CO2 Geological Storage Site Research Articles

Evolution of the Caprock Sealing Capacity Induced by CO2 Intrusion: A Simulation of the Dezhou Dongying Formation

CO2–water–rock interactions have an important impact on the stability and integrity of the caprock in CO2 geological storage projects. The injected CO2 in the reservoir enters the caprock via different mechanisms, leading to either the dissolution or precipitation of minerals. The mineral alterations change the porosity, permeability, and mechanical properties of the caprock, affecting its sealing capability. To evaluate the sealing effectiveness of overlying caprock and identify the influencing factors, numerical simulations and experiments were carried out on the mudstone Dongying Formation in Dezhou, China. Based on high-temperature and high-pressure autoclave experiments, batch reaction simulations were performed to obtain some key kinetic parameters for mineral dissolution/precipitation. Then, they were applied to the following simulation. The simulation results indicate that gaseous CO2 has migrated 7 m in the caprock, while dissolved CO2 migrated to the top of the caprock. Calcite is the dominant mineral within 1 m of the bottom of the caprock. The dissolution of calcite increases the porosity from 0.0625 to 0.4, but the overall porosity of the caprock decreases, with a minimum of 0.054, mainly due to the precipitation of montmorillonite and K-feldspar. A sensitivity analysis of the factors affecting the sealing performance of the caprock considered the changes in sealing performance under different reservoir sealing conditions. Sensitivity analysis of the factors affecting the sealing performance of the caprock indicates that the difference in pressure between reservoir and caprock affects the range of CO2 transport and the degree of mineral reaction, and the sealing of the caprock increases with the difference in pressure. Increasing the initial reservoir gas saturation can weaken the caprock’s self-sealing behavior but shorten the migration distance of CO2 within the caprock. When the content is lower than 2%, the presence of chlorite improves the sealing performance of the caprock and does not increase with further chlorite content. This study elucidates the factors that affect the sealing ability of the caprock, providing a theoretical basis for the selection and safety evaluation of CO2 geological storage sites.

Key indicators of caprock sealing assessment with consideration of faults in potential CO2 geological storage sites in Subei Basin, China

Good caprock sealing is crucial for ensuring the long-term safety and security of carbon dioxide (CO2) geological storage. However, concealed faults within caprocks and reservoirs can impact the transport and accumulation of CO2 plumes. Due to the uncertainties associated with the geometric structure, physical properties, and combined relationships among reservoir, caprock and fault, accurately evaluating caprock sealing is challenging. To address the challenge of identifying key indicators for caprock sealing considering faults, this study focuses on the one potential CO2 geological storage field in the Subei Basin, China. First, this study establishes a hydraulic-mechanical (HM) coupled finite element model considering a combination of caprock, reservoir and fault. Then, 22 research indicators, including fault offset, fault dip, caprock thickness, burial depth, permeability and mechanical properties, are analysed to evaluate their influence on caprock sealing via the tornado analysis and response surface methods. Finally, key indicators are determined based on evaluation criteria, such as pore pressure increment (ΔPP) and Coulomb failure stress (CFS), in the fault plane. The research results indicate that fault dip, fault offset, fault permeability, burial depth, and reservoir permeability are key indicators. The caprock thickness, caprock permeability, and caprock Young's modulus significantly influence the caprock sealing capacity. The ΔPP and CFS increase with increasing fault dip and offset. When the fault dip exceeds 45°, the ΔPP and CFS reach maximum values at the interface between the reservoir and caprock. Fault permeability has a greater impact than reservoir permeability and caprock permeability. The research results may provide guidance for the evaluation of caprock sealing capacity for CO2 geological storage.

