Rock-physics diagnostics of a turbidite oil reservoir offshore northwest Australia

Geophysics ◽  
2017 ◽  
Vol 82 (1) ◽  
pp. MR1-MR13 ◽  
Author(s):  
Humberto S. Arévalo-López ◽  
Jack P. Dvorkin
Keyword(s):  
Seismic Data ◽  
Rock Physics ◽  
Rock Properties ◽  
Oil Reservoir ◽  
Controlled Experiments ◽  
Seismic Modeling ◽  
Physics Model ◽  
Rock Physics Model ◽  
Offshore Oil ◽  
Northwest Australia

Interpreting seismic data for petrophysical rock properties requires a rock-physics model that links the petrophysical rock properties to the elastic properties, such as velocity and impedance. Such a model can only be established from controlled experiments in which both groups of rock properties are measured on the same samples. A prolific source of such data is wellbore measurements. We use data from four wells drilled through a clastic offshore oil reservoir to perform rock-physics diagnostics, i.e., to find a theoretical rock-physics model that quantitatively explains the measurements. Using the model, we correct questionable well curves. Moreover, a crucial purpose of rock-physics diagnostics is to go beyond the settings represented in the wells and understand the seismic signatures of rock properties varying in a wider range via forward seismic modeling. With this goal in mind, we use our model to generate synthetic seismic gathers from perturbational modeling to address “what-if” scenarios not present in the wells.

Stochastic perturbation optimization for discrete-continuous inverse problems

Geophysics ◽  
2020 ◽  
Vol 85 (5) ◽  
pp. M73-M83 ◽  
Author(s):  
Leonardo Azevedo ◽  
Dario Grana ◽  
Leandro de Figueiredo
Keyword(s):  
Seismic Data ◽  
Seismic Reflection ◽  
Stochastic Perturbation ◽  
Rock Physics ◽  
Rock Properties ◽  
Petrophysical Properties ◽  
Seismic Reflection Data ◽  
Reflection Data ◽  
Physics Model ◽  
Rock Physics Model

Accurate subsurface modeling and characterization require the prediction of facies and rock properties within the reservoir model. This is commonly achieved by inverting geophysical data, such as seismic reflection data, using a two-step approach either in the discrete or the continuous domain. We have adopted an iterative simultaneous method, namely, stochastic perturbation optimization, to invert seismic reflection data jointly for facies and rock properties. Facies first are simulated according to a Markov chain model, and then rock properties are generated with stochastic sequential simulation and cosimulation conditioned to each facies. Elastic and seismic data are computed by applying a rock-physics model to the realizations of petrophysical properties and a seismic convolutional model. The similarity between observed and synthetic seismic data is used to update the solution by perturbing facies and rock properties until convergence. Coupling the discrete and continuous domains ensures a consistent perturbation of the reservoir models throughout the iterations. We have evaluated the method in a 1D synthetic example for the estimation of facies and porosity from zero-offset seismic data assuming a linear rock-physics model to demonstrate the validity of the method. Then, we apply the method to a real 3D data set from the North Sea for the joint estimation of facies and petrophysical properties from prestack seismic data. The results show spatially consistent rock and fluid inverted models in which the predicted facies reproduce the vertical ordering as observed in the well data.

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.

Estimating the amount of gas hydrate and free gas from marine seismic data

Geophysics ◽  
2000 ◽  
Vol 65 (2) ◽  
pp. 565-573 ◽  
Author(s):  
Christine Ecker ◽  
Jack Dvorkin ◽  
Amos M. Nur
Keyword(s):  
Gas Hydrate ◽  
Seismic Data ◽  
Rock Physics ◽  
Free Gas ◽  
Interval Velocity ◽  
Blake Ridge ◽  
Hydrate Saturation ◽  
Physics Model ◽  
Rock Physics Model ◽  
Marine Seismic

Marine seismic data and well‐log measurements at the Blake Ridge offshore South Carolina show that prominent seismic bottom‐simulating reflectors (BSRs) are caused by sediment layers with gas hydrate overlying sediments with free gas. We apply a theoretical rock‐physics model to 2-D Blake Ridge marine seismic data to determine gas‐hydrate and free‐gas saturation. High‐porosity marine sediment is modeled as a granular system where the elastic wave velocities are linked to porosity; effective pressure; mineralogy; elastic properties of the pore‐filling material; and water, gas, and gas‐hydrate saturation of the pore space. To apply this model to seismic data, we first obtain interval velocity using stacking velocity analysis. Next, all input parameters to the rock‐physics model, except porosity and water, gas, and gas hydrate saturation, are estimated from geologic information. To estimate porosity and saturation from interval velocity, we first assume that the entire sediment does not contain gas hydrate or free gas. Then we use the rock‐physics model to calculate porosity directly from the interval velocity. Such porosity profiles appear to have anomalies where gas hydrate and free gas are present (as compared to typical profiles expected and obtained in sediment without gas hydrate or gas). Porosity is underestimated in the hydrate region and is overestimated in the free‐gas region. We calculate the porosity residuals by subtracting a typical porosity profile (without gas hydrate and gas) from that with anomalies. Next we use the rock‐physics model to eliminate these anomalies by introducing gas‐hydrate or gas saturation. As a result, we obtain the desired 2-D saturation map. The maximum gas‐hydrate saturation thus obtained is between 13% and 18% of the pore space (depending on the version of the model used). These saturation values are consistent with those measured in the Blake Ridge wells (away from the seismic line), which are about 12%. Free‐gas saturation varies between 1% and 2%. The saturation estimates are extremely sensitive to the input velocity values. Therefore, accurate velocity determination is crucial for correct reservoir characterization.

