Historically nuclear magnetic resonance (NMR) is used as a useful tool in petrophysical based reservoir evaluation. The objective of this study is to define a relationship between NMR T2 distribution and seismic attributes for accurately rock properties prediction. To define rock properties, we used laboratory NMR and ultrasonic measured data, rock physics, and AVO analysis. From this study, we define the following relationship:
Presentation Date: Wednesday, October 19, 2016
Start Time: 11:10:00 AM
Location: Lobby D/C
Presentation Type: POSTER
The objective of this study is to demonstrate the power of integrating rock physics theory, measurement and simulation to improve facies prediction in an unconventional limestone and shale reservoir. Reliable facies prediction is a challenge in unconventional reservoir characterization because of complex geological heterogeneities. Both deterministic and probabilistic approaches are commonly used in facies classifications that use well and seismic data. Bayes' theory with uninformative priors is often used for probabilistic facies classification. We provide a case study that uses Bayes' theory with informative priors for facies classification from pre-stack simultaneous elastic inversion results in an unconventional reservoir. In the proposed methodology, we integrate rock physics based theory, measurements and simulation with Bayesian statistical techniques where the prior probability represents our knowledge about rock properties, and is consistent with our geological knowledge, rock physics theory and measured data. We evaluate four facies classification methodologies: deterministic method, probabilistic method with uninformative priors, probabilistic method with uninformative priors and training facies defined from simulation, and probabilistic method with informative priors and training facies defined from simulation. This study indicates that, in probabilistic facies classification (Method 2), if uninformative priors are used, results are sub-optimal compared to deterministic methods involving a Rock Physics Template (RPT) workflow (Method 1). Additionally, probabilistic facies classification can be further improved if we use uninformative priors and training facies defined from Monte Carlo simulation (Method 3). Probabilistic facies prediction improves if we use informative priors and training facies defined from Monte Carlo simulation (Method 4).
Presentation Date: Wednesday, October 19, 2016
Start Time: 10:20:00 AM
Presentation Type: ORAL
As indicated by Thomsen's landmark paper on seismic anisotropy, delta (δ) can be positive or negative. Because of this, anisotropy may have an additive or subtractive effect on stress ratios, pore-pressure, tectonic stress and anisotropy gradient predictions for seismic based geomechanical characterization of conventional and unconventional reservoirs. Therefore, the objective of this study is to demonstrate the effect of Thomsen's δ on stress anisotropy in complex hydrocarbon reservoirs. We provided the relations between vertical and horizontal stress as a function of δ for orthorhombic media. Furthermore, we derived a mechanical definition of Thomsen's δ to reveal when δ is positive and when δ is negative. Finally, we established a link between δ, tectonic stress and anisotropy gradient. For conventional depleted reservoirs, we demonstrated how δ can be negative because of small horizontal stress. We described that δ is a potential parameter to monitor a dynamic reservoir where stress changes are related with production, injection, and compaction. For unconventional reservoirs, we established a link between Thomsen's delta and tectonic strains. We showed that in the absence of a layer anisotropy parameter, tectonic stress and the anisotropy gradient can be calculated from the upper bound and lower bound of Thomsen's δ. We used the anisotropy gradient to describe fracture density and tectonic stress to define whether fractures are open or closed. Hence, combining the anisotropy gradient with tectonic stress can be used to define the optimal conditions for hydraulic fracturing for unconventional reservoir characterization.
The objective of this study is to demonstrate the effect of Thomsen's delta (δ) on stress anisotropy in complex hydrocarbon reservoirs. Based on Thomsen's δ, we provided the relationship between vertical and horizontal stress for orthorhombic media:
where, σh is the minimum horizontal stress, σH is the maximum horizontal stress, δh minimum value of Thomsen's delta and δH maximum value of Thomsen delta,
For transversely isotropic (TI) media, δH=δh, equation (1) becomes (Thomsen, 1986):
As indicated by Thomsen's landmark paper on seismic anisotropy (Thomsen, 1986),
where, εh is the minimum shear strain and?εH is the maximum shear strain, E is the Young's modulus.