Assimilation of Geophysics-Derived Spatial Data for Model Calibration in Geologic CO2 Sequestration

Summary Uncertainty in geological models usually leads to large uncertainty in the predictions of risk-related system properties and/or risk metrics (e.g., CO2 plumes and CO2/brine leakage rates) at a geologic CO2 storage site. Different types of data (e.g., point measurements from monitoring wells and spatial data from 4D seismic surveys) can be leveraged or assimilated to reduce the risk predictions. In this work, we develop a novel framework for spatial data assimilation and risk forecasting. Under the U.S. Department of Energy’s National Risk Assessment Partnership (NRAP), we have developed a framework using an ensemble-based data assimilation approach for spatial data assimilation and forecasting. In particular, we took CO2 saturation maps interpreted from 4D seismic surveys as inputs for spatial data assimilation. Three seismic surveys at Years 1, 3, and 5 were considered in this study. Accordingly, three saturation maps were generated for data assimilation. The impact from the level of data noise was also investigated in this work. Our results show increased similarity between the updated reservoir models and the “ground-truth” model with the increased number of seismic surveys. Predictive accuracy in CO2 saturation plume increases with the increased number of seismic surveys as well. We also observed that with the increase in the level of data noise from 1% to 10%, the difference between the updated models and the ground truth does not increase significantly. Similar observations were made for the prediction of CO2 plume distribution at the end of the CO2 injection period by increasing the data noise.

Carbon storage units and carbon storage obligations: A review of policy approaches

Policies that incentivize the capture and geological storage of CO2 from large point sources (‘CCS’; and more recently, atmospheric removals), have so far tended to reward the resultant avoided CO2 emissions (or CO2 removals) achieved by operators at the point of capture. The expectation has been that geological CO2 storage sites, as well as the connecting infrastructure, will be developed and operated based upon the funding delivered from the single point of incentive (e.g. under an emissions trading system or a carbon tax, only CO2 capture installation operators are absolved of the obligation to acquire and surrender CO2 emission rights or to pay the tax). Project-based crediting mechanisms (e.g. in the voluntary carbon market) tend to treat the entire chain of operations as a single entity to be supplied with emission reduction or removal credits. Consequently, there has been minimal explicit financial incentive to store CO2. Yet a multiple gigaton-per-year scale capture and storage industry requires complex CO2 networks to evolve, with multiple sources connecting to multiple sinks, with installations owned by different operators with different technical expertise, climate mitigation goals and obligations. This multiplicity of goals and incentives can create agency problems and cross-chain risks, which impact negatively upon investment decisions. In this paper, we review the history, evolution and potential of geological net zero (GNZ) and carbon storage (or takeback) obligation concepts applied to fossil carbon producers and suppliers as a means to address these risks alongside policies aimed at atmospheric net zero (ANZ) and fossil carbon emitters.

The effect of monitoring complexity on stakeholder acceptance of CO2 geological storage projects in the US gulf coast region

Environmental monitoring at geologic CO2 storage sites is required by regulations for the purposes of environmental protection and emissions accounting in the case of leakage to surface. However, another very important goal of environmental monitoring is to assure stakeholders that the project is monitored for safety and effectiveness. With current efforts to optimize monitoring for cost-effectiveness, the question remains: will optimization of monitoring approaches degrade stakeholder assurance, or do heavily-instrumented sites communicate higher risk to a stakeholder? We report the results of a stakeholder survey in Gulf Coast states of the US where carbon capture and storage (CCS) is developing quickly. We rely on a 2 by 2 factorial experiment in which we manipulate message complexity (complex v. simple) and social norm (support from scientists v. support from community members). Subjects were randomly assigned to one of four conditions: 1) complex message with scientist support; 2) complex message with community member support; 3) simple message with scientist support; or 4) simple message with community member support. In addition to the experimental stimuli, subjects were also asked about their need for cognition, attitudes toward science and scientists, attitudes about climate change and support for carbon capture and storage (CCS). Our sample is drawn from residents in states bordering the western Gulf of Mexico (Texas, Louisiana, Florida) where CO2 geologic storage is being planned both onshore and offshore. The results offer important implications for public outreach efforts to key stakeholders.

