scholarly journals An analytic nonlinear model of thermo-poro-elastic pressure transients in porous rocks 2 with application to deep CO2 storage.

2021 ◽  
Vol 64 (Vol. 64 (2021)) ◽  
Author(s):  
Roman Kanivetsky ◽  
Ettore Salusti

• Today a CO2 storage/segregation is an important option for a significant enhancing of CO2 sinks, to reduce the net carbon emissions into our planet atmosphere. Such storage/sequestration is a complex process, dealing with many facets of decision about the site selection, taking into consideration the local geological, geothermal, hydrodynamic and hydrocarbon potentials. In such multifaceted context, a thermo-poro-elastic nonlinear analytic model of fluid pressure P in deep rocks, can play an important role. To tackle this dynamics we here examine a nonlinear model of fluid pressure transient also considering convection, thermal dynamics and fluid/rock "frictions”. In addition, we here show that pressure dynamics, induced by an eventual external time or areal forcing can allow simple analytical determinations of pressure transients in these deep porous  media. Such processes indeed can have practical impacts on the CO2 evolution for storage in deep rocks and thus influence the final site choice for a deep CO2 injection. In synthesis, this model provides simple characterizations of thermo-poro-elastic transients for CO2 storage. 24 25 26

2021 ◽  
pp. petgeo2020-124
Author(s):  
Alexandra Tsopela ◽  
Adam Bere ◽  
Martin Dutko ◽  
Jun Kato ◽  
S. C. Niranjan ◽  
...  

With the increasing demand for CO2 storage into the subsurface, it is important to recognize that candidate formations may present complex stress conditions and material characteristics. Consequently, modelling of CO2 injection requires the selection of the most appropriate constitutive material model for the best possible representation of the material response. The authors focus on modelling the geomechanical behaviour of the reservoir material, coupled with multi-phase flow solution of CO2 injection into a saline saturated medium. It is proposed to use the SR3 critical state material model which considers a direct link between strength-volume-permeability that evolves during the simulation; furthermore the material is considered to yield prior to reaching a peak strength in agreement with experimental observations. Verification of the material model against established laboratory tests is conducted, including multi-phase flow accounting for relative permeabilities and fluid densities. Multi-phase flow coupled to advanced geomechanics provides a holistic approach to modelling CO2 injection into sandstone reservoirs. The resulting injection pressures, CO2 migration extent and patterns, formation dilation and strength reduction are compared for a range of in-situ porosities and incremental material enhancements. This work aims to demonstrate a numerical modelling framework to aid in the understanding of geomechanical responses to CO2 injection for safe and efficient deployment and is particularly applicable to CO2 sequestration in less favourable aquifers with a relatively low permeability, receiving CO2 from a limited number of injection wells at high flow rates. The proposed framework can also enable additional features to be incorporated into the model such as faults and detailed overburden representation.Thematic collection: This article is part of the Geoscience for CO2 storage collection available at: https://www.lyellcollection.org/cc/geoscience-for-co2-storage


SPE Journal ◽  
2014 ◽  
Vol 19 (06) ◽  
pp. 1058-1068 ◽  
Author(s):  
P.. Bolourinejad ◽  
R.. Herber

Summary Depleted gas fields are among the most probable candidates for subsurface storage of carbon dioxide (CO2). With proven reservoir and qualified seal, these fields have retained gas over geological time scales. However, unlike methane, injection of CO2 changes the pH of the brine because of the formation of carbonic acid. Subsequent dissolution/precipitation of minerals changes the porosity/permeability of reservoir and caprock. Thus, for adequate, safe, and effective CO2 storage, the subsurface system needs to be fully understood. An important aspect for subsurface storage of CO2 is purity of this gas, which influences risk and cost of the process. To investigate the effects of CO2 plus impurities in a real case example, we have carried out medium-term (30-day) laboratory experiments (300 bar, 100°C) on reservoir and caprock core samples from gas fields in the northeast of the Netherlands. In addition, we attempted to determine the maximum allowable concentration of one of the possible impurities in the CO2 stream [hydrogen sulfide (H2S)] in these fields. The injected gases—CO2, CO2+100 ppm H2S, and CO2+5,000 ppm H2S—were reacting with core samples and brine (81 g/L Na+, 173 g/L Cl−, 22 g/L Ca2+, 23 g/L Mg2+, 1.5 g/L K+, and 0.2 g/L SO42−). Before and after the experiments, the core samples were analyzed by scanning electron microscope (SEM) and X-ray diffraction (XRD) for mineralogical variations. The permeability of the samples was also measured. After the experiments, dissolution of feldspars, carbonates, and kaolinite was observed as expected. In addition, we observed fresh precipitation of kaolinite. However, two significant results were obtained when adding H2S to the CO2 stream. First, we observed precipitation of sulfate minerals (anhydrite and pyrite). This differs from results after pure CO2 injection, where dissolution of anhydrite was dominant in the samples. Second, severe salt precipitation took place in the presence of H2S. This is mainly caused by the nucleation of anhydrite and pyrite, which enabled halite precipitation, and to a lesser degree by the higher solubility of H2S in water and higher water content of the gas phase in the presence of H2S. This was confirmed by the use of CMG-GEM (CMG 2011) modeling software. The precipitation of halite, anhydrite, and pyrite affects the permeability of the samples in different ways. After pure CO2 and CO2+100 ppm H2S injection, permeability of the reservoir samples increased by 10–30% and ≤3%, respectively. In caprock samples, permeability increased by a factor of 3–10 and 1.3, respectively. However, after addition of 5,000 ppm H2S, the permeability of all samples decreased significantly. In the case of CO2+100 ppm H2S, halite, anhydrite, and pyrite precipitation did balance mineral dissolution, causing minimal variation in the permeability of samples.