Reliable facies prediction is a key problem in reservoir characterization. Facies classification using an arbitrary selected zone is the simplest method. However, the problem is that the interpretation result strongly depends on the size of the selected zone. Using an RPT (rock physics template), we can define an accurate zone instead of defining an arbitrarily sharp cutoff for the zone. The next level of sophistication is using a statistical technique, whereby we can calculate not only the best zone, but also the probability of occurrence of that zone. Baye’s theory is normally used for probabilistic facies classification. However, the prior belief is a fundamental part of Bayesian statistics. The posterior probabilities are heavily influenced by the prior probabilities, so any error caused by the interpretation of the prior probability will be amplified in the posterior probability. The objective of this study is to improve the prior probability predictions using rock physics analysis for quantitative facies classification. We use an RPT as a guidance to define these prior probabilities. For seismic reservoir characterization, well data along with rock physics theory via RPT are used to define the prior probability. We found that Baye’s prediction increases as we define the prior probabilities from the RPT.
Reliable facies prediction is a key problem in reservoir characterization. For reservoir facies characterization, three different methods are normally used (Figure 1a, 1b, 1c). We combined method 2 (Figure 1b) and Method 3 (Figure 1c) to improve facies classification for quantitative seismic interpretation (Figure 1d). Facies classification using an arbitrarily selected zone is the simplest method (Figure 1a). However, the problem is that interpretation results strongly depend on the size of the selected zone. Using an RPT, we can define an accurate zone instead of defining an arbitrary sharp cutoff for the zone (Figure 1b). Using a statistical technique (Figure 1b), we can calculate not only the best zone, but also the probability of occurrence of that zone. Bayes’ theory is normally used for probabilistic facies classification. This theory primarily involves a prior to posterior updating technique. Mathematically Bayes’ theory is given by (Stigler, 1983):
Analysis of electrically anisotropic reservoirs has been challenging with traditional petrophysical analysis. Several techniques were proposed as a framework for using graphical cross-plots to evaluate shaly-sand reservoirs. However, there has never been a clear workflow to define shale laminations and shale anisotropy. In this study, we incorporate a depth-dependent Thomas-Stieber model to describe the shale laminations. From the vertical and horizontal resistivity, an electrical anisotropy template was built in conjunction with the modified Thomas-Stieber model. The template generated assuming isotropic shale underestimated the hydrocarbon volume. However, the template generated treating the shale as anisotropic improved the estimations of hydrocarbon presence, permitting a global assessment of the hydrocarbon potential of the shaly-sand reservoirs. Using the depth-dependent Thomas-Stieber model we showed that electrical anisotropy is a function of shale laminations as well as shale compaction. Our electrical anisotropy template enhanced the accuracy of hydrocarbon identification in the anisotropic reservoir and permitted identification of more pay zones from vertical and horizontal resistivity data.
Summary The objective of this study is to experimentally and theoretically revise the relations between porosity, permeability, and elastic wave velocity of diagenetic sandstone. Many such relationships exist in the literature, however, they do not consider diagenetic effects. We found clean sandstone can be modeled with Kozeny's relation; however it breaks down for clay-bearing sandstones and diagenetically-altered sandstones. Porosity is the first order parameter that affects permeability and elastic properties; clay and cement cause secondary effects on these properties.Combining theoretical models with laboratory measured data, we have derived mathematical relationships for porosity-permeability, porosity-velocity and permeability-velocity in diagenetic sandstone. The effects of clay and cementation are described using coefficients introduced into these relationships.