Time-lapse seismic inversion for CO2 saturation with SeisCO2Net: An application to Frio-II site

Seismic monitoring of geological CO2 storage (GCS) involves highly nonlinear seismic inversion and petrophysical inversion, making it challenging to estimate CO2 volume efficiently and detect possible early CO2 leakages. Deep learning (DL) using convolutional neural networks (CNNs) has shown promise in solving highly nonlinear seismic inversion problems. However, direct estimation of CO2 plume extent/saturation from time-lapse seismic gathers using DL is still underexplored, with no reported field applications to date. The investigation of field data is primarily hindered by scarcity of field data for neural network training. Other obstacles include highly nonlinear seismic-petrophysics inverse relationship, and presence of noise in field seismic data. We introduce SeisCO2Net, a deep CNN that predicts CO2 saturation maps directly from time-lapse full waveform shot gathers. For training, we use site-specific geological information, fluid flow physics, rock physics, and seismic modeling to generate synthetic datasets that closely resemble the CO2 storage site. Synthetic tests show promising results, inspiring us to apply SeisCO2Net's trained weights on field data collected at Frio-II GCS site by leveraging transfer learning principles. As reference, we compare SeisCO2Net's predicted CO2 saturation maps with results obtained from physics-based inversion. Our analyses show both methods display similar CO2 plume shapes, reasonable CO2 plume characteristics, and comparable saturation values. Our results suggest pre-training CNNs on physics-informed synthetic datasets and then applying the learned weights to field data is a viable approach to estimating field CO2 saturation. This method effectively addresses the scarcity of field training data, thus encouraging the feasibility of long-term GCS monitoring.

Effect of ScCO2-H2O treatment duration on the microscopic structure of coal reservoirs: Implications for CO2 geological sequestration in coal

The microstructure of coal reservoirs, especially the pore structure, alters as a result of physicochemical reactions between the CO2 acidic fluid and coals. However, it is still unclear what controls this process and how the pore structure properties of coal alter by the action of CO2 acid fluids change over time. The objective of this study is to identify the underlying mechanism by analyzing the changes in the mineral composition, surface roughness, as well as micropore and mesopore structure of anthracite and bituminous coal when exposed to supercritical CO2 (ScCO2)-H2O. The results indicate that coal reservoirs primarily undergo processes of adsorption expansion and mineral dissolution/precipitation. Among these, adsorption expansion concluded or weakened after 7 days, with mineral precipitation gradually becoming the dominant factor, which results in more secure geological CO2 storage (GCS). Furthermore, comparative analysis of anthracite and bituminous coal with untreated and long-term treatment demonstrates that anthracite exhibits higher CO2 storage capacity and greater wettability. Consequently, anthracite is more suitable as a target reservoir for GCS compared to bituminous coal. These results, therefore, offer a theoretical foundation and a guide for choosing GCS sites in deep un-minable coal seams.

Developing a roadmap for carbon capture, and storage in Oklahoma by assessing the viability of stacked storage

AbstractThe Intergovernmental Panel on Climate Change concludes that CO2 capture and storage (CCS) is critical for climate‐stabilizing energy transitions. In CCS, captured CO2 is sequestered in saline aquifers within sedimentary basins. The CO2 storage capacity and the rate of injection are functions of the geology of the saline aquifer, which is uncertain. To minimize impacts of this uncertainty, CCS projects could include backup plans, such as co‐locating geologic CO2 storage (GCS) sites with or near existing CO2‐enhanced oil recovery (CO2‐EOR) operations. These “stacked storage” projects could hedge against uncertainty in the saline formation performance because captured CO2 could be injected into either location in the event of unexpected events (e.g., the injectivity decreases). Here, we investigate the possibility and ramifications of developing CCS networks in Oklahoma that are amendable to stacked storage. We find that stacked storage is possible in Oklahoma but the counties with the lowest‐cost saline storage resources do not have existing CO2‐EOR operations. At the systems level, we find it is slightly more expensive (e.g., $1/tCO2 to $5/tCO2) to site GCS in counties with CO2‐EOR projects. This increased expense is largely due to increased CO2 transportation costs because hundreds of km of additional pipeline is required to capture CO2 from the lowest‐cost sources. Overall, our results suggest that it is optimal to build more pipelines and avoid injecting CO2 in some of the lowest‐cost saline storage resources, to enable capturing CO2 from the least‐cost sources. © 2023 Society of Chemical Industry and John Wiley & Sons, Ltd.

