Sequestration Operations Research Articles

Optimal monitoring design for uncertainty quantification during geologic CO[formula omitted] sequestration: A machine learning approach

An effective monitoring design is crucial to ensure the safe and permanent geologic storage of CO2. Optimal monitoring design involve an optimal placement of monitoring wells, and optimal monitoring measurement data (pressure, CO2 saturation, temperature, etc.). We developed a filtering-based data assimilation approach to design an optimal monitoring strategy for well placement and monitoring data design. To efficiently solve the optimization problem and reduce computational costs, Artificial Neural Networks are used to develop computationally efficient reduced-order models based on full-physics numerical simulations of CO2 injection in saline aquifers. We demonstrate our approach in two scenarios of CO2 leakage through legacy or abandoned wellbores where an optimal monitoring strategy are devised to reduce the uncertainty in cumulative CO2 leakage in the geologic CO2 sequestration (GCS) site. The optimal monitoring design resulted in an uncertainty reduction in the cumulative leakage of CO2 of approximately 73% and 62% in each case, respectively. The proposed approach is efficient in developing monitoring designs under geologic uncertainty and enables safe geologic carbon sequestration operations.

Numerical investigations on the performance of sc-CO2 sequestration in heterogeneous deep saline aquifers under non-isothermal conditions

CO2 sequestration in geological formations is an efficient step towards mitigating climate change by reducing global warming. The CO2 emitted from natural sources and anthropogenic activities is injected into geological formations. The flow and transport of CO2 during sequestration operations require in-depth knowledge of the effects of the type of geological formation. The present work analyses the CO2 migration and storage in a heterogeneous deep saline aquifer with variable porosity and evolving permeability under non-isothermal flow conditions while upscaling the capillary pressure using the Leverett J-function. The developed numerical model is history-matched with CO2 gas saturation profiles reported using analytical and numerical approaches. The novelty of the present work lies in its ability to capture fine-scale heterogeneities in the aquifer, which is modelled through variation in the porosity (ϕ) distribution and the permeability (k). The thermal-hydraulic numerical analysis projected a pronounced effect of the degree of heterogeneity arising from the variation in porosity and permeability on pressure buildup along the top of the formation decreasing from a maximum of about 6.41 MPa at the injection well to about 0.933 MPa at 1200 m and affecting gas characteristics and transmission. The thermal front could only propagate to a maximum extent of about 142 m from the injection well in aquifers, while gas plume lengths migrated to a maximum plume length of about 1010 m. The permeability and porosity of the aquifer are critically observed to vary during the sequestration by a ratio (k/k0) of about 1.07 to 1.01 and a percentage of about 0.791 % – 3.136 % in the low permeable conditions. Maximum effective storage of CO2 by a factor of 0.95 observed in low-permeable heterogeneous aquifers with normally distributed porosity affirms maintenance of optimum gas injection rates below the fracture gradient in these formations to sequester the CO2 economically.

Mechanisms for Microseismicity Occurrence Due to CO2 Injection at Decatur, Illinois: A Coupled Multiphase Flow and Geomechanics Perspective

ABSTRACT We numerically investigate the mechanisms that resulted in induced seismicity occurrence associated with CO2 injection at the Illinois Basin–Decatur Project (IBDP). We build a geologically consistent model that honors key stratigraphic horizons and 3D fault surfaces interpreted using surface seismic data and microseismicity locations. We populate our model with reservoir and geomechanical properties estimated using well-log and core data. We then performed coupled multiphase flow and geomechanics modeling to investigate the impact of CO2 injection on fault stability using the Coulomb failure criteria. We calibrate our flow model using measured reservoir pressure during the CO2 injection phase. Our model results show that pore-pressure diffusion along faults connecting the injection interval to the basement is essential to explain the destabilization of the regions where microseismicity occurred, and that poroelastic stresses alone would result in stabilization of those regions. Slip tendency analysis indicates that, due to their orientations with respect to the maximum horizontal stress direction, the faults where the microseismicity occurred were very close to failure prior to injection. These model results highlight the importance of accurate subsurface fault characterization for CO2 sequestration operations.

