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.
Carbonate formations are very complex in their pore structure and exhibit a wide variety of pore classes. Pore classes such as interparticle porosity, moldic porosity, vuggy porosity, intercrystalline porosity, and microporosity. Understanding the role of pore class on the performance of emulsified acid treatment and characterizing the physics of the flow inside is the objective of our study.
The study was performed using vuggy dolomite cores that represent mainly the vuggy porosity dominated structure, while the homogenous cores represent the intercrystalline pore structure. Core flood runs were conducted on 6 x 1.5 in. cores using emulsified acid formulated at 1 vol% emulsifier and 0.7 acid volume fraction. The objective of this set of experiments is to determine the acid pore volume to breakthrough for each carbonate pore class at different injection rates.
In this paper, a novel approach to interpret the core flood run results using thin section observations, tracer experiments, SEM, and resistivity measurements will be presented. Thin section observations provide means to study the vugs size and their distribution, connectivity, and explain the contribution of the pore class in the acid propagation. Relating the rotating disk experiments of emulsified acid with dolomite to our core flood run results will be also conducted in order.
The acid pore volumes to breakthrough for vuggy porosity dominated rocks were observed to be much lower than that for homogenous carbonates (intercrystalline pore structure). Also, the wormhole dissolution pattern was found to be significantly different in vuggy rocks than that in homogenous ones. Comparison of thin section observations, tracer results and the core flood runs results indicates that the vugs are distributed in a manner that creates a preferential flow path which can cause a rapid acid breakthrough and effective wormholing than those with a uniform pore structure. Rotating disk experiment results, demonstrating that the reaction of emulsified acid with dolomite is much lower than that with calcite, showed that the reaction kinetics played a role in determining the wormhole pattern.
Mishra, Prasanta Kumar (Kuwait Oil Company) | Al-Harthy, Abdulrahman (Target Oilfields Services) | Al-Kanderi, Jasem M. (Kuwait Oil Company) | Al-Raisi, Muatasam (Target Oilfields Services) | Al-Alawi, Ghaliah (Target Oilfields Services) | Alhashmi, Salim (Target Oilfields Services) | Turkey, Shaikha (Kuwait Oil Company)
This paper presents the main steps of rock-typing workflow and the technique applied to estimate permeability.
Reservoir rock typing (RRT) is a process of up-scaling detailed geological and petrophysical information to provide more accurate input for 3D geological and flow simulation models. The reservoir rocks that correspond to a particular rock type should have similar rock fabric, pore types and pore throat size distribution. The study integrated multi-scale data types to develop a robust and predictable rock type scheme. This consists of detailed sedimentological description of depositional environment and associated sedimentary features, detailed numerical petrographic analysis of rock texture, grain types, porosity types and rock mineralogy and petrophysical data grouping using openhole log and core plugs porosity-permeability relationship and pore throat size distribution (MICP).
The main objective was to develop a reliable reservoir rock type scheme that captures the heterogeneity in Jurassic carbonate reservoir for the Middle Marrat Formation in South East Kuwait area and implementation of the RRT to the permeability prediction within the field. Integration of the thin sections, porosity-permeability, pore throat size and distribution has resulted in the identification of reservoir rock types. A total of 14 different rock types were identified within the reservoir interval in the cored wells, which is subsequently grouped into eight due to modelling limitation. The RRT up-scaling was done in a way to minimize the impact of grouping on permeability and saturation computations. The prediction success between the cored RRT and the predicted RRT using openhole data is more than 85%. As a result, the permeability computation success between core plugs and computed permeability using the RRT is more than 80%.
Facies modeling forms an integral part of geological numerical modeling. Over the last two decades, different facies modeling methods have been developed using geostatistical algorithms. Most of these methods rely on the assumption of discrete or binary modeling during which each model cell is assigned a single facies. In this study, the size of the cells is on average 100 meters by 100 meters laterally by one meter thick. Based on comparisons to outcrops and subsurface data, such cells should, in fact, include a mixture of facies.
The discrete-facies approach assumes a single facies per cell. The distribution of the facies between wells is described using classical categorical geostatistical algorithms. Reservoir properties are then populated by facies within mapped environments of deposition. This process is well-established and straightforward, especially with regard to tying well data, handling property trends, and applying net rock cut-offs.
A mixed-facies approach can be performed using effective property modeling in which multiple small, fine-scale models are built for each environment of deposition. These models are re-sampled to the full-field cell volume using static and flow-based upscaling methods. The resulting statistics are then used with geostatistics, conditioned to the proportion of each facies present, to populate the full-field model. Such models allow the incorporation of core-scale heterogeneity potentially important in improved oil recovery projects, and may reduce modeling cycle times, especially when multiple iterations are required, such as during history-matching or uncertainty analysis.
This paper compares the impact on simulated fluid flow of modeling facies using discrete modeling versus a mix of facies per cell. Shoreface and subordinate fluvial environments of deposition facies, and five reservoir lithofacies, were modeled.
