Wormhole Generations in Indiana Limestone with CO2 Intrusion

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Cite This: Energy Fuels XXXX, XXX, XXX-XXX

Wormhole Generations in Indiana Limestone with CO2 Intrusion: Numerical Simulations Based on Core Flooding Experiments Ting Xiao,†,‡ Hyukmin Kweon,§ Brian McPherson,†,‡ and Milind Deo*,§ †

Department of Civil and Environmental Engineering, University of Utah, Salt Lake City, Utah 84112, United States Energy and Geoscience Institute, University of Utah, Salt Lake City, Utah 84108, United States § Department of Chemical Engineering, University of Utah, 50 S. Central Campus Drive, Salt Lake City, Utah 84112, United States ‡

ABSTRACT: In this paper, we examined possible impact factors for calcite dissolution and wormhole generation in limestone formations with CO2 saturated brine intrusion by continuum-scale reactive transport simulations. Previous core-flood experiments that mimic near-wellbore region conditions of Geological CO2 Storage (GCS) fields were used as verification cases. Simulation results reasonably reproduce the experimental results. The results suggest that the initial permeability distribution of the core and pre-existing large permeability zones along the core were key factors for wormhole generation. Porosity distribution also affects wormhole generation, but not significantly. According to our simulation results, CO2 saturated brine injection rate, injection pattern, calcite dissolution rate, and permeability anisotropy do not significantly impact calcite dissolution and wormhole generation. The Damköhler (Da) numbers were 0.45−0.9 for the experiments at the core scale in this study, which are in accordance with the value for wormhole growth in previous studies. The numerical models would be applicable in further studies at core scale or a larger scale, and the findings that existing levels of high-permeability pathways help drive wormhole generation and the time scale over which the phenomenon occurs are directly applicable in a field injection scenario.

1. INTRODUCTION

During dissolution of CO2, the weak acid H2CO3 forms and dissociates in the water.22 This decreases pH, which in turn induces dissolution of carbonate minerals of the host rock to buffer the reduced pH:

Reservoir acidization is a decades-old, widely used stimulation technique developed by the oil industry to remove nearwellbore damage.1,2 When acid is injected into a reservoir formation (especially carbonates), matrix minerals rapidly dissolve and form highly conductive flow channels, what many call “wormholes” that enhance oil production. Studies on wormhole initiation and growth patterns in acidized carbonate reservoirs are many, including Hung et al.,1 Hoefner et al.,3 Wang et al.,4 and Panga et al.5 Major objectives of these studies were numerical simulations of wormhole generation and growth1,5,6 and evaluation of mechanisms/key factors for wormhole initiation with both experiments and numerical methods.3,4,7−11 Hydrochloric acid is the most commonly used agent for carbonate acidizing because of its cost and performance, and organic acids (i.e., acetic, citric, and lactic acids) are also examined in recent studies.12,13 Recently, wormhole structures have also been observed in carbonate formation for carbon capture and sequestration (CCS) purposes.14−18 It is believed that the acidization process is an irreversible first-order dissolution reaction with strong acid injection;6,19 however, the mechanisms of CO2−water−rock interactions are quite different, due to the weak acid property of CO2 and the buffering effects of carbonate minerals.15,16In a typical implementation of the CCS process, supercritical CO2 is injected into underground porous formations (i.e., oil and gas reservoirs and deep saline aquifers), which then dissolves in formation water via the following reactions:20,21

CaCO3(calcite) + H+ ⇌ Ca 2 + + HCO3−

These CO2−water−rock interactions have considerable implications for porosity and permeability in the near-well environment, as a result of dissolution.23,24 Previous studies concluded that five main types of dissolution occur, including face dissolution, conical wormhole, dominant wormhole, ramified wormhole, and uniform dissolution, depending on injection rates and fluid/mineral properties.5 During CO2 injection in a carbonate reservoir, mineral dissolution could be either beneficial or detrimental, depending on the location in a reservoir system. When CO2 enters sealing units, it may increase permeability due to mineral dissolution. However, most studies suggest that CO2 “prefers” higher permeability reservoirs unless a fractured structure exists or the pressure exceeds the capillary entry pressure.25−27 When dissolution occurs in the near-wellbore reservoir, an increase in permeability and porosity could potentially allow an increase in CO2 flowrate and lower pressure gradients,20 resulting in greater connectivity and injection mode,28 which benefits the CO2 sequestration process in most scenarios. However, geomechanical implications of such changes on the stability of the reservoir are of crucial importance with respect to risk assessment.15,29 Thus, studies are necessary to understand the mechanisms and key factors of wormhole generation in