Underground energy-related product storage and sequestration: site characterization, risk analysis and monitoring

Abstract This paper presents a high-level overview of site characterization, risk analysis and monitoring priorities for underground energy-related product storage or sequestration facilities. The siting of an underground storage or sequestration facility depends on several important factors beginning with the area of review. Collection of all existing and available records and data from within the rock volume, including potential vulnerabilities such as prior containment issues, proximity to infrastructure and/or population centres, must be evaluated. Baselining of natural processes before storage or sequestration operations begin provides the basis for assessing the effects of storage or sequestration on the surroundings. These initial investigations include geological, geophysical and geochemical analyses of the suitability of the geological host rock and environs for storage or sequestration. A risk analysis identifies and evaluates threats and hazards, the potential impact should they develop into unwanted circumstances or events and the consequences to the facility should any of them occur. This forms the basis for framing effective mitigation measures. A comprehensive monitoring programme that may include downhole well surveillance, observation wells, geochemical sampling and well testing ensures that the facility operates as designed and that unforeseen issues, such as product migration or loss of integrity, can be identified and mitigated. In addition to these technical issues, human factors and public perception of a project are a critical part of the site characterization, construction and operational phases of a project. Despite differences between underground storage and sequestration, the characterization, risk analysis and monitoring approaches that were developed for underground natural gas storage or for carbon dioxide sequestration could be used for underground storage or sequestration of any type of energy-related product. Recommendations from this work include: (1) develop an industry-standard evaluation protocol (workflow) for the evaluation of salt beds, saline aquifers, depleted hydrocarbon reservoirs, underground mines and cased wellbores for potential underground storage or sequestration development beyond those in use today; and (2) develop an industry-wide collaborative process whereby incident and near-miss data related to underground storage or sequestration operations can be reported, documented and shared for use in refining risk analysis modelling.

CO2 leak detection threshold using vertical seismic profiles

At the Containment and Monitoring Institute Field Research Station in Alberta, Canada, CO2 is being injected into a saline aquifer at 300 m depth to simulate a shallow leak from a deep carbon sequestration operation. The injection interval is a 7 m thick sandstone with a porosity of 11%. The gas-phase CO2 plume was detected with time-lapse vertical seismic profiles (VSP) after 32 tonnes of CO2 had been injected. The VSP surveys had high repeatability with permanent borehole geophones and carefully repeated source locations. A data processing workflow was developed to produce directly comparable baseline and monitor amplitudes while preserving subtle amplitude changes caused by partial CO2 saturation. Seasonal variations in the physical properties of the near-surface glacial tills introduced spectral differences between baseline and monitor datasets that were successfully mitigated by deterministic deconvolution and selected band-pass filters. The 32 t detection threshold represents a lower limit of CO2 detectability with borehole geophones in this geological setting. These results provide a rare field data example of CO2 monitoring at shallow to intermediate depths and demonstrate that VSP surveys are capable of identifying loss of containment in industrial-scale CO2 sequestration operations.

Insights into wettability alteration during cyclic scCO2-brine injections in a layered Bentheimer sandstone

Residual trapping of supercritical carbon dioxide (“scCO2”) is a key mechanism contributing to the safety and security of geologic sequestration operations. Recent experimental studies have suggested that cycles of scCO2 and brine injections cause surface chemistry reactions that increase residual trapping. We present results of a new experiment, analyzed with X-ray microcomputed tomography, aimed at pinning down specifics of the alteration mechanism. Four cycles of scCO2 and brine injections were conducted in a Bentheimer sandstone core with a prominent low permeability region at the base (inlet side) of the core. Multiple successive scCO2 injections were performed within cycles, and scCO2 injection flow rate was varied. Saturation profiles near the low permeability layer remain approximately constant, while downstream scCO2 saturation profiles change shape and generally increase for successive injections. Residual trapping increases over the four cycles, but only in the upper region of the core. Microstructural analysis of the scCO2 phase indicates increasing presence of relatively high contact angle (i.e. less water-wetting) surfaces as the experiment progresses. These results suggest that surface chemistry alteration occurs during drainage injections, and may also occur during imbibition. However, the effect is only evident in the relatively high permeability region of the core; in the low permeability region, capillary heterogeneity dominates flow patterns and wettability alteration effects are not evident. These results support previous work demonstrating sandstone wettability alteration due to scCO2/brine cycling, and provide new clarification as to the conditions under which this wettability alteration will cause shifts in scCO2 flow and trapping.