Author(s):  
Zheming Zhang ◽  
Ramesh Agarwal

With recent concerns on CO2 emissions from coal fired electricity generation plants; there has been major emphasis on the development of safe and economical Carbon Dioxide Capture and Sequestration (CCS) technology worldwide. Saline reservoirs are attractive geological sites for CO2 sequestration because of their huge capacity for sequestration. Over the last decade, numerical simulation codes have been developed in U.S, Europe and Japan to determine a priori the CO2 storage capacity of a saline aquifer and provide risk assessment with reasonable confidence before the actual deployment of CO2 sequestration can proceed with enormous investment. In U.S, TOUGH2 numerical simulator has been widely used for this purpose. However at present it does not have the capability to determine optimal parameters such as injection rate, injection pressure, injection depth for vertical and horizontal wells etc. for optimization of the CO2 storage capacity and for minimizing the leakage potential by confining the plume migration. This paper describes the development of a “Genetic Algorithm (GA)” based optimizer for TOUGH2 that can be used by the industry with good confidence to optimize the CO2 storage capacity in a saline aquifer of interest. This new code including the TOUGH2 and the GA optimizer is designated as “GATOUGH2”. It has been validated by conducting simulations of three widely used benchmark problems by the CCS researchers worldwide: (a) Study of CO2 plume evolution and leakage through an abandoned well, (b) Study of enhanced CH4 recovery in combination with CO2 storage in depleted gas reservoirs, and (c) Study of CO2 injection into a heterogeneous geological formation. Our results of these simulations are in excellent agreement with those of other researchers obtained with different codes. The validated code has been employed to optimize the proposed water-alternating-gas (WAG) injection scheme for (a) a vertical CO2 injection well and (b) a horizontal CO2 injection well, for optimizing the CO2 sequestration capacity of an aquifer. These optimized calculations are compared with the brute force nearly optimized results obtained by performing a large number of calculations. These comparisons demonstrate the significant efficiency and accuracy of GATOUGH2 as an optimizer for TOUGH2. This capability holds a great promise in studying a host of other problems in CO2 sequestration such as how to optimally accelerate the capillary trapping, accelerate the dissolution of CO2 in water or brine, and immobilize the CO2 plume.


Energies ◽  
2021 ◽  
Vol 14 (6) ◽  
pp. 1557
Author(s):  
Amine Tadjer ◽  
Reidar B. Bratvold

Carbon capture and storage (CCS) has been increasingly looking like a promising strategy to reduce CO2 emissions and meet the Paris agreement’s climate target. To ensure that CCS is safe and successful, an efficient monitoring program that will prevent storage reservoir leakage and drinking water contamination in groundwater aquifers must be implemented. However, geologic CO2 sequestration (GCS) sites are not completely certain about the geological properties, which makes it difficult to predict the behavior of the injected gases, CO2 brine leakage rates through wellbores, and CO2 plume migration. Significant effort is required to observe how CO2 behaves in reservoirs. A key question is: Will the CO2 injection and storage behave as expected, and can we anticipate leakages? History matching of reservoir models can mitigate uncertainty towards a predictive strategy. It could prove challenging to develop a set of history matching models that preserve geological realism. A new Bayesian evidential learning (BEL) protocol for uncertainty quantification was released through literature, as an alternative to the model-space inversion in the history-matching approach. Consequently, an ensemble of previous geological models was developed using a prior distribution’s Monte Carlo simulation, followed by direct forecasting (DF) for joint uncertainty quantification. The goal of this work is to use prior models to identify a statistical relationship between data prediction, ensemble models, and data variables, without any explicit model inversion. The paper also introduces a new DF implementation using an ensemble smoother and shows that the new implementation can make the computation more robust than the standard method. The Utsira saline aquifer west of Norway is used to exemplify BEL’s ability to predict the CO2 mass and leakages and improve decision support regarding CO2 storage projects.