CO2 + H 2O ⇌ H 2CO3 ⇌ H+ + HCO3−

Received: July 31, 2017 Revised: September 25, 2017 Published: October 18, 2017

⇌ 2H+ + CO32 − © XXXX American Chemical Society

A

DOI: 10.1021/acs.energyfuels.7b01720 Energy Fuels XXXX, XXX, XXX−XXX

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(ICP-MS) were used for mineral components and cation elements. For ICP-MS analysis, the samples were digested using hydrofluoric acids (HF) and nitric acids (HNO3). General core properties of the unreacted Indiana limestone core are summarized in Table 1. The BET N2 adsorption method was used to measure mineral surface area of the samples.

carbonate reservoirs with CO2 injection, in order to increase CO2 injection efficiency and safety in CCS projects. Specifically, Kweon et al.30 found wormhole-type structures form at a previous existing hollow structure within an Indiana limestone core sample following CO2 and brine injection under reservoir conditions (3000 psi, 60 °C). However, similar structures did not form in other limestone samples of their experiment. Both flowrate and geometry structure were hypothesized as key controlling factors for the observed results. Gharbi et al.14 investigated CO2 saturated brine−limestone interactions with experiments, image analysis, and pore-scale modeling techniques. Wormholes were observed with a significant increase in porosity and permeability, and flow became concentrated in the wormhole regions. Wang et al.17 conducted four core-flood experiments and numerical modeling to assess pore space and pressure changes with CO2 injection. Features of the shape of the wormhole generation were simulated, which matched the pressure history of the experiments. Smith et al.16 studied CO2-induced dissolution of low permeability carbonates in the Weyburn-Midale CO2EOR site core samples, and pore structure heterogeneity was found to be the major reason for unstable dissolution fronts and fast pathways. Hao et al.31 conducted numerical modeling experiments to investigate effects of carbonate reactivity, flow velocity, permeability, and time on the development of dissolution fronts, based in part on experimental data of Smith et al.16 Results suggest that wormholes initiate more easily in areas of greater porosity and permeability, and fitted calcite dissolution rate constants range a few orders of magnitude among rock types, reflecting uncertainty. Most of these studies focused on the investigation of specific experimental phenomena with imaging tools such as micro tomography and a scanning electron microscope. Some of the studies conducted modeling calculations with simplified settings to estimate the flow and transport properties. However, none of these studies interpreted the dissolution patterns within the heterogeneous region, especially the key parameters controlling the wormhole generation process and their roles on the structure of the wormhole generation. In this context, the primary purpose of this study is to quantify mineral dissolution patterns in heterogeneous carbonate reservoirs. The mechanisms of wormhole generation and growth with CO2 injection are especially of great interest. We developed and applied reactive transport models of limestone core flooding experiments conducted by Kweon et al.30 Specific objectives of this study are (1) to compare the simulation and experimental results and confirm simulation results with experimental data, and (2) to analyze and interpret calcite dissolution and wormhole-type structure generation patterns and the relative roles of permeability and porosity heterogeneity, CO2 injection rate, and other potential variables.

Table 1. Mineralogical Compositions of Unreacted Indiana Limestone Core Used in the Experiments composition (based on XRD)

elements (based on ICP-MS)

calcite quartz dolomite Mg (mg/kg) K (mg/kg) Ca (mg/kg) Fe (mg/kg)