Well‐based monitoring of CO2 geological sequestration operations in saline aquifers: Critical insights into key questions

Geological carbon sequestration in saline aquifers is one of the most promising strategies to help mitigate emissions of CO2 to the atmosphere. Significant challenges in ensuring the security of the sequestration process rest in the evolution and expansion of the CO2 plume in the subsurface. The ability to track the movement of the injected CO2 poses another challenge. Critical questions related to the integrity of the sequestration operations in saline aquifers relate to plume characteristics that can we monitor using well-based variables. We addressed this and related questions using an integrated modeling framework through a numerical investigation of carbon sequestration in saline aquifers during long-term and post-injection periods. This modeling paradigm incorporates the effect of structural, geological, and petrophysical characteristics. That way, we can account for critical physicochemical processes, rock-fluid interactions, and lithology dependencies. The well fluid variables investigated include fluid composition, pH, fluid density, and ion activity. We learned that fluid property analytics and diagnostics can be powerful tools to estimate the movement of CO2 and its storage in different trapping mechanisms. These analytics can help optimize operational aspects and simplify reservoir-scale models while still reflecting the complex nature of the CO2 interactions underground and offering insights into plume evolution.

Machine Learning-Based, Near Real-time Leakage Detection for Caprock Integrity Monitoring using Distributed Acoustic Sensing (DAS) Data from Carbon Capture and Sequestration (CCS) Operations

Machine Learning-Based, Near Real-time Leakage Detection for Caprock Integrity Monitoring using Distributed Acoustic Sensing (DAS) Data from Carbon Capture and Sequestration (CCS) Operations

Modeling Gaseous CO2 Flow Behavior in LayeredBasalts: Dimensional Analysis andAquifer Response.

Particular attention is paid to the risk of carbon dioxide (CO2 ) leakage in geologic carbon sequestration (GCS) operations, as it might lead to the failure of sequestration efforts and to the contamination of underground sources of drinking water. As carbon dioxide would eventually reach shallower formations under its gaseous state, understanding its multiphase flow behavior is essential. To this aim, a hypothetical gaseous leak of carbon dioxide resulting from a well integrity failure of the GCS system in operation at Hellisheiði (CarbFix2) is here modeled. Simulations show that migration of gaseous carbon dioxide is largely affected by formation stratigraphy, intrinsic permeability, and retention properties, whereas the initial groundwater hydraulic gradient (0.0284) has practically no effect. In two different scenarios, about 18.3 and 30.6% of the CO2 that would have been injected by the GCS system for 3 days could be potentially released again into the atmosphere due to a sustained leakage of the same duration. As the gaseous leak occurs, the aquifer experiences high pressure buildups, and the presence of a less conductive layer further magnifies these. Strikingly, the dimensional analysis showed that buoyant and viscous forces can be comparable over time within the predicted gaseous plumes, even far from the leakage source. Local pressure gradients, buoyant, viscous, and capillary forces all play an important role during leakage. Therefore, neglecting one or more of these contributions might lead to a partial prediction of gaseous CO2 flow behavior in the subsurface, giving space to incorrect interpretations and wrong operational choices.

