Investigation of the permeability of carbonate rocks is essential and challenging due to the heterogeneity of carbonates at all scales. At the micro-scale, pore geometry, pore size distribution, and pore connectivity are important factors controlling permeability. This study focuses on the influence of pore size distribution and pore structure on permeability to better understand the fluid flow in carbonate rocks.
In this paper, we use micro-computer tomography (micro-CT) to capture the microscopic heterogeneity in the pore structure. Firstly, we collected seven 1 x 6 inch carbonate rock samples including Indiana Limestone, Desert Rose, and Travertine with various porosities and permeabilities. The porosity was measured gravimetrically, and permeability was measured with core plug flooding experiments. Cubic centimeter size core samples were scanned with enhanced micro-CT imaging with the resolution of 6-8 μm/voxel, then scanned 2D images were processed with image processing software to distinguish the pore system from the matrix. The pore size distribution for each rock sample was determined by fitting a statistical function based on the binarized images. We defined a concept of equivalent pore radius to characterize the pore system, which effectively filters out the non-contributing small pores and preserves the pores actually contributing to fluid flow. The relationship between the equivalent pore radius of each rock and permeability was investigated. Based on the 2D image stack, we also constructed the 3D pore network to observe the pore structure, quantify connectivity and specific surface ratio to study their influence on permeability.
We found that laboratory measured permeability from core plugs was strongly correlated to the equivalent pore radius calculated from micro-CT scanned images among the investigated carbonate rock samples. The semilogarithmic correlation between permeability and effective pore radius fit the measured permeability data very well over a permeability range of more than two orders of magnitude. The findings of pore-scale pore structure and pore size distribution in this study are helpful for carbonate rock analysis, and the proposed new correlation between equivalent pore radius and permeability is practical for permeability estimation for a wide range of carbonate rocks.
Copyright 2019 held jointly by the Society of Petrophysicists and Well Log Analysts (SPWLA) and the submitting authors. ABSTRACT Today, many machine learning techniques are regularly employed in petrophysical modelling such as cluster analysis, neural networks, fuzzy logic, self-organising maps, genetic algorithm, principal component analysis etc. While each of these methods has its strengths and weaknesses, one of the challenges to most of the existing techniques is how to best handle the variety of dynamic ranges present in petrophysical input data. Mixing input data with logarithmic variation (such as resistivity) and linear variation (such as gamma ray) while effectively balancing the weight of each variable can be particularly difficult to manage. DTA is conceived based on extensive research conducted in the field of CFD (Computational Fluid Dynamics). This paper is focused on the application of DTA to petrophysics and its fundamental distinction from various other statistical methods adopted in the industry. Case studies are shown, predicting porosity and permeability for a variety of scenarios using the DTA method and other techniques. The results from the various methods are compared, and the robustness of DTA is illustrated. The example datasets are drawn from public databases within the Norwegian and Dutch sectors of the North Sea, and Western Australia, some of which have a rich set of input data including logs, core, and reservoir characterisation from which to build a model, while others have relatively sparse data available allowing for an analysis of the effectiveness of the method when both rich and poor training data are available. The paper concludes with recommendations on the best way to use DTA in real-time to predict porosity and permeability. INTRODUCTION The seismic shift in the data analytics landscape after the Macondo disaster has produced intensive focus on the accuracy and precision of prediction of pore pressure and petrophysical parameters.
Relative permeability (kr) functions are among the essential data required for the simulation of multiphase flow in hydrocarbon reservoirs. These functions can be measured in the laboratory using different techniques including the steady state displacement technique. However, relative permeability measurement of shale rocks is extremely difficult mainly because of the low/ultralow matrix permeability and porosity, dominant capillary pressure and stress-dependent permeability of these formations.
In this study, the impacts of stress and capillary end effects (CEE) on the measured relative permeability data were investigated. The steady state relative permeability (SS-kr) measurements were performed on Eagle Ford and Pierre shale samples. To overcome the difficulties regarding the kr measurements of shale rocks, a special setup equipped with a high-pressure visual separator (with an accuracy of 0.07 cc) was used. The kr data were measured at different total injection rates and liquid gas ratios (LGR). In addition, to evaluate the impacts of effective stress, the kr data of an Eagle Ford shale sample were measured at two different effective stresses of 1000 and 3000 psi.