Research on anisotropy of shale oil reservoir based on rock physics model

2016 ◽  
Vol 13 (2) ◽  
pp. 382-392 ◽  
Author(s):  
Zhi-Qi Guo ◽  
Cai Liu ◽  
Xi-Wu Liu ◽  
Ning Dong ◽  
Yu-Wei Liu
Keyword(s):  
Rock Physics ◽  
Oil Reservoir ◽  
Shale Oil ◽  
Physics Model ◽  
Rock Physics Model

Prediction of porosity and gas saturation for deep-buried sandstone reservoirs from seismic data using an improved rock-physics model

2019 ◽  
Vol 67 (2) ◽  
pp. 557-575 ◽  
Author(s):  
Yaneng Luo ◽  
Handong Huang ◽  
Morten Jakobsen ◽  
Yadi Yang ◽  
Jinwei Zhang ◽  
...  
Keyword(s):  
Seismic Data ◽  
Rock Physics ◽  
Gas Saturation ◽  
Sandstone Reservoirs ◽  
Physics Model ◽  
Rock Physics Model

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.

Two-parameter prestack seismic inversion of porosity and pore structure parameter of fractured carbonate reservoirs: Part 1 — Methods

2018 ◽  
Vol 6 (4) ◽  
pp. SM1-SM8 ◽  
Author(s):  
Tingting Zhang ◽  
Yuefeng Sun
Keyword(s):  
Pore Structure ◽  
Seismic Data ◽  
Rock Physics ◽  
Seismic Inversion ◽  
High Porosity ◽  
Structure Parameter ◽  
Pore Structure Parameter ◽  
Fractured Zones ◽  
Physics Model ◽  
Rock Physics Model

Fractured zones in deeply buried carbonate hills are important because they often have better permeability resulting in prolific production than similar low-porosity rocks. Nevertheless, their detection poses great challenge to conventional seismic inversion methods because they are mostly low in acoustic impedance and bulk modulus, hardly distinguishable from high-porosity zones or mudstones. A proxy parameter of pore structure defined in a rock-physics model, the so-called Sun model, has been used for delineating fractured zones in which the pore structure parameter is relatively high, whereas the porosity is low in general. Simultaneous seismic inversion of the pore structure parameter and porosity proves to be difficult and nontrivial in practice. Although the pore structure parameter is well-defined at locations where density, P-, and S-velocity are known from logs, estimation of P- and S-velocity information, especially density information from prestack seismic data is rather challenging. A three-step iterative inversion method, which uses acoustic, gradient, and elastic impedance from angle-stacked seismic data as input to the rock-physics model for calculating porosity and bulk and shear pore structure parameters simultaneously, is proposed and implemented to solve this problem. The methodology is successfully tested with well logs and seismic data from a deeply buried carbonate hill in the Bohai Bay Basin, China.

A predictive anisotropic rock-physics model for estimating elastic rock properties of unconventional shale reservoirs

2019 ◽  
Vol 38 (5) ◽  
pp. 358-365 ◽  
Author(s):  
Colin M. Sayers ◽  
Sagnik Dasgupta
Keyword(s):  
Accurate Determination ◽  
Rock Physics ◽  
Seismic Inversion ◽  
P Wave ◽  
Rock Properties ◽  
Anisotropic Rock ◽  
Rock Classification ◽  
Shale Reservoirs ◽  
Physics Model ◽  
Rock Physics Model

This paper presents a predictive rock-physics model for unconventional shale reservoirs based on an extended Maxwell scheme. This model accounts for intrinsic anisotropy of rock matrix and heterogeneities and shape-induced anisotropy arising because the dimensions of kerogen inclusions and pores are larger parallel to the bedding plane than perpendicular to this plane. The model relates the results of seismic amplitude variation with offset inversion, such as P- and S-impedance, to the composition of the rock and enables identification of rock classes such as calcareous, argillaceous, siliceous, and mixed shales. This allows the choice of locations with the best potential for economic production of hydrocarbons. While this can be done using well data, prestack inversion of seismic P-wave data allows identification of the best locations before the wells are drilled. The results clearly show the ambiguity in rock classification obtained using poststack inversion of P-wave seismic data and demonstrate the need for prestack seismic inversion. The model provides estimates of formation anisotropy, as required for accurate determination of P- and S-impedance, and shows that anisotropy is a function not only of clay content but also other components of the rock as well as the aspect ratio of kerogen and pores. Estimates of minimum horizontal stress based on the model demonstrate the need to identify rock class and estimate anisotropy to determine the location of any stress barriers that may inhibit hydraulic fracture growth.

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.

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