Evaluation of Geo-Mechanical-Chemical Impacts of Co2 Injection to Depleted Oil Reservoirs

This paper presents a more holistic approach in evaluating the impacts of CO2 injection in CO2 sequestration operations in a depleted Morrow B sandstone of the Farnsworth Unit, Ochiltree County, Texas. The complex interactions between CO2 and the formation fluids (oil and brine) and the acidized brine interactions with formation rock when coupled with mechanical processes present an integrated and realistic effect of CO2 injection in the underground environment. In light of this, different coupled numerical simulation models were developed to investigate the various CO2 trapping mechanisms and the long-term fate of CO2 in a depleted Morrow B sandstone. The models include hydrodynamical model, coupled hydrodynamical-mechanical model, coupled hydrodynamical-chemical model, and coupled hydrodynamical-chemical-mechanical model. A WAG operation was carried out for 20 years after the history period and followed by a post-injection period of 1000 years to monitor and evaluate the effect of the injected CO2 on the underground environment. This work shows that geomechanics impacted the petrophysical properties of the reservoir and had significant impact on the injectivity of CO2. The chemical reactions had very little impact on the petrophysical properties of the reservoir. The different simulation scenarios resulted in variable amounts of storage within the partially depleted oil reservoir.

A metric for evaluating conformance robustness during geologic CO2 sequestration operations

A metric for quantifying the robustness of a designation of conformance of a geologic CO2 sequestration (GCS) project during its operational phase is developed and demonstrated. Conformance in this context is a measure of the degree to which the sequestration system is understood and can be accurately modeled along with the degree to which the storage system is performing as designed. The robustness of conformance quantifies the degree to which parameter values can deviate from their current nominal estimates and still produce model forecasts that meet the performance criteria for the GCS operation. We develop and demonstrate the approach on a simplified scenario to illustrate the concept using a single uncertain parameter (homogeneous reservoir permeability) and a single performance criterion (critical pressure at a monitoring well in the reservoir; i.e., one that may displace brine from the reservoir to an overlying drinking water aquifer for example). Increased confidence in conformance assessment as more monitoring data are obtained is incorporated through the standard error of the coefficient (reservoir permeability in the case presented here), which we designate as the concordance metric. As more monitoring data become available during the course of the GCS operation, the standard error of the coefficient decreases (in general), thereby leading to increased conformance robustness as a larger deviation from nominal is required to fail to meet performance criteria. Increasing conformance robustness over time builds confidence that a GCS project will continue to meet performance criteria during the life-span of the project, thereby supporting designations of conformance. A lack of conformance robustness provides a critical warning that the performance criteria of the GCS operation are not robust against probabilistic and non-probabilistic uncertainty in model conceptualization and/or model parameters.

Adaptive Pressure Management and Plume Control in Geological Co2 Storage: Designing a Brine Extraction Field Experiment

Industrial scale injection of CO2 into the subsurface can result in significant fluid pressure increases, which can lead to potential environmental impacts such as caprock fracturing, fault activation and leakage into underground fresh water aquifers. Pressure management through brine extraction is an approach for managing formation pressure, effective stress, and plume movement in response to CO2 injection. However, the handling and management of the extracted brine has a cost that is added to carbon capture and sequestration (CCS) operations; therefore minimizing the extracted volume of brine can be of great importance. At the same time, economics of pressure management via brine extraction can be improved by treating the extracted high-salinity water and making it available for beneficial uses, for example as cooling water for power plants. In this paper, we introduce and demonstrate application of an adaptive reservoir management approach that optimizes extraction rates of reservoir brines for pressure control in an integrated optimization framework. Our approach will be tested during a brine extraction field experiment located in the southern United States, which is currently in the design and planning stages. The objective of the experiment is to evaluate the technical feasibility of managing subsurface pressures associated with large-scale CO2 injection volumes and to assess the cost and effectiveness of desalination technologies for saline waters containing high total dissolved solids (TDS). Our integrated adaptive management approach involves monitoring, model calibration, and optimization of brine extraction for pressure control. Based on measurements obtained during the injection phase and utilizing improved predictive models from repeated calibration, initial optimization calculations will be revised in regular intervals and the operating decisions for controlling and managing subsurface pressurization will be updated. In this paper, in preparation of the actual field demonstration, we investigate use of borehole measurements (i.e., pressure changes) and electromagnetic (EM) geophysical methods (i.e. salinity changes) in the adaptive management of the injection and brine extraction project. We also present a numerical exercise to investigate how the optimization performance is affected by the quality of initial site characterization data and by the frequency of dynamic model updates with newly acquired data during the injection. Our numerical study shows that more accurate initial reservoir characterization data reduce the risk of pressure buildup above a given maximum pressure because the optimization algorithm arrives at better estimates of initial extraction rates, which in turn results in better control of pressure during the overall injection times. Results also show that low frequencies of model calibration and optimization with the new data, especially at early injection periods, may lead to optimization problems, either because pressure buildup constraints are violated or excessively high extraction rates are proposed. These optimization problems can be eliminated if more frequent data collection and model calibration are conducted, especially at early injection times. Approaches such as adaptive pressure management may constitute an effective tool to manage pressure buildup under uncertain reservoir conditions by minimizing the brine extraction volumes while controlling pressure buildups. This will be demonstrated in the actual field study, with injection planned to start in early 2019.

