CO2 Injection Wells Research Articles

Leakage monitoring of carbon dioxide injection well string using distributed optical fiber sensor

Whether the oil and gas fields in the Carbon Capture, Utilization, and Storage (CCUS) project use underground storage or energy supplementation to enhance oil recovery, they must be injected or monitored through the wellbore. Thus, the foundation and requirement for the safety of carbon dioxide (CO2) storage is the wellbore's integrity. When CO2 is dissolved in water, carbonic acid is created, and this acid strongly corrodes underground pipes. Therefore, the integrity issue with CO2 injection wells is more noticeable than with other wellbores. An annular pressure during gas injection is the primary symptom of gas injection string leakage in CO2 injection wells. This study aims to provide real-time pipe string monitoring using a distributed optical fiber temperature sensing system (DTS) and a distributed optical fiber acoustic sensing system (DAS). Variations in temperature and vibration are caused by annulus pressure relief or gas injection. Optical fiber logging, in contrast to traditional logging, has better performance indicators for optical fiber sensing apparatus. To adapt to complex wellbore conditions, it is necessary to enhance the temperature accuracy of DTS and the sensitivity and signal-to-noise ratio of DAS in CO2 drive injection wells based on the features of the gas injection string. To differentiate the leakage signal from the regular fluid flow signal, the energy calculation in the frequency band is done for DAS based on noise reduction, and the signal processing in the frequency band is done by the spectrum characteristics of the CO2 wellbore signal. The translation invariant wavelet algorithm is the primary denoising method for DTS, overcoming the shortcomings of traditional wavelet threshold algorithms such as excessive smoothing and the pseudo-Gibbs phenomenon. Furthermore, the depth correction during the optical cable lowering process is also examined in this paper. A CO2 gas injection well field experiment was conducted using this technology. A 1671m well was dug, and 1631m of optical cable were installed in the tubing. The tubing leakage position was successfully identified through gas injection, annulus pressure relief, and a comparison of DAS and DTS data. The field results demonstrate the accuracy with which the gas injection string integrity can be accurately monitored in real-time using distributed optical fiber sensing technology for CO2 injection wells.

Offset VSP acquired with a single-use fiber-optic probe: Gorgon CCS case study

There are many challenges associated with monitoring industrial subsurface CO2 storage. Utilizing a reliable strategy for monitoring and assurance is paramount. Numerous aspects and trade-offs need to be considered when designing a cost-effective monitoring solution that must satisfy regulatory and social licensing requirements and minimize operational complexity. Among various geophysical techniques that are included in the suite of carbon capture and storage (CCS) monitoring programs, seismic surveys provide reliable observations of the deep subsurface. However, active surface seismic techniques are expensive, resulting in significant time separation between surveys (several months or years). Downhole seismic approaches combined with fiber-optic sensing provide flexible options in designing on-demand monitoring strategies. Distributed acoustic sensing offers the opportunity to utilize injection wells for downhole time-lapse seismic imaging and microseismic detection, minimizing the impact on production operations. This paper presents the results of a multioffset vertical seismic profiling survey acquired in CO2 injection wells using bare fibers. The fibers were deployed inside the production tubing through FiberLine Intervention technology developed by Well-SENSE. The test utilized two injection wells for active seismic acquisition. The study took place on Barrow Island (Western Australia) as part of the Gorgon CCS project. The study demonstrates the technological advantages of fast deployment of the sensing fiber and the high quality of acquired seismic data. The paper highlights characteristic noise patterns in the recorded data and suggests approaches to attenuate their effects on seismic image quality. Finally, the impact of survey geometry and directional sensitivity of fiber on the recorded wavefield and the quality of seismic imaging is discussed.

Evaluation method of residual life of casing with corrosion defect in CO2 injection Wells

With the hot development of CCUS project in major oil fields, CO2 flooding technology is also developing continuously. CO2 flooding needs to transform old oil field Wells into CO2 Wells, and the residual life of casing with corrosion defects in old oil Wells needs to be evaluated. To solve this problem, the residual strength of casing with corrosion defects under the combined force is analyzed, and a finite element analysis model is established considering the material nonlinearity. It is found that the temperature difference and axial force will significantly reduce the residual strength of casing. The influence of corrosion rate and pitting pit radius on the residual life of CO2 injection well is discussed. It is found that well H can continue to serve for 13 years after CO2 injection. The research results can provide a theoretical basis for predicting the residual life of CO2 injection Wells in old wells, and ensure the normal production and operation of CO2 injection flooding development.

Enhancing CO2 Injection Efficiency: Rock-Breaking Characteristics of Particle Jet Impact in Bottom Hole

Storing CO2 in oil and gas reservoirs offers a dual benefit: it reduces atmospheric CO2 concentration while simultaneously enhancing oil displacement efficiency and increasing crude oil production. This is achieved by injecting CO2 into producing oil and gas wells. Employing particle jet technology at the bottom of CO2 injection wells significantly expands the bottom hole diameter, thereby improving CO2 injection efficiency and storage safety. To further investigate the rock-breaking characteristics and efficiency, a finite element model for particle jet rock breaking is established by utilizing the smoothed particle hydrodynamics (SPH) method. Specifically, this new model considers the high temperature and confining pressure conditions present at the bottom hole. The dynamic response and fracturing effects of rock subjected to a particle jet are also revealed. The results indicate that particle jet impact rebound significantly influences the size of the impact crater, with the maximum first principal stress primarily concentrated on the crater’s surface. The impact creates a “v”-shaped crater on the rock surface, with both depth and volume increasing proportionally to jet inlet velocity and particle diameter. However, beyond a key particle concentration of 3%, the increase in depth and volume becomes less pronounced. Confining pressure is found to hinder particle impact rock-breaking efficiency, while high temperatures contribute to larger impact depths and breaking volumes. This research can provide theoretical support and parameter guidance for the practical application of particle impact technology in enhancing CO2 injection efficiency at the bottom hole.