99.34% 0.49% 0.17% 3959 871 497 661 205

Micro Computed Tomography (Micro-CT) was applied for the quantitative examination of porosity changes and wormhole generations. The Micro-CT analyses were conducted with the 7 in. limestone cores before and after the experiments. The Micro-CT system provided an optical resolution of 42 μm. Four scans of each core were taken, including inlet, outlet, and two in between. Due to the angle limitations of the scanning device, a continuous scan of the entire core was not possible and a small gap exists between each scanned section. The angle limitation also resulted in a somewhat distorted image at both ends of the scan due to lower energy manifested at the extremes of the angle range. Micro-CT scans a surface, rendering a raw two-dimensional image. The 2-D raw images from Micro-CT are typically dark and difficult to interpret without additional processing. The brightness quality of the 2-D raw images was improved with MIPAV (Medical Image Processing, Analysis, and Visualization; http://mipav.cit.nih.gov) software. After brightness was improved in all the images, interpretation capability was improved. Other than brightness, nothing additional was altered. The enhanced 2D images were then superimposed or “stacked” to generate a 3-D image with Drishti v2.4 (https://sf.anu.edu.au/Vizlab/drishti/) software. Micro-CT detected the solid portions of each surface, but in the core flooding experiments, the dissolved portions were of more interest. Therefore, using Drishti v2.4 again, a negative image was rendered to highlight the portions of the limestone that were dissolved. The negative image was created by changing the settings to display the solid portions of the core as vacant, and the vacant core sections to display a solid. 2.2. Core Flooding System. The core flooding system used in these experiments is depicted in Figure 1. The main components of the experimental apparatus were a dual syringe pump system (Teledyne Technologies International Corp, ISCO D-500 series) for continuous flow and another syringe pump for confining flood, a supercritical CO2 pump (Supercritical Fluid Technologies, INC, SFT10), a core holder (Harbert Engineering, Hassler Core Cell), a high temperature oven, a pressure transducer, a back-pressure regulator (EQUILIBAR, EB1HP1), and a gas regulator. The core flooding experiments with limestone cores were described in the previous study,30 and a brief description of the material and methods is shown here. The limestone core was hosted in a core holder that was under 3000 psi confining pressure and 2000 psi back regulating pressure at the outlet in an isothermal oven at 60 °C. Supercritical CO2 and 2 wt % brine were mixed first in the mixing chamber and pumped at a constant flowrate into the core that was presaturated with the brine. The flowrates of the brine and CO2 were maintained constant for each experiment. 0.5 and 1 mL/min flowrates of brine were used for different runs; and three CO2 flowrates were used: 0 mL/min (blank brine run), 0.71 mL/min, and 1.41 mL/min. The different flowrates were chosen to verify the hypothesis that brine with a higher CO2 saturation would be more reactive. A flowrate of 0 mL/min CO2 and 0.5 mL/min brine was chosen as a blank test to compare with other experimental results. The pH of the influent

2. METHODS 2.1. Limestone Core Analyses. Indiana limestone has been widely used for tests of flow and transport in reservoirs over the world. The cores for this study (Product ID, B-101c) were obtained from Kocurek Industries INC. Hard Rock Division (Caldwell, Texas). The original size of each core was 8 in. in length and 1.5 in. in diameter. Samples for porosity measurements with the helium (He) porosimeter were prepared by cutting a 1 in. core section from the end of the core. The result of porosity was 0.2, consistent with the manufacturer’s calibrated value. For the core flooding experiments, limestone cores were approximately 7 in. in length and 1.5 in. in diameter. X-ray diffraction (XRD) and inductively coupled plasma mass spectrometry B


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Figure 1. Schematic diagram of the core flooding system.20 solutions was estimated ∼3.1 according to published data on pH values of CO2−brine mixtures at pressures and temperatures of our system.32 2.3. Brine Analysis. Effluent brine samples were collected over the entire duration of the experiments. The effluent collection container was changed with each sampling process, and this outlet fluid was then analyzed with ICP-MS for major cations. Preliminary data suggested that, for most ions, their concentration changes mostly occurred within a short span of time and would be negligible as time elapsed. In order to fully understand how these outflow water ion concentrations changed, and to obtain a continuous pattern of outflow cation concentrations, the samples were taken every 1 h for 24 h, every 2 h for 12 h, every 4 h for 12 h, every 8 h for 24 h, and then every 24 h for the remainder of the experiments. 2.4. Numerical Simulations of Wormhole Generation. 2.4.1. Simulation Tool. All simulations were performed with TOUGHREACT V233 and an equation of state for multiphase CO2 and brine, ECO2N.34 2.4.2. Model Domain. In order to simulate the porosity changes and wormhole generation of the experiments and their impact factors, a series of numerical simulations were conducted in accordance with the experimental conditions. To simplify the model and reduce the simulation time, a 2-D radial model was created to analyze the pore structure changes and wormhole generation (Figure 2). The section