Immobile Pore-Water Storage Enhancement and Retardation of Gas Transport in Fractured Rock

The effect of immobile pore-water on gas transport in fractured rock has implications for numerical modeling of soil vapor extraction, methane leakage, gaseous $$\hbox {CO}_2$$ leakage from sequestration operations, radionuclide transport from underground nuclear explosions, and nuclear waste disposal. While the ability for immobile pore-water storage to effect gas transport has been recognized in the past, the details and specific scenarios leading to enhanced, retarded, or unaffected gas transport have not been explored. We performed numerical investigations into the enhancement and retardation of gas transport due to immobile pore-water storage in order to identify implications for gas transport applications. To do this, we developed a numerical approach to model gas transport with a single-phase flow solution coupled to the advection–dispersion equation modified to account for immobile pore-water storage. Other than the immobility of pore water, the formulation contains all other physics included in two-phase formulations (advective and diffusive gas transport in fractures and rock matrix and dissolution in immobile pore water). The assumption of immobile pore water is valid here since for many applications involving transport of soluble gases in fractured rock, the rate of aqueous transport is insignificant compared to gas transport. We verify our modeling approach with analytical solutions of: (1) 1D gas diffusion, (2) 1D gas advection, (3) barometric pumping of a fracture, and (4) gas transport with uniform fracture flow and diffusion into the matrix. We account for pore-water storage in our model by implementing a kinetic formulation of gas dissolution wherein the dissolved (aqueous) phase is considered an immobile constituent. Using this formulation, we model the effect of dissolution rate and saturation on the retardation of gas transport during pure diffusion and pure advection. We also demonstrate that although it is commonly believed that pore-water storage will always enhance gas transport in fractures during oscillatory flow (e.g., during reversing pressure gradients such as barometric pumping cycles), our simulations indicate that this may not always be the case. Our numerical investigations indicate that scenarios with lower effective diffusion coefficients ( $$\lessapprox \,10^{-5}\,\hbox { m}^2/\hbox {s}$$ ) and lower dissolution coefficients (i.e., the dissolution diffusion coefficient) ( $$\lessapprox \,10^{-11}\,\hbox { m}^2/\hbox {s}$$ ) will result in enhanced gas transport. Other combinations of gaseous diffusion and dissolution coefficients result in delayed gas transport or insignificant effect on gas transport. Based on these results, and given the fact that the free-air diffusion coefficients for many gases are slightly above $$10^{-5}\,\hbox { m}^2/\hbox {s}$$ (near the boundary of enhanced/non-enhanced gas transport), tortuosity would have to be significant for gas transport enhancement to occur. Similarly, if we consider the free-water diffusion coefficient of gases (around $$10^{-9}\,\hbox { m}^2/\hbox {s}$$ for many gases of interest) to be a maximum bound for the effective dissolution coefficients (i.e., the rate of diffusion into the water away from the air/water interface will limit the dissolution rate), the effective dissolution coefficient would have to be at least 2 orders of magnitude less for enhanced gas transport to occur. Otherwise, pore-water storage will delay or have negligible effect on the gas transport. The results also indicate that the assumption of instantaneous equilibrium, often invoked in numerical codes for dissolution processes (i.e., dissolution coefficient is effectively infinite), will fail to accurately capture important details of soluble gas transport. The implication of our results is that gas breakthrough times in fractured rock during oscillatory flow may be highly dependent on the effective gaseous diffusion and dissolution coefficients.