From the experimental data, it was observed that the measured SS-kr data of the shale samples have been influenced by the capillary end effects as the data showed significant variation when measured at different injection rates (with the same LGR). This suggested that the liquid hold-up (i.e. capillary end effects) depends on the competition of capillary and viscous forces. In addition, it was shown that it is more necessary to correct the experimental kr data measured at the lower LGRs. Furthermore, different relative permeability curves were obtained when the kr data were measured at different effective stresses. This behavior was explained as the capillary pressure was expected to be more dominant at the higher effective stress.
The results from this study improve our understanding of unconventional mechanisms in shale reservoirs. It is evident that the behavior of unconventional reservoirs can be better predicted when more reliable and accurate relative permeability data are available. The outcomes of this study will be useful for accurate determination of such kr data.
Bagheri, Mohammadreza (Research Centre for Fluid and Complex Systems, Coventry University) | Shariatipour, Seyed M. (Research Centre for Fluid and Complex Systems, Coventry University) | Ganjian, Eshmaiel (School of Energy, Construction and Environment, Built & Natural Environment Research Centre, Coventry University)
The fluid pressure, the stress due to the column of the cement in the annulus of oil and gas wells, and the radial pressure exerted on the cement sheath from the surrounding geological layers all affect the integrity of the cement sheath. This paper studies the impact of CO2-bearing fluids, coupled with the geomechanical alterations within the cement matrix on its integrity. These geochemical and geomechanical alterations within the cement matrix have been coupled to determine the cement lifespan. Two main scenarios including radial cracking and radial compaction, were assumed in order to investigate the behaviour of the cement matrix exposed to CO2-bearing fluids over long periods. If the radial pressure from the surrounding rocks on the cement matrix overcomes the strength of the degraded layers within the cement matrix, cement failure can be postponed, while on the other hand, high vertical stress on the cement matrix in the absence of a proper radial pressure can lead to a reduction in the cement lifespan. The radial cracking process generates local areas of high permeability around the outer face of the cement sheath. Our simulation results show at the shallower depths the cement matrices resist CO2-bearing fluids more and this delays exponentially the travel time of CO2-bearing fluids towards the Earth's surface. This is based on the evolution of CO2 gas from the aqueous phase due to the reduction in the fluid pressure at shallower depths, and consumption of CO2 in the reactions which occur at the deeper locations.
An important aspect of reservoir management process is monitoring and revising plans and an essential component of reservoir management strategy is integration of technologies (Satter et al. 1994). In revisions of reservoir management plans, very rarely do operators incorporate any other data than the data from newly drilled wells and the field production in between the revisions. Any inference in the inter-well space is an interpolation between the well data, as surface seismic is limited by its resolution, as the calibration data is available only at well level. For an effective reservoir management, especially in the decline phase of the field, a logical integration of technologies to capture maximum heterogeneity in the interwell space can be very advantageous. Crosswell technologies, that provide high resolution data between a set of wells, but if used individually, are essentially limited to a very small part of the field having multiple wells. Therefore, in order to monitor and revise reservoir management plans, it is important that such technologies are integrated with full-field solutions. This paper describes a methodology that aims to better manage reservoir by logically integration the 3D reservoir model-a full-field solution-and crosswell electromagnetics/crosswell seismic-an interwell solution.
The significant oil reserves related to karst reservoirs in Brazilian pre-salt field adds new frontiers to the development of upscaling procedures to reduce time on numerical simulations. This work aims to represent karst reservoirs in reservoir simulators based on special connections between matrix and karst mediums, both modeled in different grid domains of a single porosity flow model. This representation intends to provide a good relationship between accuracy and simulation time.