placed at the core sample inlets to distribute the injected liquid uniformly. However, the efficiency of these distribution plates was not confirmed for a relatively high rate of injection. In order to confirm experimental conditions, both linear injection and point injection patterns were applied in the simulations. For point injection, brine and CO2 were injected into the central grid cell at the bottom; and for linear injection, injection rates were uniformly distributed over 1.0 cm (20 cells) along the injection surface. The simulation time duration was set as 10 days. 2.4.3. Model Parameters and Boundary Conditions. An isothermal temperature of 60 °C and pressure of 138 bar (2000 psi) were assigned as initial conditions. Heterogeneous porosity (mean value 0.2) and permeability (mean value 2.45 × 10−14 m2, calculated from experimental pressure drop at stabilized conditions) were assigned via random number generation. The top boundary was set as the constant pressure boundary, and others were set as closed boundaries. Calcite was more than 99% of the limestone compositions for all samples based on the XRD test; thus, the mineral compositions were assumed to be 99% calcite and 1% nonreact minerals (inert) to simplify analysis. In the simulations, calcite dissolution and calcium concentration changes of the outflow were of specific interest. The particle size of a mineral grain was set to 1 mm based on the grain size analysis (0.98 mm), and specific surface area (SSA) was calculated by

SSA =

A·v V · MW

where A is sphere area, v is molar volume, V is sphere volume, and MW is molecular weight.35 The initial water chemistry of the domain was calculated via equilibrium state of the mineral compositions. For CO2 and brine injection, all simulations assumed that CO2 dissolves in brine and became saturated before it reached the modeled domain. The injected brine chemistry (2 wt % NaCl) was balanced with saturated CO2 in our simulations. This simulation result showed that the influent solution pH was 3.06, which was accordant to previous experimental data32 and the assumption of the experiments. CO2 saturated brine injection rates were set as 0.5 and 1 mL/min. Gaseous CO2 injection was much more than what dissolved in the brine, and the injection rates of CO2 were still maintained at 0.71 and 1.41 mL/ min, as used in experiments. The dominant reaction between limestone and injected CO2 is calcite dissolution. To reduce simulation running time, the reactions with Mg, Fe, K, and other elements were neglected. The thermodynamic parameters for aqueous and mineral reactions were taken from the EQ3/6 database.36 The parameters for the kinetic rate law of calcite were taken from Palandri and Kharaka.37 The diffusion coefficient was adopted from Gherardi et al.38 2.4.4. Porosity−Permeability Relationship. It is usually believed that reservoir permeability fits a log-normal distribution function, but also may be statistically distributed in a variety of ways.39,40 It is also believed that a broad relationship exists between porosity and

Figure 2. Simplified conceptual model. near the inlet was of specific interest, because experimental Micro-CT results suggested that the porosity increases were the greatest at the bottom sections.30 The dimensions of the model were 1.9 cm (radius of the core samples) × 6 cm (2.4 in., bottom section of the core sample) with a total of 4560 cells (each grid cell is 0.5 mm × 0.5 mm). CO2 and brine were injected with constant rates, corresponding to the experimental design. In the experiments, distribution plates were C


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3. RESULTS AND DISCUSSION 3.1. Effluent Water Chemistry. The outflow calcium concentrations were plotted over time for the experiments and one example of simulations with a constant brine injection rate (0.5 mL/min) and various CO2 injection rates (Figure 4). For

Table 2. Porosity−Permeability Relationship and Distribution Used in This Study category

porosity distribution

permeability distribution

porosity−permeability relationship

I II III

linear normal linear

log-normal log-normal linear

none exponential linear

permeability and porosity distribution used in this study. The mean values were set as 2.45 × 10−14 m2 and 0.2, respectively, following the experimental results and manufacturer instructions. For the log-normal distribution, permeability was assumed to vary within 2 orders of magnitude (2.45 × 10−15 to 2.45 × 10−13 m2), and for the linear distribution, it was assumed to vary between 1.0 × 10−14 and 5.0 × 10−14 m2. For both linear and normal distributions of porosity, it was assumed to vary between 0 and 0.4. Permeability anisotropy was also considered in this study. For those simulation cases with permeability anisotropy, we set a higher z-direction permeability and lower x- and ydirection permeability. The mean value for the domain keeps the same as experimental results. Fracture permeability changes due to porosity changes were considered in the simulations. Cubic law is used to describe this change.33 The modified permeability k is given by