Prediction of CO2 leakage risk for wells in carbon sequestration fields with an optimal artificial neural network

Carbon Capture and Storage (CCS) is a key climate mitigation technology. Leakage of the injected CO2 is one of the major environmental concerns. The potential for CO2 leakage from wells is one of the critical risks identified in geological CO2 sequestration. The objective of this study is to develop a computerized statistical model with the neural network algorithm for predicting the probability of long-term leak of wells in CO2 sequestration operations. Well design and operation data for over 500 CO2 exposed wells were generated from the West Hastings oil field and Oyster Bayou oil field in southern Texas, USA. The well integrity conditions were assessed by analyzing the well attribute data (well type, well age, CO2 exposed period, well construction details and materials), well operation histories and regulatory changes. Leakage-safe Probability Index (LPI) was assigned to individual wells. A computerized statistical model with network algorithm was developed based on data processing and grouping. Comprehensive training and testing of the model were carried out to ensure that the model was accurate and efficient enough for predicting the probability of long-leak of wells in CO2 sequestration operations. The accuracy of the trained neural network for well leakage prediction was also verified by the field operation in the Cranfield Field, Mississippi, USA. The developed neural network model can improve the efficiency of the storage operations by predicting the risk of CO2 leakage in the current exposed wells. In addition, it can also contribute in developing best practices standards by proposing recommendations for well construction in future wells.

Desalination of hypersaline brines via Joule-heating: Experimental investigations and comparison of results to existing models

Thermodynamic data of multicomponent brines are needed to properly treat brines from oil/gas and CO2 sequestration operations. Joule-heating treatment of hypersaline brine is a unique methodology that allows for direct heating of brines without the need of external heating, potentially simplifying operation and reducing process footprint. The thermodynamic properties of multicomponent hypersaline brine (>3.5wt%) are unknown and limited to estimations based on single component brine data. Experimental data for multicomponent brines at elevated temperatures and pressures do not exist due to operating conditions above the pseudocritical point of pure water. This study combines experimental results for multicomponent brines using a Joule- heated desalinator at pressures of 230 to 280bar and temperatures of 387 to 406°C with thermodynamic models previously created for single component NaCl brines to identify the deviations resulting from the additional species. In addition, a comparison between an Aspen Plus® v9 simulation using the ELECTNRTL model with experimental results is provided.

Treatment of produced water from an oilfield and selected coal mines in the Illinois Basin

If large-scale CO2 sequestration operations are implemented in oilfields or coal mines, large volumes of water (i.e., produced water) could potentially be generated that would need to be properly managed. In this work, produced water samples with total dissolved solids (TDS) values of 18,000–102,000mg/L (ppm) were collected from an oilfield, a coal-bed methane field, and a coal mine in the Illinois Basin of the United States and were treated by selected conventional pretreatment processes followed by a reverse osmosis desalination process. Pretreatment processes included coagulation by lime, ferric chloride, or aluminum sulfate; filtration by sand, walnut shells, anthracite coal, or microfiltration; and adsorption by organoclay, activated carbon, or ion-exchange resins. Selected pretreatment processes were sufficient for removing most of the contaminants, but the high sodium background of the high-TDS produced water (102,000ppm) limited the effectiveness of the ion-exchange pretreatment in removing scale-forming species. Reverse osmosis was a practical process for desalination of pretreated produced water samples tested (by reducing the TDS more than 96%) except for the high-TDS produced water. Reported bench-scale produced water treatment data might be beneficial for the design and operation of pilot-scale plants for treating produced waters with similar properties.

