scholarly journals An approach for predicting stress-induced anisotropy around a borehole

Geophysics ◽  
2013 ◽  
Vol 78 (3) ◽  
pp. D143-D150 ◽  
Author(s):  
Xinding Fang ◽  
Michael Fehler ◽  
Zhenya Zhu ◽  
Tianrun Chen ◽  
Stephen Brown ◽  
...  

Formation elastic properties near a borehole may be altered from their original state due to the stress concentration around the borehole. This could result in a biased estimation of formation properties but could provide a means to estimate in situ stress from sonic logging data. To properly account for the formation property alteration, we propose an iterative numerical approach to calculate stress-induced anisotropy around a borehole by combining a rock physics model and a finite-element method. We tested the validity and accuracy of our approach by comparing numerical results to laboratory measurements of the stress-strain relation of a sample of Berea sandstone, which contains a borehole and is subjected to a uniaxial stress loading. Our iterative approach converges very fast and can be applied to calculate the spatially varying stiffness tensor of the formation around a borehole for any given stress state.

2016 ◽  
Author(s):  
Wang Changsheng* ◽  
Shi Yujiang ◽  
Wang Daxing ◽  
Zhang Haitao

Geophysics ◽  
2018 ◽  
Vol 83 (3) ◽  
pp. MR167-MR185 ◽  
Author(s):  
Romain Prioul ◽  
Richard Nolen-Hoeksema ◽  
MaryEllen Loan ◽  
Michael Herron ◽  
Ridvan Akkurt ◽  
...  

We have developed a method using measurements on drill cuttings as well as calibrated models to estimate anisotropic mechanical properties and stresses in unconventional reservoirs, when logs are not available in lateral wells. We measured mineralogy and organic matter on cuttings using diffuse reflectance infrared Fourier transform spectroscopy (DRIFTS). We described the methodology and illustrated it using two vertical control wells in the Vaca Muerta Formation, Argentina, and one lateral well drilled in the low-maturity oil-bearing reservoir. The method has two steps. First, using a vertical control well containing measurements from cuttings, a comprehensive logging suite, cores, and in situ stress tests, we define and calibrate four models: petrophysical, rock physics, dynamic-static elastic, and geomechanical. The petrophysical model provides petrophysical constituent volumes (mineralogy, organic matter, and fluids) from logs or DRIFTS inputs to the rock-physics model for calculating the dynamic anisotropic elastic moduli. The dynamic-static elastic and geomechanics models provide the relationships for computing static elastic properties and the minimum stress. Second, we acquire DRIFTS data on cuttings in the target lateral well and apply the four models for calculating stresses. We find that the method is successful for two reasons. First, the sonic-log-derived elastic moduli could be reconstructed accurately from the rock-physics model using input from petrophysical volumes from logs and DRIFTS data. A striking observation is that the elastic-property heterogeneity in those wells is explainable almost solely by compositional variations. Second, petrophysical volumes can be reconstructed by the petrophysical model and DRIFTS data. In the lateral well, we observed horizontal variations of mineralogy and organic matter, which controlled variations of elastic moduli and its anisotropy, and, in turn, affected partitioning of the gravitational and tectonic components in the minimum stress. This methodology promises accurate in situ stress estimates using cutting-based measurements and assessments of unconventional-reservoir heterogeneity.


Geophysics ◽  
2021 ◽  
pp. 1-43
Author(s):  
Dario Grana

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.


2021 ◽  
pp. 1-59
Author(s):  
Kai Lin ◽  
Xilei He ◽  
Bo Zhang ◽  
Xiaotao Wen ◽  
Zhenhua He ◽  
...  

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.


2010 ◽  
Vol 75 (1) ◽  
pp. 59-71 ◽  
Author(s):  
Takao Inamori ◽  
Masami Hato ◽  
Kiyofumi Suzuki ◽  
Tatsuo Saeki

2006 ◽  
Author(s):  
Kyle Spikes ◽  
Jack Dvorkin ◽  
Gary Mavko

Sign in / Sign up

Export Citation Format

Share Document