Figure 4. Effluent calcium concentrations of limestone flooding experiments and simulation results with different CO2 injection rates (brine injection rate is 0.5 mL/min for all the cases; dot for experiments and line for simulation results of category I).

the calcium concentrations of the experimental effluent, the blank test tends to have relatively low values for the elements throughout the time period, with the exception of a few large “spikes” at the beginning of the experiments. Similar results are obtained with the simulation of the blank test without significant concentration changes in the beginning, because we use a pre-equilibrium aqueous-mineral system. With CO2 injection, calcium concentration increases right after injection

⎛ ϕ ⎞3 k = ki⎜⎜ ⎟⎟ ⎝ ϕi ⎠ where ki and ϕi are the initial permeability and porosity, respectively.

Figure 3. Permeability and porosity distribution functions: (a) permeability distribution frequency; (b) cumulative distribution function (CDF) of permeability; (c) porosity distribution frequency; (d) CDF of porosity. D


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suggesting that the analyses based on simulations are substantially correct. 3.2. Impact Factors for Porosity Increase. In order to understand the impacts of different parameters for limestone porosity increase when in contact with CO2, seven cases were simulated for each category (Table 3). Injection rates of brine

for both experiments and simulations. Within 1 h, the effluent shows a high calcium concentration up to 800 mg/L and decreases to ∼600 mg/L later in the experiments. With high CO2 injection rate (1.41 mL/min), it seems that outflow calcium reaches a higher concentration in the beginning compared with low injection rate (0.71 mL/min). However, the trend is not significant, and after a few hours, the concentrations of the two cases drop to the same level. The simulation results also show a significant increase of calcium concentration right after injection occurs, and decreases afterward. However, Ca concentration changes vary among the cases with different initial permeability settings. For the two cases with different CO2 injection rates, calcium concentrations do not show a significant difference ( 0.9) for a relatively large area in category III, and permeability increases up to 10−10 m2. With varying degrees of simulated calcite dissolution of the three categories, the effluent water chemistry also shows corresponding differencesmore calcite dissolution causes higher effluent brine calcium concentration (shown in section 3.1). This explains the reason for different simulated pHs and Ca concentrations in three categories, E


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Figure 5. Porosity before and after simulation for category I: (a) initial condition; (b)−(h) cases 1−7.

these cases, and it might also have an impact on wormhole generation at large permeability zones. Therefore, our hypotheses for the key factors of wormhole generation mechanisms include: (1) CO2 flowrate (dissolved and gaseous), (2) pre-existing wormhole (high porosity) structures on the flow pathways, and (3) high permeability zone in the core (difficult to measure with the Micro-CT test). According to the hypotheses listed above, to analyze possible impact factors for wormhole generation, a series of simulations were conducted for each category (Table 4) following the experimental settings. Permeability, initial wormhole position, and porosity were of interest. Category I was set as the default category. For pre-existing wormholes, initial porosity was set with 0.95, assuming that the grids were totally dissolved. The permeability for those grids was set with 10−12 m2, which is significantly larger than the domain mean permeability value. 3.3.1. Pre-existing Wormhole Position. Three positions of pre-existing wormholes are tested in this study. Figure 8 shows the impact for wormhole generation by pre-existing wormhole positions of category I (cases 8, 11, and 12). The results suggest that a pre-existing wormhole position could affect wormhole generation to an extent, especially when the plume flows through the porous area. For the three cases, permeability distribution after 10-day injection shows an obvious difference. The larger permeability tends to control the flow pathways, and further increases the porosity. However, for case 12 with the pre-existing wormhole at the injection inlet, its impact is not as significant as the other cases (8 and 11). For neighboring areas of the pre-existing wormholes, calcite shows dissolution, but no