The concept follows the Embedded Discrete Fracture Model (EDFM) developed by Moinfar, 2013; however, this work extends the approach for karst reservoirs (Embedded Discrete Karst Model - EDKM) by adding a representative volume through grid blocks to represent karst geometries and porosity. For the extension of EDFM approach in a karst reservoir, we adapt the methodology to four stages: (a) construction of a single porosity model with two grid domains, (b) geomodeling of karst and matrix properties for the corresponding grid domain, (c) application of special connections through the conventional reservoir simulator to represent the transmissibility between matrix and karst medium, (d) calculation of transmissibility between karst and matrix medium.
For a proper validation, we applied the EDKM methodology in a carbonate reservoir with mega-karst structures, which consists of non-well-connected enlarged conduits and above 300 mm of aperture. The reference model was a refined grid with karst features explicitly combined with matrix facies, including coquinas interbedded with mudstones and shales. The grid block of the reference model measures approximately 10 × 10 × 1 meters. For the simulation model, the matrix grid domain has a grid block size of approximately 100 × 100 × 5 meters. The karst grid domain had the same block size as the refined grid. Flow in the individual karst grid domain or matrix grid domain is governed by Darcy's equation, implicitly solved by simulator. However, the transmissibility for the special connections between karst and matrix blocks is calculated as a function of open area to flow, matrix permeability and block center distance. The matrix properties were upscaled through conventional analytical methods. The results show that EDKM had a considerable performance regarding a dynamic matching response with reference model, within a reduced simulation time while maintaining a higher dynamic resolution in the karst grid domain without using an unconstructed grid.
This work aims to contribute to the extension of EDFM approach for karst reservoirs, which can be applied to commercial finite-difference reservoir simulators and it presents itself as a solution to reduce simulation time without disregarding the explicit representation of karst features in structured grids.
The petro-elastic model (PEM) represents an integral component in the closed-loop calibration of integrated four-dimensional (4D) solutions incorporating time-lapse seismic, elastic and petrophysical rock property modeling, and reservoir simulation. Calibration of the reservoir simulation model is needed so that it is not only consistent with production history but also with the contemporaneous subsurface description as characterized by time-lapse seismic. The PEM requires dry rock properties in its description, which are typically derived from mechanical rock tests. In the absence of those mechanical tests, a small data challenge is posed, whereby all necessary data is not available but the value of reconciling seismic attributes to simulated production remains. A seismic inversion-constrained n-dimensional metaheuristic optimization technique is employed directly on three-dimensional (3D) geocellular arrays to determine elastic and density properties for the PEM embedded in the commercial reservoir simulator.
Ill-posed dry elastic and density property models are considered in a field case where the seismic inversion and petrophysical property model constrained by seismic inversion exist. An n-dimensional design optimization technique is implemented to determine the optimal solution of a multidimensional pseudo-objective function comprised of multidimensional design variables. This study investigates the execution of a modified particle swarm optimization (PSO) method combined with an exterior penalty function (EPF) with varied constraints. The proposed technique involves using n-dimensional design optimization to solve the pseudo-objective function comprised of the PSO and EPF given limited availability of constraints. In this work, an examination of heavily and reduced-order penalized metaheuristic optimization processes, where the design variables and optimal solution are derived from 3D arrays, is conducted so that constraint applicability is quantified. While the process is examined specifically for PEM, it can be applied to other data-limited modeling techniques.
This study is based on the premise that most of the trapped hydrocarbons can be produced, if we substitute them with another ‘acrificial’ fluid that has amplified interactions with organic pore walls, such as CO2. For the presented study, a downhole shale sample is analyzed in the laboratory to predict gas storage properties such as pore-volume, pore compressibility, and gas adsorption capacity. Then a series of pressure pulse decay measurements are performed to delineate transport mechanisms and predict stress-sensitive permeability. These coefficients are obtained as the calibration parameters of a simulation-based optimization for injection and production. Simulation model considers compositional gas flow in a deformable porous media and includes a multi-continuum porosity, with organic and inorganic pores, and micro-fractures. The experimental and simulation results show that most of the injected CO2 is adsorbed in the organic matrix and are not produced back. This is because CO2 molecules have significantly larger adsorption capacity when compared to methane. The strong adsorption of CO2 improves the release of natural gas from kerogen pores. This indicates that the separation of produced CO2 will be a minimal cost. Transport in kerogen has significant pore wall effects, and includes large mass fluxes of the adsorbed molecules by the walls due to surface diffusion. In essence, the adsorbed CO2 molecules significantly influence transport of methane. The results also show core-plug permeability is stress-sensitive due to presence of micro-fractures. Forward simulation results using optimum parameters indicate that closure stress developing near the fractures could significantly control the volume of CO2 injected. This raises operational issues on when to start injecting, and how to inject CO2. Using a simulation study of a production well with single-fracture, we show that fracture closure stress develops rapidly and production rate becomes a slave of the fracture geo-mechanics, e.g., strength of the proppants and the level of proppant embedment.
