Cinar, Yildiray (The University of New South Wales) | Arns, Christoph (The University of New South Wales) | Dehghan Khalili, Ahmad (The University of New South Wales) | Yanici, Sefer (The University of New South Wales)
Resistivity measurements play a key role in hydrocarbon in place calculations for oil and gas reservoirs. They are a direct indi-cator of fluid saturation and connected pore space available in the formation. Carbonate rocks, which host around half of the world's hydrocarbons, exhibit a wide range of porosities with scales spanning from nanometres to centimetres. The often sig-nificant amount of microporosity displayed by Carbonate rocks emphasizes the necessity of an adequate characterization of their micro-features and their contribution to hydrocarbon in place. In this paper we examine upscaling methods to probe for-mation factor of a fully saturated carbonate sample using an X-ray CT based numerical approach and compare to experimental measurements.
Three-dimensional high-resolution X-ray CT enables the numerical calculation of petrophysical properties of interest at the pore scale with resolutions down to a few microns per voxel. For more complex and heterogeneous samples however, a direct calculation of petrophysical properties is not feasible, since the required resolution and a sufficient field of view cannot be obtained simultaneously. Thus an integration of measurements at different scale is required. In this study a carbonate sample of 38mm in diameter is first scanned using the X-ray CT method with a resolution of 26µm. After accompanying experimental measurements on the full plug, four 5mm plugs were drilled vertically from this sample and X-ray CT images of these plugs acquired at resolutions down to 2.74 µm. We calculate the porosity of the sample (macro- and micro-porosities) using the phase separation methods and then predict the formation factor of the sample at several scales using a Laplace solver. The formation factor is calculated by using a general value of m=2 as cementation factor for intermediate porosity voxels. We compare to experimental measurements of formation factor and porosity both at the small plug and full plug scale and find good agreement.
To assess the degree of uncertainty of the numerical estimate, we probe the extent of heterogeneity by investigating the size of a representative elementary volume (REV) for formation factor. We find that for the considered heterogeneous carbonate sam-ple, formation factor varies considerably over intervals less than a centimetre. Our results show that this variation could be explained by different cementation exponents applied at the micro-voxel scale, with the exemption of one plug, for which the cementation exponent would have to be unreasonably low. These cementation factors are derived by direct comparison be-tween numerical simulation and experiment. We conclude that for one plug an error in experimental measurement might have occurred. The numerical approach presented here therefore aids in quality control. Excluding this plug in the upscaling proce-dure improves the agreement with the experimental result for the whole core while still underestimating formation factor. Al-lowing for a constant m=2 in the simulation at the small scale and using directly the resulting relationship between porosity and formation factor in the upscaling process leads to an overestimation of formation factor.
Kumar, Munish (Research School of Physics and Engineering, Australian National University) | Sok, Rob (Research School of Physics and Engineering, Australian National University) | Knackstedt, Mark A. (Research School of Physics and Engineering, Australian National University) | Latham, Shane (Research School of Physics and Engineering, Australian National University) | Senden, Tim J. (Research School of Physics and Engineering, Australian National University) | Sheppard, Adrian P. (Research School of Physics and Engineering, Australian National University) | Varslot, Trond (Research School of Physics and Engineering, Australian National University) | Arns, Christoph (School of Petroleum Engineering, University of New South Wales)
Kumar, Munish (Australian National University, Canberra) | Sok, Rob (Australian National University, Canberra) | Knackstedt, Mark A. (Australian National University, Canberra) | Latham, Shane (Australian National University, Canberra) | Senden, Tim J. (Australian National University, Canberra) | Sheppard, Adrian P. (Australian National University, Canberra) | Varslot, Trond (Australian National University, Canberra) | Arns, Christoph (School of Petroleum Engineering, University of New South Wales, Sydney, Australia)
Complexities in pore scale structure, rock-fluid and fluid-fluid interactions have a profound effect on the estimation of reserves, reservoir recovery and productivity in reservoir core material. These complexities determine the pore scale distribution of fluids within the pore space, which, in turn, determine the petrophysical response of the rock. A very important example is the estimation of water saturation via resistivity measurements. Default saturation exponents (n=2) are often used in estimating saturations despite numerous measurements which have shown that n can depend strongly on the rock type, mineralogy, saturation history and wettability. Non- Archie behavior is reported frequently. Experimental laboratory results for the resistivity response of clastic and carbonate reservoir cores under varying wettability states have exhibited a range of saturation exponents; 1
Understanding the resistivity response of reservoir cores requires an ability to accurately map the pore scale structure and the fluid distributions in 3D within core material under variable wettability states and based on different saturation history. We use an image registration technique which allows voxel perfect overlays of 3D tomographic images of the same core sample at varying saturation states. The method allows one to explicitly visualize the experimental two-phase fluid distributions within reservoir core material at the pore scale. The ability to perform multiple experiments on the same core and to accurately compare their fluid distributions at the pore scale allows one to probe the (potentially competing) roles of complex rock structure, rock type, wettability and saturation history on the resistivity response.