A numerical model for gas CO 2 migration in a fault zone

Understanding whether fractures and faults impact the CO 2 migration through the overburden is critical in the evaluation and monitoring of CO 2 geological storage sites. We present a numerical model and workflow to describe the hydraulic behaviour of a fault located in the shallow part of the overburden. This helps to evaluate the sealing potential of the system in case of unwanted CO 2 migration toward the surface and to design an efficient monitoring plan. The model configuration is representative of several experiments performed at real sites under quite shallow conditions (50–500 m). The model results, applied to a selected fault outcropping in the Apennines (Italy), show that most of the gas migrates through the high permeable footwall damage zone. A significant amount of gas then dissolves into the water, emphasizing the importance of accurate modelling to assess the hazard of CO 2 leakage into near-surface aquifers or to the surface. The occurrence of pressure buildup close to the fault core points out that detailed modelling of the migration conditions is required to predict gas path through a fault zone. Thematic collection: This article is part of the Fault and top seals 2022 collection available at: https://www.lyellcollection.org/topic/collections/fault-and-top-seals-2022

What do stakeholders expect from an integrated system for informing social partners and decision makers in digital monitoring of CO2 storage

The authors participate in DigiMon international project (“Digital monitoring of CO2 storage projects”), which aims to develop a next generation human centred monitoring system for CO2 geological storage sites. It includes newly developed subsurface imaging technologies based on seismic fibre optic and gravity surveying. In addition, the SEL methodology was developed, which provides an assessment framework to understand which technical and non-technical aspects still need to be improved in order to implement CCS and its monitoring system successfully. Application of the SEL methodology based on socio-economic research carried out in Norway, Netherlands, Germany and Greece, identified what do stakeholders expect from a monitoring system. In this paper, the authors provide hints on how the outcomes of the international project DigiMon can be integrated within a Decision Support System (DSS) in order to assist the operator to follow up and manage CCS operation. The role of DSS is to assist data access, reservoir modelling, results interpretation and development of alternative solutions. The key stakeholders (decision makers) that must be kept informed are determined by National legislation. Their role is to assess environmental risk and manage emergency crises, if and when they occur. Processed data can be transmitted exclusively to them and can also be presented on regional maps, highlighting possible mitigation scenarios and intervention measures.

Screening, classification, capacity estimation and reservoir modelling of potential CO2 geological storage sites in the NW Adriatic Sea, Italy

In Italy, the central-northern Apennines and Adriatic Sea domains have been identified as potential CO2 storage areas. Although capacity estimates have been undertaken at a regional scale, more detailed research is required to reduce uncertainty. The present study helps address this gap by conducting a detailed screening of a representative area in the north-western Adriatic Sea for suitable CCS sites, using an extensive dataset composed of both public and private seismic and borehole data. Work included selecting suitable sites based on proposed selection criteria, calculating their theoretical and effective storage capacities applying a probabilistic approach, and then performing dynamic flow modelling on one of the selected sites that is representative of fractured carbonate reservoirs. Based on the screening results, a total of 21 out of 38 structures were selected as having the required characteristics suitable for CO2 storage. As expected, the clastic rock reservoirs have the greatest potential capacity, although some fractured carbonate reservoirs did yield important volumes due to their dual porosity / permeability characteristics. Modelling of one such site highlighted the complex interplay between primary and secondary porosity / permeability on plume migration and capacity estimation. Our results highlight the need to integrate analytical calculations with dynamic simulations for more detailed, site-specific studies to improve the estimates of CO2 storage capacity.