Fluid-flow simulation of the mixed-facies model, under both primary depletion and pressure maintenance conditions, was smooth and uniform, with a highly conformable flood front. The discrete model was more stratified, with faster and less conformable water movement.
The assignment of discrete facies to large model cells (few hundred meters laterally & few meters vertically) takes less time than a mixed-facies approach and does a better job of preserving organized extremes of permeability important at the production timescale. In the early stages of field development, when there is much uncertainty and a rapid, scenario-based modeling approach is desirable, the discrete approach can be used to flag heterogeneity-related risks more quickly and confidently than the mixed-facies technique. Inaccuracies in performance parameters resulting from the assignment of unscaled discrete values can be corrected using fine-scale sector models tailored to the highest risk cases.
The Middle Minagish Oolite Formation is 450 to 550 feet thick interval of porous limestone reservoir, composed of peloidal/skeletal grainstones with lesser amount of packstone, oolitic grainstone, wackstone and mudstone in Umm Gudair field, West Kuwait. It is characterized by small scale reservoir heterogeneity, primarily related to the depositional as well as diagenetic features. Capturing reservoir properties in micro scale and its spatial variation needs special attention in this reservoir due to its inherent anisotropy. Reservoir properties will depend on the level that we are analyzing on reservoir (millimeter to meter scale). Here we used Electrical Borehole Image (EBI) and Nuclear Magnetic Resonance (NMR) to capture small scale feature of Umm Gudair carbonate reservoir and compared them with core data
In present work, reservoir properties (including texture, facies, porosity and permeability) interpreted by the EBI shows good match with NMR driven properties and core data. Textural changes in image logs also match well with pore size distribution from NMR logs. Further highly porous zones which are considered either due to primary porosity or vugs match with larger pores of NMR logs and these corroborates with also core derived porosity. A good match has been observed between EBI, NMR and cored derived porosity. Permeability calculations have also been made and compared with core data. A detail workflow has been developed here to interpret reservoir properties on un-cored wells, where only low vertical resolution data is available. This technique is quite useful to identify the characters and mode of origin highly porous zones in reservoir section which are generally not identifiable by low resolution standard logs. This workflow will allow us to interpret the heterogeneity at high resolution level in un-cored wells, as results are validated with integration of EBI, NMR and core data.
The matrix blocks in fractured reservoirs are the primary storage of hydrocarbons, so matrix-fracture transfer mechanisms are of crucial importance in recovery from fractured reservoirs. During gas injection into fractured reservoirs, fractures are filled with injected gas while matrix blocks contain the reservoir fluid. In this condition due to compositional difference between the gas in fractures and the fluid in matrix, diffusive exchanges of components between matrix and fracture may have significant contribution on matrix oil recovery in addition to gravity drainage or other transfer mechanisms.
In this work, to evaluate the significance of molecular diffusion, the laboratory experiment of "Gas Injection into Fractured cores?? is simulated using a compositional model and this model is used to run several experiments which help in understanding the way that each recovery mechanism acts. The advantage of running simulation in core scale is that in this way there is the possibility of using small grid size which significantly reduces the issues of numerical dispersion. And more over the existing experimental data can be used for model adjustment. In the experimental works the procedure is to place a core sample into a core holder in such a way that the annulus space between the core boundary and the core holder is very small. This annulus space is representative of the fracture surrounding the matrix blocks in the reservoir. Then after using special techniques the core is saturated with the representative reservoir oil, and after this primary core initialization, gas is injected into the annulus and the amount of recovered oil is measured versus time.
This study reveals that, molecular diffusion acts like a catalyst and improves the recovery mechanism by enhancing the gas movement within matrix. At the prevalent conditions of this work, the main recovery mechanisms are the miscibility effects (Condensing or Vaporizing gas drives) that are enhanced by molecular diffusion. Sensitivity analysis done in this work reveals that significance and contribution of molecular diffusion in recovery changes with different parameters such as matrix permeability and porosity, gas composition, etc.
Fractured reservoirs contain a significant portion of the world's reserves, and Gas injection is a common recovery practice in these reservoirs and understanding the recovery mechanisms is of crucial importance for correct simulation of this process. This study shows, although significance of molecular diffusion changes with reservoir parameters, any way neglecting it in simulation studies will result in underestimation of gas injection efficiency.
This paper presents a method for determining the Archie saturation exponent, n, from a single, nonequilibrium centrifuge step. The input measurements include detailed 3D saturation distributions from magnetic resonance imaging and the DC conductivity of the sample under examination. The latter is obtained by making use of a patented 4-contact cell. The sample is modeled as a 3D conductivity network and a specially developed algorithm based on random walk (RW) is used to compute its overall conductivity in a very short time. The value of the n exponent is determined by matching the measured conductivity to the calculated one. The entire analysis takes one day. Examples demonstrate the method and details of the impedance cell and the RW algorithm are provided.