Reasons for non-Archie behavior can be explained from the direct visualization of pore scale fluid distributions. This understanding can lead to more accurate predictions of in-situ fluid saturations within reservoir core. The technique can also be applied to the prediction of other petrophysical and multiphase flow properties (e.g., recoveries, relative permeability).
One of the most widely used techniques to evaluate hydrocarbon saturation in a petroleum reservoir is based on electrical logging. Standard methods in clay free reservoirs are based on the Archie saturation equation: RI = Rt/R0=Sw-n where RI is the resistivity index, Rt is the resistivity of the sample at brine saturation Sw and R0 is the resistivity of the sample at 100% saturation. n, the Archie saturation exponent, is an empirical parameter which is best determined by experimental core analysis. One problem in petrophysics is how to carry out a meaningful evaluation of saturation when core analysis data is unavailable or is insufficient to ground truth the interpretation satisfactorily. Saturation exponent measurements are very time consuming, expensive and vulnerable to many factors. Default estimations of the saturation exponents (n=2) are often used despite numerous measurements which have shown that n can depend strongly on the rock type, pore morphology, mineralogy and wettability.
Bächle, Gregor (University of Miami) | Eberli, Gregor (University of Miami) | Madadi, Mahyar (Australian National University) | Sok, Rob (Australian National University) | Knackstedt, Mark A. (Australian National University) | Arns, Christoph (Australian National University) | Latham, Shane (Australian National University) | Sheppard, Adrian P. (Australian National University)
Knackstedt, Mark (Australian National University) | Sheppard, Adrian (Australian National University) | Nguyen, Viet (Univ. of NSW) | Arns, Christoph (Australian National University) | Sok, Rob (Australian National University)
Copyright 2006, held jointly by the Society of Petrophysicists and Well Log Analysts (SPWLA) and the submitting authors. Annual Logging Symposium held in Veracruz, Mexico, June 4-7, 2006. ABSTRACT The ability of a rock to store and flow fluids is dependent upon the pore volume, pore geometry and its connectivity. Carbonate rocks are inherently heterogeneous having been laid down in a range of depositional environments and having undergone significant diagenesis. They are particularly difficult to characterise as the pore sizes can vary over orders of magnitudes and connectivity of pores of different scales can impact greatly on flow properties. For example, separate vuggy porosity in a underlying matrix pore system can increase the porosity, but not the permeability and lead to large residual oil saturations due to trapping in vugs. A touching vug network can have a dramatic effect on permeability and lead to higher recoveries. The morphology of the pore space from different core material exhibits a broad range of topology and connectivity. Images at lower resolution (larger sample size) allow one to deduce the size, shape and spatial distribution of the (disconnected) vuggy porosity. Higher resolution images (down to 2 micron resolution) on subsets of the core allow one to probe the 3D intergranular porosity. The delineation of regions with submicron porosity is achieved via a differential contrast technique in the µCT. Experimental MICP measurements performed on the imaged core material are in good agreement with image-based MICP simulations.
NMR is a popular logging technique used to estimate pore size information,formation permeability, wettability and irreducible water saturation.Quantitative interpretation of NMR data is based on a set of fundamentalassumptions (e.g., pore isolation and fast diffusion. These assumptionsestablish the quantitative link between NMR response and petrophysicalpredictions. While there is a need to test these assumptions directly,to date no quantitative study on reservoir core materialhas been undertaken. The ability to digitally image reservoirrock in 3D, calculate petrophysical properties directly from the imagescoupled with a comprehensive simulation tool to numerically generatea range of NMR response data may help to address this need.
In this paper we image a large set of reservoir cores including sandstonesand carbonates at the pore scale using high resolution micro-CT. A set ofpetrophysical properties are measured directly on the cores includingsurface-to-volume, permeability and pore size distribution. Thepermeabilities of the cores range from 10 mD to several Darcies.Realistic multiphase fluid distributions are derived by simulationof drainage.We then simulate the NMR responses on the same core images using acomprehensive NMR simulator.The internal magnetic fieldis derived numerically from applied magnetic fields and susceptibilitydistributions and the phase evolution of the magnetic spinscalculated with a random walk method. NMR responses currentlyinclude inversion recovery (T1 and CPMG (T2, and thelongitudinal and transversal signals aremonitored simultaneously. The interpretation of the signals acquired isdone by standard 1D Laplace inversion to calculate the pore sizedistribution from T2 responses, and with a 2D inverse Laplacetransform for fluid typing.
In a preliminary study we compare predictions of petrophysicalproperties from the interpretation of the NMR response to directcalculations on the images. The foundational assumption of pore isolationis directly tested by partitioning of the pore space.This allows one to calculate the coupling constants and magnetisationexchange between pores, or between macro- and micro-porous regions.Further, the sensitivity of the responses to variations in relaxivitiesor the presence of magnetic impurities is studied. Fluid typing isperformed on a shaly sandstone sample.