respectively. The difference between categories I and II suggests that porosity distribution could affect limestone dissolution behavior (permeability distribution is the same), and the difference between categories I and III indicates the intrinsic permeability distribution could affect dissolution behavior more significantly. This also indicates that the limestone dissolution pattern largely depends on the intrinsic formation geometry; thus, site-specific studies are indispensable to assess CO2 storage efficiency and mechanisms. 3.3. Wormhole Generation Mechanisms. Figure 7 (Micro-CT scan) shows the images of the limestone cores using micro-CT before and after experiments. The scenarios include: (1) 0.5 mL/min brine only; (2) 0.5 mL/min brine + 0.71 mL/min CO2; (3) 0.5 mL/min brine + 1.41 mL/min CO2; and (4) 1 mL/min brine + 1.41 mL/min CO2. For scenario (1), the core does not show obvious difference in porosity before and after the experiment, and the effluent water chemistry also does not show much fluctuation. Both scenarios (2) and (3) show obvious dissolution at the bottom sections; with a pre-existing porous area (wormhole) in the core, wormhole generates with scenario (4). The results suggest that the limestone core would not get impacted without acid fluid (CO2) injected, and a wormhole would generate with a preexisting wormhole and higher injection rate of CO2 and brine. For the scenarios without pre-existing wormhole structures, it seems not likely to generate further wormholes. However, the injection rates are smaller for these cases (2) and (3); the wormhole generation also might be due to the CO2 injection amount (rate). It is difficult to test permeability distribution in F


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Figure 6. Porosity and permeability before and after simulations: (a)−(d) category I; (e)−(h) category II; (i)−(l) category III.

core sample was cut in the experiments, it was also set with a large permeability along the injection inlet. Figure 9 shows selected results of simulations with porosity and permeability before and after injection. With a larger permeability (10−12 m2) along the core in a line, porosity of this line gets significantly increased, and a wormhole could be considered generated (porosity > 0.7 and significantly larger than neighboring sections; Figure 9a−d: (a) and (c) are initial porosity and permeability; (b) and (d) are porosity and permeability after 10 days). With an even larger permeability (10−11 m2) as an initial condition set within a line at the same position (case 20), the results of wormhole generation do not show a significant difference than the other cases (case 15 specifically). The permeability of the domain increases especially along the initial large permeability area (up to 2 orders of magnitude). The wormhole could also show up without the pre-existing porous

further wormholes are generated to enlarge the pre-existing wormhole for all the three cases. Another simulation was also conducted with a pre-existing porous area but without larger permeability for the initial condition. The results do not show much difference than the results from case 1, indicating that permeability is the main factor for the flow pathways and further porosity increase. For case 14 with further enlarged permeability (10−11 m2) at the pre-existing porous area, the impact for fluid flow and porosity increase is not significant compared to case 8. Generally, the pre-existing wormhole position could impact the flow pathway some, but its effect is not significant. 3.3.2. Large Permeability Zones. To test the role of permeability for wormhole generation, cases 15−21 were conducted. For these cases, a large permeability was set below and above the pre-existing wormhole. Because the edge of the G


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Figure 7. Micro-CT images of pre- (left) and post- (right) experiments:30 (a) 0.5 mL/min brine only; (b) 0.5 mL/min brine + 0.71 mL/min CO2; (c) 0.5 mL/min brine + 1.41 mL/min CO2; and (d) 1 mL/min brine + 1.41 mL/min CO2. The top of the core is at the top of each image, and the lighter color indicates pore space.

area but with a large permeability along the core (Figure 9i−l). This simulated scenario indicates that it is not necessary to have existing wormholes in the core; as long as there is a large permeability area along the core, the flow pathways could be controlled and wormholes would generate when contacting with CO2. However, the results also suggest that, with 10−13 m2 permeability ( 0.8) are limited for category II after 10 days injection, but average around 0.6−0.7. With the normal distribution of porosity (category II), the deviation is less than the linear distribution, and most of the porosity of the domain grids is around 0.2. It indicates that, with the same permeability domain, larger deviation of porosity could cause the wormhole generation faster. However, with a longer time, the impact of porosity distribution might not be as significant as the permeability. 3.3.4. Others. Other than the parameters discussed in former sections, flowrate, injection mode, permeability anisotropy, and calcite dissolution rate were also tested in our simulations. Larger flowrate and calcite dissolution kinetics could somewhat accelerate the wormhole generation; larger z-direction permeability and point injection could control the fluid flow direction at some level. However, their effects on wormhole generation are negligible compared to the effects of permeability in this study. Previous studies show that advection, diffusion, carbonate reaction, and their relationships also impact the wormhole generation, and its pattern could be characterized by using dimensionless numbers such as Péclet (Pe) and Damköhler (Da) numbers, where Pe is the ratio of advection and diffusion, and Da is the ratio of advection and carbonate reactions.4,31,42 The two nondimensional numbers are defined as31 Pe =