The objective of this study is to describe the inequalities of anisotropic rock physics. Anisotropic rock physics provides the link between seismic anisotropy and anisotropic properties of rocks. However, the limitations of anisotropic rock physics predictions and measurements are not well understood. In this study we provided rock physics inequalities as guidelines to check the validities of anisotropic rock physics predictions and lab measurements. Initially we used Rudzki’s inequalities for TI media; then we provided proof of concept of these inequalities as well as extended these inequalities for isotropic media. In addition, we verified these inequalities using published moduli of isotropic crystals, and finally we used these inequalities to check the qualitiy of rock physics predictions and measurements. For spherical pore structure where isotropic self-consistent (SC) rock physics approximations are equal to the anisotropic SC rock physics approximations, inequalities satisfy the rock physics predictions for porosity up-to 60%. With increasing the complexity of pore structure where isotropic rock physics approximations are not equal to anisotropic rock physics approximations, rock physics inequalities describe that part of the anisotropic SC rock physics prediction are not valid for transversely isotropic media. We found these invalid predictions are associated with a higher anisotropic constant. Laboratory measured anisotropic velocity data which have a lower anisotropic constant (less than 0.6) satisfy theses inequalities. However, measured results for clay minerals (e.g. illite and kaolinite) which have a higher anisotropic constant (above 0.6) do not satisfy these inequalities. We concluded these unsatisfied anisotropic rock physics predictions and measurements should be treated as higher anisotropic media (orthorhombic, monoclinic) than transversely isotropic media.
The objective of this study is to estimate the amount of cement from Rock Physics Diagnostic (RPD). Rock Physics Diagnostic is widely used to describe the useful relation between seismic velocity and porosity, which is consistence with local geology, e.g. diagenetic pore- filling cement and contact cements. Rock physics studies indicate that quantitative cement substitution is as important as fluid substitution to understand the difference between the hydrocarbon effect and the cementation effect from seismic data. Cement quantification is also important to understand the fluid flow and mechanical strength of reservoir rocks. We offer a new method to quantify the amount of contact and non-contact cement by using RPD analysis. Our cement quantification method combines soft-sand, stiff-sand and intermediate-stiff-sand models and is a physical based approach to quantify the amount of contact and non-contact cement. By using these rock-physics models, we examine the relationship between elastic properties and porosity in laboratory data and link rock-physics properties to diagenesis to quantify the amount of cement. Pore-filling berthierine cements determined from thin section analyses agree well with non-contact cement determined from RPD analysis. The amount of contact cements determined from RPD analysis also agrees well with the amount of quartz cement determined from thin section analyses. This new approach can be used to quantify the amount of non-contact and contact cement from seismic properties.
CO2 capture and storage (CCS) is a technique to reduce CO2 emission, and CO2 is also used in EOR (enhanced oil recovery). It may increase oil production by 15-25% from an oil field. In this paper we present how to deal with the seismic response due to CO2 injection. To understand the seismic response due to CO2 flooding requires knowledge of the distribution of CO2 in brine, viscous loss due to CO2 and dissolution of CO2 in brine. Furthermore, the basic principle for EOR methods by CO2 is that high solubility of CO2 increases the density and lowers the viscosity at reservoir conditions of the oil, thus improving the oil mobility and the efficiency of water flooding. However, the viscous losses during the fluid flow are responsible for seismic wave attenuation. Moreover, when injecting CO2 into the water-saturated sample, some CO2 may be dissolved in the water. The Gassmann and Reuss or Gassmann and Voigt method may be used to calculate CO2 saturated seismic properties. Considering the significant differences between velocity values in these two methods, a large uncertainty is associated with fluid-saturation estimation from seismic data. I provided the rock physics model to calculate the CO2 saturated seismic properties to understand the seismic response due to the CO2 flooding. This model was tested laboratory measured data of sandstone from Lei and Xueb (2009) and carbonate from Wang et al. 1998. Modeling results provided us the viscous loss and dissolution of CO2 effects to calculate the CO2 saturated seismic properties. This model may be also used to calculate the accurate hydrocarbon production during the EOR method by CO2 injection.