Evaluation of heterogeneity effect on CO2 transport in regularly distributed and natural clast-matrix conglomerate cores

A series of numerical simulations were performed to investigate the heterogeneity effect resulting from spatial distribution of clast-matrix in conglomerates on CO2 migration under the reservoir conditions. Natural conglomerate cores drilled from geological CO2 storage site in South Korea as well as constructed cores comprising regularly distributed clast-matrix were numerically analyzed. Throughout the study, CO2 distribution, velocity of the CO2 front, breakthrough curves (BTCs), differential pressure (ΔP), gravity number (Ngv), and capillary number (Nc) were assessed to highlight the heterogeneity effect. In the regularly distributed clast-matrix cores, the CO2 plume with the corrugated shape of the front migrated faster than the matrix-only core. Even though the clast ratio was changed more than 10 %, there was not much difference in the arrival velocity of the CO2 plume (∼2.0×10−4 m/min). Nevertheless, there was a correlation between the clast ratio and the arrival velocity, clearly shown in the L-5 core having alternating layers of matrix and clasts. At natural conglomerate cores (JC-1 and JC-2), the migration pattern of the CO2 plume significantly differed. However, the clast-matrix ratio and the arrival velocity were strongly correlated with a large variation in the arrival velocity (∼2.6×10−3 m/min) despite the small change of the clast-matrix ratio. The variance of the cumulative arrival velocity was correlated with the clast-matrix ratio and the irregularity of the BTCs, which implied that the instability in the frontal displacement of the CO2 plume became greater where the clast ratio increased more. The ΔP was significantly affected by the distribution of clasts and matrix; ΔP increased as the CO2 passed narrow or heterogeneous pathways enclosed by the clasts and decreased as CO2 passed wide or diverging pathways. Interestingly, the highest ΔP was shown in the cores having the smallest clast ratio, implied that the heterogeneous distribution of clast-matrix could influence a degree of overpressure generation. The lowest Ngv below 1 and highest Ngv appear in JC-2 where the total clast ratio is more than 50 % and in H-1 consisting of matrix-only, respectively. The obtained ranges of Nc show that all the models are under capillary-dominated flow conditions relevant for CO2 sequestration. The magnitude of both Ngv and Nc correlates to the total clast ratio.

MULTIMOORA Method-Based Schweizer–Sklar Operations for CO2 Geological Storage Site Selection Under Pythagorean Fuzzy Environment

The site selection of CO2 geological storage facilities is essential for the development of safe and efficient carbon capture, utilization, and storage (CCUS) projects. Normally, CO2 geological storage site selection can be regarded as a complex multi-criteria decision-making (MCDM) problem. The aim of this paper is to present an integrated decision-making method for solving the site selection problem for CO2 geological storage. To achieve this goal, this method is based on multi-objective optimization by ratio analysis plus the full multiplicative form (MULTIMOORA) method and prioritized aggregation operators in Pythagorean fuzzy environment. The academic contributions of this study include: first, some Pythagorean fuzzy Schweizer–Sklar prioritized aggregation (PFSSPA) operators are proposed, which take into account the priority levels of criteria and the risk preferences of decision makers. The excellent properties of these operators are given. Then this study extends the classical MULTIMOORA method based on the developed aggregation operators (named PFSSPA-MULTIMOORA), and the calculation process of this method is described in detail. Subsequently, on the basis of the constructed criteria system, the PFSSPA-MULTIMOORA method is applied to rank the alternatives. Finally, we successfully utilized the PFSSPA-MULTIMOORA method to solve the site selection problem of CO2 geological storage in China. A comparative analysis of existing methods verifies the effectiveness and robustness of the proposed method. This work can provide advanced decision support for researchers and practitioners.

Seismic characterization of a fluid escape structure in the North Sea: the Scanner Pockmark complex area