Collective properties of injection‐induced earthquake sequences: 1. Model description and directivity bias

AbstractInduced seismicity is of increasing concern for oil and gas, geothermal, and carbon sequestration operations, with several M > 5 events triggered in recent years. Modeling plays an important role in understanding the causes of this seismicity and in constraining seismic hazard. Here we study the collective properties of induced earthquake sequences and the physics underpinning them. In this first paper of a two‐part series, we focus on the directivity ratio, which quantifies whether fault rupture is dominated by one (unilateral) or two (bilateral) propagating fronts. In a second paper, we focus on the spatiotemporal and magnitude‐frequency distributions of induced seismicity. We develop a model that couples a fracture mechanics description of 1‐D fault rupture with fractal stress heterogeneity and the evolving pore pressure distribution around an injection well that triggers earthquakes. The extent of fault rupture is calculated from the equations of motion for two tips of an expanding crack centered at the earthquake hypocenter. Under tectonic loading conditions, our model exhibits a preference for unilateral rupture and a normal distribution of hypocenter locations, two features that are consistent with seismological observations. On the other hand, catalogs of induced events when injection occurs directly onto a fault exhibit a bias toward ruptures that propagate toward the injection well. This bias is due to relatively favorable conditions for rupture that exist within the high‐pressure plume. The strength of the directivity bias depends on a number of factors including the style of pressure buildup, the proximity of the fault to failure and event magnitude. For injection off a fault that triggers earthquakes, the modeled directivity bias is small and may be too weak for practical detection. For two hypothetical injection scenarios, we estimate the number of earthquake observations required to detect directivity bias.

Impact of wettability alteration on 3D nonwetting phase trapping and transport

We investigate capillary trapping and fluid migration via x-ray computed microtomography (x-ray CMT) of nonwetting phase (air) and wetting phase (brine) in Bentheimer sandstone cores which have been treated to exhibit different degrees of uniform wettability. x-Ray CMT scans were acquired at multiple steps during drainage and imbibition processes, as well as at the endpoints; allowing for assessment of the impact of wettability on nonwetting phase saturation and cluster size distribution, connectivity, topology and efficiency of trapping. Compared with untreated (water-wet) Bentheimer sandstone, cores treated with tetramethoxylsilane (TMS) were rendered weakly water-wet, and cores treated with octadecyltrichlorosilane (OTS) demonstrate intermediate-wet characteristics. As apparent contact angle increases, drainage flow patterns deviate from those derived for water-wet systems, total residual trapping and trapping efficiency decrease, and buoyancy plays a larger role during nonwetting phase mobilization; this has significant implications for CO2 migration and trapping during CO2 sequestration operations.

Accurate prediction of properties of carbon dioxide for carbon capture and sequestration operations

Development of robust predictive models to estimate the transport properties of gases (namely viscosity and thermal conductivity) is of immense help in many engineering applications. This study highlights the application of the artificial neural network (ANN) and least squares support vector machine (LSSVM) modeling approaches to estimate the viscosity and thermal conductivity of CO2. To propose the machine learning methods, a total of 800 data gathered from the literature covering a wide temperature range of 200–1000 K and a wide pressure range of 0.1–100 MPa were used. Particle swarm optimization (PSO) and genetic algorithm (GA) as population-based stochastic search algorithms were applied for training of ANNs and to achieve the optimum LSSVM model variables. For the purpose of predicting viscosity, the PSO-ANN and GA-LSSVM methods yielded the mean absolute error (MAE) and coefficient of determination (R2) values of 1.736 and 0.995 as well as 0.51930 and 0.99934, respectively for the whole data set, while for the purpose of predicting thermal conductivity, the PSO-ANN and GA-LSSVM models yielded the MAE and R2 values of 1.43044 and 0.99704 as well as 0.72140 and 0.99857, respectively for the whole data set. Both methods provide properly capable method for predicting the thermal conductivity and viscosity of CO2.

Design and Scheduling of CO2 Enhanced Oil Recovery with Geological Sequestration Operations as a Strip Packing Problem

Carbon capture and storage (CCS) is an important technology that enables the reduction of CO2 emissions while allowing the use of power plants running in fossil fuels. Coupled with enhanced oil recovery (EOR), it allows additional revenues to be realized by increased oil production through the injection of captured CO2 into depleted oil reservoirs. For a system with multiple reservoirs, it is necessary to determine the amount of CO2 to be supplied and the schedule of EOR operations to be conducted. This also requires the optimal design and scheduling of each operation to maximize profitability. In this study, a mixed integer linear program (MILP) was developed using the analogy of the strip packing problem. A case study is presented to illustrate the model.