2018 ◽  
Vol 141 (4) ◽  
Author(s):  
Qihong Feng ◽  
Ronghao Cui ◽  
Sen Wang ◽  
Jin Zhang ◽  
Zhe Jiang

Diffusion coefficient of carbon dioxide (CO2), a significant parameter describing the mass transfer process, exerts a profound influence on the safety of CO2 storage in depleted reservoirs, saline aquifers, and marine ecosystems. However, experimental determination of diffusion coefficient in CO2-brine system is time-consuming and complex because the procedure requires sophisticated laboratory equipment and reasonable interpretation methods. To facilitate the acquisition of more accurate values, an intelligent model, termed MKSVM-GA, is developed using a hybrid technique of support vector machine (SVM), mixed kernels (MK), and genetic algorithm (GA). Confirmed by the statistical evaluation indicators, our proposed model exhibits excellent performance with high accuracy and strong robustness in a wide range of temperatures (273–473.15 K), pressures (0.1–49.3 MPa), and viscosities (0.139–1.950 mPa·s). Our results show that the proposed model is more applicable than the artificial neural network (ANN) model at this sample size, which is superior to four commonly used traditional empirical correlations. The technique presented in this study can provide a fast and precise prediction of CO2 diffusivity in brine at reservoir conditions for the engineering design and the technical risk assessment during the process of CO2 injection.


2020 ◽  
Vol 12 (22) ◽  
pp. 9723
Author(s):  
Chanmaly Chhun ◽  
Takeshi Tsuji

It is important to distinguish between natural earthquakes and those induced by CO2 injection at carbon capture and storage sites. For example, the 2004 Mw 6.8 Chuetsu earthquake occurred close to the Nagaoka CO2 storage site during gas injection, but we could not quantify whether the earthquake was due to CO2 injection or not. Here, changes in pore pressure during CO2 injection at the Nagaoka site were simulated and compared with estimated natural seasonal fluctuations in pore pressure due to rainfall and snowmelt, as well as estimated pore pressure increases related to remote earthquakes. Changes in pore pressure due to CO2 injection were clearly distinguished from those due to rainfall and snowmelt. The simulated local increase in pore pressure at the seismogenic fault area was much less than the seasonal fluctuations related to precipitation and increases caused by remote earthquakes, and the lateral extent of pore pressure increase was insufficient to influence seismogenic faults. We also demonstrated that pore pressure changes due to distant earthquakes are capable of triggering slip on seismogenic faults. The approach we developed could be used to distinguish natural from injection-induced earthquakes and will be useful for that purpose at other CO2 sequestration sites.


Energies ◽  
2020 ◽  
Vol 13 (23) ◽  
pp. 6456
Author(s):  
Ewa Knapik ◽  
Katarzyna Chruszcz-Lipska

Worldwide experiences related to geological CO2 storage show that the process of the injection of carbon dioxide into depleted oil reservoirs (CCS-EOR, Carbon Capture and Storage—Enhanced Oil Recovery) is highly profitable. The injection of CO2 will allow an increasing recovery factor (thus increasing CCS process profitability) and revitalize mature reservoirs, which may lead to oil spills due to pressure buildups. In Poland, such a solution has not yet been implemented in the industry. This work provides additional data for analysis of the possibility of the CCS-EOR method’s implementation for three potential clusters of Polish oil reservoirs located at a short distance one from another. The aim of the work was to examine the properties of reservoir fluids for these selected oil reservoirs in order to assure a better understanding of the physicochemical phenomena that accompany the gas injection process. The chemical composition of oils was determined by gas chromatography. All tested oils represent a medium black oil type with the density ranging from 795 to 843 g/L and the viscosity at 313 K, varying from 1.95 to 5.04 mm/s. The content of heavier components C25+ is up to 17 wt. %. CO2–oil MMP (Minimum Miscibility Pressure) was calculated in a CHEMCAD simulator using the Soave–Redlich–Kwong equation of state (SRK EoS). The oil composition was defined as a mixture of n-alkanes. Relatively low MMP values (ca. 8.3 MPa for all tested oils at 313 K) indicate a high potential of the EOR method, and make this geological CO2 storage form more attractive to the industry. For reservoir brines, the content of the main ions was experimentally measured and CO2 solubility under reservoir conditions was calculated. The reservoir brines showed a significant variation in properties with total dissolved solids contents varying from 17.5 to 378 g/L. CO2 solubility in brines depends on reservoir conditions and brine chemistry. The highest calculated CO2 solubility is 1.79 mol/kg, which suggest possible CO2 storage in aquifers.


Author(s):  
Sai-Kit Wu ◽  
Garrett Waycaster ◽  
Tad Driver ◽  
Xiangrong Shen

A robust control approach is presented in this part of the paper, which provides an effective servo control for the novel PAM actuation system presented in Part I. Control of PAM actuation systems is generally considered as a challenging topic, due primarily to the highly nonlinear nature of such system. With the introduction of new design features (variable-radius pulley and spring-return mechanism), the new PAM actuation system involves additional nonlinearities (e.g. the nonlinear relationship between the joint angle and the actuator length), which further increasing the control difficulty. To address this issue, a nonlinear model based approach is developed. The foundation of this approach is a dynamic model of the new actuation system, which covers the major nonlinear processes in the system, including the load dynamics, force generation from internal pressure, pressure dynamics, and mass flow regulation with servo valve. Based on this nonlinear model, a sliding mode control approach is developed, which provides a robust control of the joint motion in the presence of model uncertainties and disturbances. This control was implemented on an experimental setup, and the effectiveness of the controller demonstrated by sinusoidal tracking at different frequencies.


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