SUMMARYSubsurface fluid escape structures are geological features which are commonly observed in sedimentary basins worldwide. Their identification and description have implications for various subsurface fluid flow applications, such as assuring integrity of overburden rocks to geological CO2 storage sites. In this study, we applied 3-D first-arrival traveltime tomography to a densely sampled wide-azimuth and wide-angle ocean bottom seismometer (OBS) data set collected over the Scanner Pockmark complex, a site of active gas venting in the North Sea. Seismic reflection data show a chimney structure underlying the Scanner Pockmark. The objective of this study was to characterize this chimney as a representative fluid escape structure in the North Sea. An area of 6$\times $6 km2 down to a depth of 2 km below sea level was investigated using a regularized tomography algorithm. In total, 182 069 manually picked traveltimes from 24 OBS were used. Our final velocity model contains compressional wave velocity perturbations ranging from −125 to +110 ms−1 relative to its average 1-D model and compares favourably with a coincident seismic reflection data set. The tomographic velocity model reveals that the chimney as observed in seismic reflection data is part of a larger complex fluid escape structure, and discriminates the genuine chimney from seismic artefacts. We find that part of the seeping gas migrates from a deep source, accumulates beneath the Crenulate Reflector unconformity at ∼250 m below seafloor (mbsf) before reaching the porous sediments of the Ling Bank and Coal Pit formation at <100 mbsf. In addition, the model shows that the venting gas at Scanner Pockmark is also being fed laterally through a narrow NW–SE shallow channel. Quantitative velocity analysis suggests a patchy gas saturation within the gas-charged sediments of the Ling Bank and the Coal Pit formations. Confined to the well-resolved regions, we estimate a base case average gas saturation of ∼9 per cent and in-situ gas volume of ∼1.64 $\times {10^6}\ {{\rm{m}}^3}$ across the Ling Bank and Coal Pit Fm. that can sustain the observed methane flux rate at the Scanner Pockmark for about 10 to 17 yr.

Optimization of CO2 geological storage sites based on regional stability evaluation—A case study on geological storage in tianjin, china

Carbon dioxide geological storage is one of the important means to mitigate the greenhouse effect and curb global warming. The key to carbon dioxide (CO2) geological storage is to select a suitable storage site. Using the geological analysis method and analytic hierarchy process (AHP)–fuzzy comprehensive evaluation method, combining the qualitative analysis of geological conditions with the quantitative calculation of site parameters, this study determines a site target area suitable for CO2 geological storage in Tianjin. First, the regional crustal stability of Tianjin is discussed, and the characteristics of regional gravity field anomaly, regional crustal thickness, and regional aeromagnetic characteristics are comprehensively analyzed. The site is focused on Banqiao sag, a class ⅳ tectonic unit in Bohai Bay Basin. Second, aiming at the storability, safety, and economy of the site, the expert investigation method is used to construct the target area evaluation index system, including four primary indexes and ten secondary indexes. The weight of each index is determined using the analytic hierarchy process. A two-level fuzzy comprehensive evaluation mathematical model is constructed. The suitability of CO2 geological storage in three sites (site A, site B, and site C) in Banqiao sag is evaluated. The results are as follows: the comprehensive membership of site A, site B, and site C is 0.8629, 0.3926 and 0.1750, respectively. The comprehensive membership of site A is the largest. The evaluation results show that the preferred target area of Tianjin local carbon dioxide geological storage site is located in ‘site A’ near Dazhangtuo fault in Banqiao sag, Huanghua depression, Bohai Bay Basin (with an area of about 5 km2). In this study, a suitable target area is delineated for the local CO2 geological storage site in Tianjin, which can be used as an advantageous location for CO2 geological storage. The conclusion has a positive response to the problem of CO2 emission reduction in Tianjin.

Passive seismic interferometry imaging: An example from the Ketzin pilot CO2 geological storage site

Ketzin is a well-known onshore CO2 geological storage test site. Injection started in June 2008 and ended in August 2013. About 67 kt of CO2 was injected into a saline aquifer reservoir. Numerous geophysical surveys have been conducted at the site, including passive seismic ones. Passive seismic interferometry can be applied in many seismic exploration investigations to image the underground structures. This study compares several passive seismic interferometry imaging methods to a data set acquired at Ketzin. The passive data set consist of 5 lines with 20 h of recordings in total. First, we apply the autocorrelation method to obtain zero offset stacked sections directly. Secondly, we test different interferometry methods to generate virtual shot gathers. These virtual shot gathers are then processed to obtain CDP stacked sections. Results from these methods are compared with an active data set recorded at the site. The processed passive sections have relatively less coherent reflections compared with the active stacked sections. However, the passive sections obtained by autocorrelation show good agreement with the active stacked sections. The stacked sections obtained by processing virtual shot gathers using crosscorrelation show similar features to the active stacked sections, but with poorer coherence in the reflections and are noisier than the autocorrelation sections.

