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).

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.

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.

Simultaneous impedance inversion and interpretation for an offshore turbiditic reservoir

2017 ◽  
Vol 5 (3) ◽  
pp. SL9-SL23 ◽  
Author(s):  
Humberto S. Arévalo-López ◽  
Jack P. Dvorkin
Keyword(s):  
Rock Physics ◽  
Clay Content ◽  
Wave Impedance ◽  
New Paradigm ◽  
S Wave ◽  
Impedance Inversion ◽  
Physics Model ◽  
Well Data ◽  
Rock Physics Model ◽  
Amplitude Variation With Angle

By using simultaneous impedance inversion, we obtained P- and S-wave impedance ([Formula: see text] and [Formula: see text]) volumes from angle stacks at a siliciclastic turbidite oil reservoir offshore northwest Australia. The ultimate goal was to interpret these elastic variables for fluid, porosity, and mineralogy. This is why an essential part of our workflow was finding the appropriate rock-physics model based on well data. The model-corrected S-wave velocity [Formula: see text] in the wells was used as an input to impedance inversion. The inversion parameters were optimized in small vertical sections around two wells to obtain the best possible match between the seismic impedances and the upscaled impedances measured at the wells. Special attention was paid to the seismically derived [Formula: see text] ratio because we relied on this parameter for hydrocarbon identification. Even after performing crosscorrelation between the angle stacks to correct for two-way traveltime shifts to align the stacks, these stacks did not indicate a coherent amplitude variation with angle (AVA) dependence. To deal with this common problem, we corrected the mid and far stacks by using the near and ultrafar stacks as anchoring points for fitting a [Formula: see text] AVA curve. This choice allowed us to match the seismically derived [Formula: see text] ratio with that predicted by the rock-physics model in the reservoir. Finally, the rock-physics model was used to interpret these [Formula: see text] and [Formula: see text] for the fluid, porosity, and mineralogy. The new paradigm in our inversion/interpretation workflow is that the ultimate quality control of the inversion is in an accurate deterministic match between the seismically derived petrophysical variables and the corresponding upscaled depth curves at the wells. Our interpretation is very sensitive to the inversion results, especially the [Formula: see text] ratio. Despite this fact, we were able to obtain accurate estimates of porosity and clay content in the reservoir and around it.

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.

Elastic mineral facies: Selecting site-specific elastic moduli of clay

Geophysics ◽  
2017 ◽  
Vol 82 (4) ◽  
pp. MR111-MR119
Author(s):  
Uri Wollner ◽  
Jack P. Dvorkin
Keyword(s):  
Elastic Moduli ◽  
Rock Physics ◽  
Data Sets ◽  
Depth Range ◽  
Chemical Formula ◽  
Rock Matrix ◽  
Well Control ◽  
Physics Model ◽  
Well Data ◽  
Rock Physics Model

The elastic moduli of the mineral constituents of the rock matrix are among the principal inputs in all rock-physics velocity-porosity-mineralogy models. Published experimental data indicate that the elastic moduli for essentially any mineral vary. The ranges of these variations are especially wide for clay. The question addressed here is how to select, based on well data, concrete values for clay’s elastic constants where those for other minerals are fixed. The approach is to find a rock-physics model for zero-clay intervals and then adjust the clay’s constants to describe the intervals dominated by clay using the same model. We examine three data sets from clastic environments, each represented by three wells, where the selected constants for clay were different between the fields but stable within each field. These constants can then be used for seismic forward modeling and interpretation in a specific field away from well control and within a depth range represented in the wells. In essence, we introduce the concept of elastic mineral facies where we identify clay as a mineral with certain elastic moduli rather than by its chemical formula.

scholarly journals A rock physics model for the characterization of organic-rich shale from elastic properties

2015 ◽  
Vol 12 (2) ◽  
pp. 264-272 ◽  
Author(s):  
Ying Li ◽  
Zhi-Qi Guo ◽  
Cai Liu ◽  
Xiang-Yang Li ◽  
Gang Wang
Keyword(s):  
Elastic Properties ◽  
Rock Physics ◽  
Physics Model ◽  
Rock Physics Model

Seismic reflections of gas hydrate from perturbational forward modeling

Geophysics ◽  
2006 ◽  
Vol 71 (6) ◽  
pp. F165-F171 ◽  
Author(s):  
Ingrid Cordon ◽  
Jack Dvorkin ◽  
Gary Mavko
Keyword(s):  
Reservoir Characterization ◽  
Rock Physics ◽  
Clay Content ◽  
The Arctic ◽  
Seismic Amplitude ◽  
Hydrate Reservoir ◽  
Hydrate Saturation ◽  
Physics Model ◽  
Rock Physics Model ◽  
Seismic Reflections

We perturb the elastic properties and attenuation in the Arctic Mallik methane-hydrate reservoir to produce a set of plausible seismic signatures away from the existing well. These perturbations are driven by the changes we impose on porosity, clay content, hydrate saturation, and geometry. The key is a data-guided, theoretical, rock-physics model that we adopt to link velocity and attenuation to porosity, mineralogy, and amount of hydrate. We find that the seismic amplitude is very sensitive to the hydrate saturation in the host sand and its porosity as well as the porosity of the overburden shale. However, changes to the amount of clay in the sand only weakly alter the amplitude. Attenuation, which may be substantial, must be taken into account during hydrate reservoir characterization because it lowers the amplitude to an extent that may affect the hydrate-volume prediction. The spatial structure of the reservoir affects the seismic reflection: A thinly-layered reservoir produces a noticeably different amplitude than a massive reservoir with the same hydrate volume.

Rock-physics diagnostics of an offshore gas field

Geophysics ◽  
2017 ◽  
Vol 82 (4) ◽  
pp. MR121-MR132 ◽  
Author(s):  
Uri Wollner ◽  
Yunfei Yang ◽  
Jack P. Dvorkin
Keyword(s):  
Rock Physics ◽  
Rock Properties ◽  
Gas Field ◽  
Amplitude Variation With Offset ◽  
Rock Physics Modeling ◽  
Physics Modeling ◽  
Using Data ◽  
Physics Model ◽  
Well Data ◽  
Rock Physics Model

Seismic reflections depend on the contrasts of the elastic properties of the subsurface and their 3D geometry. As a result, interpreting seismic data for petrophysical rock properties requires a theoretical rock-physics model that links the seismic response to a rock’s velocity and density. Such a model is based on controlled experiments in which the petrophysical and elastic rock properties are measured on the same samples, such as in the wellbore. Using data from three wells drilled through a clastic offshore gas reservoir, we establish a theoretical rock-physics model that quantitatively explains these data. The modeling is based on the assumption that only three minerals are present: quartz, clay, and feldspar. To have a single rock-physics transform to quantify the well data in the entire intervals under examination in all three wells, we introduced field-specific elastic moduli for the clay. We then used the model to correct the measured shear-wave velocity because it appeared to be unreasonably low. The resulting model-derived Poisson’s ratio is much smaller than the measured ratio, especially in the reservoir. The associated synthetic amplitude variation with offset response appears to be consistent with the recorded seismic angle stacks. We have shown how rock-physics modeling not only helps us to correct the well data, but also allows us to go beyond the settings represented in the wells and quantify the seismic signatures of rock properties and conditions varying in a wider range using forward seismic modeling.

Sign in / Sign up

Export Citation Format

Share Document