vary with pore structure parameters such as pore aspect ratio, consolidate coefficient, critical porosity, etc. Thus, we may obtain inaccurate 3D porosity estimation if the chosen rock physics model fails properly address the effects of pore structure parameters on the elastic parameters. However, most of current rock physics models only consider one pore structure parameter such as pore aspect ratio or consolidation coefficient. To consider the effect of multiple pore structure parameters on the elastic parameters, we propose a comprehensive pore structure (CPS) parameter set that is generalized from the current popular rock physics models. The new CPS set is based on the first order approximation of current rock physics models that consider the effect of pore aspect ratio on elastic parameters. The new CPS set can accurately simulate the behavior of current rock physics models that consider the effect of pore structure parameters on elastic parameters. To demonstrate the effectiveness of proposed parameters in porosity estimation, we use a theoretical model to demonstrate that the proposed CPS parameter set properly addresses the effect of pore aspect ratio on elastic parameters such as velocity and porosity. Then, we obtain a 3D porosity estimation for a tight sand reservoir by applying it seismic data. We also predict the porosity of the tight sand reservoir by using neural network algorithm and a rock physics model that is commonly used in porosity estimation. The comparison demonstrates that predicted porosity has higher correlation with the porosity logs at the blind well locations.

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