line line line line line line

brine

I


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Figure 8. Impact of pre-existing wormhole position (c1): (a)−(d) case 8; (e)−(h) case 11; (i)−(l) case 12.

enough to lead to a significant change on the flow pattern in the cores (Pe ≫ 1). Further studies at the pore scale are necessary for analyzing the impacts of regional flow patterns and specific pore structures.

the simulations to interpret wormhole generation with heterogeneous porosity and permeability evolution. Salient conclusions include: (1) The effluent water chemistry of the simulation reflects the experimental results, indicating that the simulations could represent the experimental conditions and process. The wormhole generation simulated by the model was in agreement with structures observed experimentally using Micro-CT. (2) Permeability distribution of the domain and pre-existing large permeability along the core were the key factors important for wormhole generation. (3) Porosity distribution affects the wormhole generation to some degree but not significantly; injection rate, injection pattern, and permeability anisotropy do not have significant impacts on wormhole generation according

4. CONCLUSIONS CO2 capture and sequestration (CCS) in geological reservoirs are widely applied worldwide. Porosity/permeability changes and wormhole generation near wellbore due to CO2−water− rock interactions highly impact CO2 flow and ultimately the storage amount in the reservoir. In this study, two-dimensional reactive transport simulations were conducted to analyze calcite dissolution and wormhole generation mechanisms in a limestone core, following the previous CO2 core-flood experiments.30 Generally, simulated results are consistent with the experimental results, which highlights the applicability of J


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Figure 9. Impact of permeability (c1): (a)−(d) case 15; (e)−(h) case 17; (i)−(l) case 19; (m)−(p) case 21.

to our simulations. However, further studies on finer pore scale are necessary for analyzing the impacts of local flow velocities.

(4) For the real core samples, the porosity and permeability distribution might be more complex than the simulated scenarios; advanced image techniques are necessary for K


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Figure 10. Porosity and permeability change for category III case 15: (a) and (b) porosity change; (c) and (d) permeability change.

Figure 11. Porosity and permeability change for category II case 15: (a) and (b) porosity change; (c) and (d) permeability change.

■

Table 5. Major Parameters for Dimensionless Number Calculations parameter

value

core length pore size

0.18 m 50 μm

flow velocity

0.036−0.073 m/s

diffusion coefficient Pe

10−9 m2/sb

a

1.8 × 103−3.7 × 103

parameter core radius kinetic rate constant calcite surface area calcite solubility Da

AUTHOR INFORMATION

Corresponding Author

*Tel.: +1 (801)581-7629. Fax: +1 (801)585-9291. E-mail: [email protected].

value 0.02 m 1.6 × 10−6 mol/ m2 s a 3000 m2/m3

ORCID

Ting Xiao: 0000-0002-4190-3826 Milind Deo: 0000-0002-4569-7097 Notes

0.13 mol/m3 (25 °C) 0.45−0.90

The authors declare no competing financial interest.

■

ACKNOWLEDGMENTS This work was funded by the Department of Energy through the project DE-FE009773. We gratefully acknowledge Dr. Trevor Irons for the interpretation of the CT images.

Palandri et al., ref 37. bGherardi et al., ref 38.

further interpretation of wormhole generation mechanisms. This study provides an example of improving the understanding of limestone dissolution and wormhole structure generations in the near-wellbore region with CO2 injection. The findings that existing levels of highpermeability pathways help drive wormhole generation and the time scale over which the phenomenon occurs are directly applicable in a field injection scenario. The model may be also applicable for studies of near-wellbore CO2 injection in other carbonate structures with specific experimental settings and/or reservoir geological data at larger scales.

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REFERENCES

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