The objective of this work is to characterize the fault system and its impact on Mishrif reservoir capacity in the West Quran oil field. Determination and modelling of these faults are crucial to evaluate and understanding fluid flow of both oil and water injection in terms of distribution and the movement. In addition to define the structure away from the well control and understanding the evolution of West Qurna arch over geologic time.
In order to achieve the aim of the work and the structural analysis, a step wise approach was undertaken. Primarily, intensive seismic interpretation and building of structure maps were carried out across the high resolution of 3D-seismic survey with focusing on the main producing Mishrif reservoir of the field. Also, seismic attributes volumes provided a good information about the distribution and geometry of faults in Mishrif reservoir. The next step, it constructs 3-D fault model which will be later merged into the developed 3D geological model. West Qurna/1 oil field situated within the Zubair Subzone, and it is structurally a part of large anticline towards the north. The observation of seismically derived faults near Mishrif reservoir indicated en-echelon faults which refer to strike-slip tectonics along with extensional faults. The statistic of Mishrif interval faulting indicates a big number faults striking north-south along western wedge of anticline. The seismic interpretation, in combination with seismic attributes volumes, deliver a valuable structural framework which in turns used to build a better geological model.
In this paper, the work demonstrates a better understanding for the perspectives on the seismic characterization of the structural framework in the Mishrif reservoir, and also for similar heterogeneous carbonate reservoirs. Further, this work will ultimately lead to improve reservoir management practises in terms of production performance and water flooding plan.
The SWP project is located in a mature waterflood undergoing conversion to CO2-WAG operations at Farnsworth, Texas, USA. Utilized CO2 is anthropogenic, sourced from a fertilizer and an ethanol plant. Major project goals are optimizing the storage/production balance, ensuring storage permanence, and developing best practices for CCUS.
This paper provides a review of work performed toward development of a 3D coupled Mechanical Earth Model (MEM) for use in assessment of caprock integrity, fault reactivation potential, and evaluation of stress dependent permeability in reservoir forecasting. Mechanical property estimates computed from geophysical logs at selected wellbores were integrated with 3D seismic elastic inversion products to create a 3D "static" mechanical property model sharing the same geological framework as the existing reservoir simulation model including 3 major faults. Stresses in the MEM were initialized from wellbore stress estimates and reservoir simulation pore pressures. One way and two way coupled simulations were performed using a compositional hydrodynamic flow model and geomechanical solvers.
Coupled simulations were performed on history matched primary, secondary (waterflood), and tertiary (CO2 WAG) recovery periods, as well as an optimized WAG prediction period. These simulations suggest that the field has been operating at conditions which are not conducive to either caprock failure or fault reactivation. Two way coupled simulations were performed in which permeability was periodically updated as a function of volumetric strain using the Kozeny-Carmen porosity-permeability relationship. These simulations illustrate the importance of frequent permeability updating when recovery scenarios result in large pressure changes such as in field re-pressurization through waterflood after a long primary depletion recovery period. Conversely, production forecasting results are less sensitive to permeability update frequency when pressure cycles are short and shallow as in WAG cycles.
This paper describes initial work on development of a mechanical earth model for use in assessment of geomechanical risks associated with CCUS operations at FWU. The emphasis of this work is on integration of available geomechanical data for creation of the static mechanical property model. Preliminary coupled hydro-mechanical simulations are presented to illustrate some of the key diagnostic output from coupled simulations which will be used in later work for in depth evaluation of specific risk factors such as induced seismicity and caprock integrity.