A gradient-based deep neural network model for simulating multiphase flow in porous media

Simulation of multiphase flow in porous media is crucial for the effective management of subsurface energy and environment-related activities. The numerical simulators used for modeling such processes rely on spatial and temporal discretization of the governing mass and energy balance partial-differential equations (PDEs) into algebraic systems via finite-difference/volume/element methods. These simulators usually require dedicated software development and maintenance, and suffer low efficiency from a runtime and memory standpoint for problems with multi-scale heterogeneity, coupled-physics processes or fluids with complex phase behavior. Therefore, developing cost-effective, data-driven models can become a practical choice, and in this work, we choose deep learning approaches as they can handle high dimensional data and accurately predict state variables with strong nonlinearity. In this paper, we describe a gradient-based deep neural network (GDNN) constrained by the physics related to multiphase flow in porous media. We tackle the nonlinearity of flow in porous media induced by rock heterogeneity, fluid properties, and fluid-rock interactions by decomposing the nonlinear PDEs into a dictionary of elementary differential operators. We use a combination of operators to handle rock spatial heterogeneity and fluid flow by advection. Since the augmented differential operators are inherently related to the physics of fluid flow, we treat them as first principles prior knowledge to regularize the GDNN training. We use the example of pressure management at geologic CO2 storage sites, where CO2 is injected in saline aquifers and brine is produced, and apply GDNN to construct a predictive model that is trained with physics-based simulation data and emulates the physics process. We demonstrate that GDNN can effectively predict the nonlinear patterns of subsurface responses, including the temporal and spatial evolution of the pressure and CO2 saturation plumes. We also successfully extend the GDNN to convolutional neural network (CNN), namely gradient-based CNN (GCNN), and validate its capability to improve the prediction accuracy. GDNN has great potential to tackle challenging problems that are governed by highly nonlinear physics and enable the development of data-driven models with higher fidelity.

3D geochemical characterization of organic-rich shales of the Irati Formation, Paraná Sedimentary Basin: New perspective for CO2 geological storage in southeastern Brazil

To mitigate the worst impacts of global warming, the IPCC (Intergovernmental Panel on Climate Change) indicates the CO2 geological storage as one of the most feasible technologies to be deployed in the next years to reduce greenhouse gas emissions (GGE) by injecting significant amounts of CO2 into adequate geological formations. This work assessed southeastern Brazil where the largest concentration of stationary sources emitting CO2 is located. The objective of the study was to evaluate the shale layers of the Irati Formation, Paraná Sedimentary Basin, in terms of organic geochemical parameters and 3D spatial extension, for characterizing potential CO2 geological storage sites in unconventional reservoirs. Two layers of organic-rich shales, identified as Units E and H, were spatially delimited as potential shale gas reservoirs, based on organic geochemistry and petrography (0.46–0.55%Ro; 0.56–7.36% TOC, and 0.80%Ro; 8.45–9.62% TOC, respectively) and their feasibility as reservoirs to CO2 geological storage. In terms of thermal maturity, alterations in Rock-Eval pyrolysis data in proximity of intrusions (relative decrease in S1, S2, and HI values) and vitrinite reflectance indicate two sites (wells 2-AA-1-SP and 2-TB-1-SP) more suitable to CO2 storage as the high TOC values and elevated thermal maturity are indirect indicators of a higher potential sorption capacity. Thus, the organic chemistry parameters should be used together with the spatial analysis of 3D geological modeling as a guide to define intrusions of the Serra Geral Formation, and then to delimit reservoirs for CO2 storage in shales rich in organic matter within the Irati Formation.

Development of a Hybrid Monitoring System for Micro-seismic Observation and Time-lapse Surveys at Geological CO2 Storage Site in Shallow Water Area

Development of a Hybrid Monitoring System for Micro-seismic Observation and Time-lapse Surveys at Geological CO2 Storage Site in Shallow Water Area

Considering the Potential for Sedimentary Basin Geothermal Power Generation When Screening for Prospective Geologic CO2 Storage Sites

Considering the Potential for Sedimentary Basin Geothermal Power Generation When Screening for Prospective Geologic CO2 Storage Sites