Glegola, Marcin A. (Delft University of Technology) | Ditmar, Pavel (Delft University of Technology) | Hanea, Remus (TNO) | Eiken, Ola (Statoil) | Vossepoel, Femke C. (Shell International Exploration and Production B.V.) | Arts, Rob (TNO) | Klees, Roland (Delft University of Technology)
Water influx is an important factor influencing production of gas reservoirs with an active aquifer. However, aquifer properties such as size, porosity, and permeability are typically uncertain and make predictions of field performance challenging. The observed pressure decline is inherently nonunique with respect to water influx, and large uncertainties in the actual reservoir state are common. Time-lapse (4D) gravimetry, which is a direct measure of a subsurface mass redistribution, has the potential to provide valuable information in this context.
Recent improvements in instrumentation and data-acquisition and -processing procedures have made time-lapse gravimetry a mature monitoring technique, both for land and offshore applications. However, despite an increasing number of gas fields in which gravimetric monitoring has been applied, little has been published on the added value of gravity data in a broader context of modern reservoir management on the basis of the closed-loop concept. The way in which gravity data can contribute to improved reservoir characterization, production-forecast accuracy, and hydrocarbon-reserves estimation is still to be addressed in many respects.
In this paper, we investigate the added value of gravimetric observations for gasfield-production monitoring and aquifer-support estimation. We perform a numerical study with a realistic 3D gasfield model that contains a large and complex aquifer system. The aquifer support and other reservoir parameters (i.e., porosity, permeability, reservoir top and bottom horizons) are estimated simultaneously using the ensemble smoother (ES). We consider three cases in which gravity only is assimilated, pressure only is assimilated, and gravity and pressure data are assimilated jointly. We show that a combined estimation of the aquifer support with the permeability field, porosity field, and reservoir structure is a very challenging and nonunique history-matching problem, in which gravity certainly has an added value. Pressure data alone may not discriminate between different reservoir scenarios. Combining pressure and gravity data may help to reduce the nonuniqueness problem and provide not only an improved gas- and water-production forecast and gas-in-place evaluation, but also a more-accurate reservoir-state description.
On the basis of micro- and mesoscale investigations, a new mathematical formulation is introduced in detail to investigate multiscale gas-transport phenomena in organic-rich-shale core samples. The formulation includes dual-porosity continua, where shale permeability is associated with inorganic matrix with relatively large irregularly shaped pores and fractures, whereas molecular phenomena (diffusive transport and nonlinear sorption) are associated with the kerogen pores. Kerogen is considered a nanoporous organic material finely dispersed within the inorganic matrix. The formulation is used to model and history match gas-permeation measurements in the laboratory using shale core plugs under confining stress. The results indicate significance of molecular transport and strong transient effects caused by gas/solid interactions within the kerogen. In the second part of the paper, we present a novel multiscale perturbation approach to quantify the overall impact of local porosity fluctuations associated with a spatially nonuniform kerogen distribution on the adsorption and transport in shale gas reservoirs. Adopting weak-noise and mean-field approximation, the approach applies a stochastic upscaling technique to the mathematical formulation developed in the first part for the laboratory. It allows us to investigate local kerogenheterogeneity effects in spectral (Fourier-Laplace) domain and to obtain an upscaled "macroscopic" model, which consists of the local heterogeneity effects in the real time-space domain. The new upscaled formulation is compared numerically with the previous homogeneous case using finite-difference approximations to initial/boundary value problems simulating the matrix gas release. We show that macrotransport and macrokinetics effects of kerogen heterogeneity are nontrivial and affect cumulative gas recovery. The work is important and timely for development of new-generation shale-gas reservoir-flow simulators, and it can be used in the laboratory for organic-rich gas-shale characterization.
Permeability provides a measure of the ability of a porous medium to transmit fluid and is significant in evaluating reservoir productivity. A case study that compares different methods of permeability prediction in a complex carbonate reservoir is presented in this paper. Presence of siliciclastic fines and diagenetic minerals (e.g., dolomite) within carbonate breccias has resulted in a tight and heterogeneous carbonate reservoir in this case. Permeability estimations from different methods are discussed and compared. In the first part of the paper, permeability measurements from conventional core analysis (CCAL), mercury-injection capillary pressure (MICP) tests, modular formation dynamic tests (MDTs), and nuclear-magnetic-resonance (NMR) logs are discussed. Different combinations of methods can be helpful in permeability calculation, but depending on the nature and scale of each method, permeability assessment in heterogeneous reservoirs is a considerable challenge. Among these methods, the NMR log provides the most continuous permeability prediction. In the second part of the paper, the measured individual permeabilities are combined and calibrated with the NMR-derived permeability. The conventional NMR-based free-fluid (Timur-Coates) model is used to compute the permeability. The NMRestimated permeability is influenced by wettability effects, presence of isolated pores, and residual oil in the invaded zone. new modified Timur-Coates model is established on the basis of fluid saturations and isolated pore volumes (PV) of the rock. This model yields a reasonable correlation with the scaled core-derived permeabilities. However, because of the reservoir heterogeneity, particularly in the brecciated intervals, discrepancies between the core data and the modified permeability model are expected.