Research on the processing and interpretation methods of distributed fiber optic vibration signal logging injection profiles

The oil and gas industry currently faces the dual challenges of improving extraction efficiency and reducing environmental impacts. Traditional well monitoring technologies are increasingly unable to meet the demands of modern oil and gas extraction due to technological limitations and environmental concerns. Distributed Acoustic Sensing (DAS) technology, which utilizes optical fibers as sensing elements, enables real-time and accurate monitoring of the CO2 injection process in wells. However, DAS technology encounters issues such as weak amplitude signals and noise interference in practical applications. In response, a comprehensive method for processing and interpreting DAS logging data for CO2 injection wells has been proposed. This method involves restoring amplitude signals through wavefront energy compensation and applying Gaussian filtering and wavelet threshold denoising algorithms for noise reduction. The processed results are classified using the K-Medoids clustering algorithm and the CO2 absorption volume in the injection layer is calculated using the integral area method. The accuracy and practicality of this method have been validated through comparative analysis with pulse neutron oxygen activation logging results. This approach aims to address the challenges faced by DAS technology in the oil and gas industry, thereby providing technical support for the efficient, environmentally friendly, and intelligent management of oil and gas fields.

Uncertainty Quantification in CO2 Trapping Mechanisms: A Case Study of PUNQ-S3 Reservoir Model Using Representative Geological Realizations and Unsupervised Machine Learning

Evaluating uncertainty in CO2 injection projections often requires numerous high-resolution geological realizations (GRs) which, although effective, are computationally demanding. This study proposes the use of representative geological realizations (RGRs) as an efficient approach to capture the uncertainty range of the full set while reducing computational costs. A predetermined number of RGRs is selected using an integrated unsupervised machine learning (UML) framework, which includes Euclidean distance measurement, multidimensional scaling (MDS), and a deterministic K-means (DK-means) clustering algorithm. In the context of the intricate 3D aquifer CO2 storage model, PUNQ-S3, these algorithms are utilized. The UML methodology selects five RGRs from a pool of 25 possibilities (20% of the total), taking into account the reservoir quality index (RQI) as a static parameter of the reservoir. To determine the credibility of these RGRs, their simulation results are scrutinized through the application of the Kolmogorov–Smirnov (KS) test, which analyzes the distribution of the output. In this assessment, 40 CO2 injection wells cover the entire reservoir alongside the full set. The end-point simulation results indicate that the CO2 structural, residual, and solubility trapping within the RGRs and full set follow the same distribution. Simulating five RGRs alongside the full set of 25 GRs over 200 years, involving 10 years of CO2 injection, reveals consistently similar trapping distribution patterns, with an average value of Dmax of 0.21 remaining lower than Dcritical (0.66). Using this methodology, computational expenses related to scenario testing and development planning for CO2 storage reservoirs in the presence of geological uncertainties can be substantially reduced.

Guest Editorial: The Difference Between CO2 EOR and CCS Injection Well Metallurgy

_ The recent surge in development of CO2 carbon capture and storage (CCS) projects has brought focus on the requirements for corrosion resistance in the injection wells as required by US Environmental Protection Agency (EPA) permitting. In some cases, the long successful history of various metallurgies in enhanced oil recovery (EOR) wells has been cited as sufficient to allow the same completions for CCS injection wells. The lack of actual data on the long-term performance of these alloys in EOR wells in combination with the more stringent requirements for Class VI wells suggests otherwise. Introduction The recent significant influx of large amounts of government incentives for a variety of green initiatives including CCS and CCUS has created a rush to drill and complete CO2 injection wells. However, the necessary corrosion data to make informed choices for corrosion resistance in these wells is minimal at best. Some oil and gas professionals have argued that there is no difference between the more than 40 years of petroleum experience with CO2 EOR and planned CCS wells. This comparison is not a valid one and can be risky considering the need for very long-term containment of CO2 required by regulators. This article presents a comparison between CO2 EOR and CCS for injection well metallurgy and explains why this comparison is invalid. Background and Comparisons There is a 50-year successful history of CO2 EOR in petroleum production that has led to a consensus, largely without merit, that corrosion of injection-well equipment is manageable and does not result in long-term degradation of certain components such as casing. The reason there is little or no merit to applying this experience to CO2 CCS wells is the lack of data specific to the long-term corrosion resistance of casing that remains in the EOR wells. Rather, the industry generally simply plugs these wells with cement, and in the majority of cases without examining the casing before abandoning. Furthermore, industry rarely returns to inspect them after years of abandonment. In a few instances, logging and retrieval of cement cores and casing have been performed and analyzed. For example, analysis of cement and casing from the SACROC field that had been exposed to CO2 for over 30 years showed corrosion along the casing-cement interface (Carey et al. 2007). Laumb et al. (2016) reported substantial casing corrosion for a CO2 EOR well in the Weyburn field based on a series of logs over several years. Koplos et al. (2007) provided survey data from numerous CO2 EOR wells and found that 11.1% of the wells failed mechanical integrity tests and concluded that injection-well mechanical integrity is a concern for CO2 injection and storage due to the corrosivity of CO2 on downhole materials.

A bi-objective optimization approach for carbon capture and storage supply chain network combining with pricing policies: Economic and social aspects

Carbon capture and storage (CCS) technology and pricing policies are two mitigation strategies that attempt to tackle the carbon emission problem. Nonetheless, the uncertainty of public reaction to CCS infrastructure installation has been noted as a significant issue that may lead to either cancelations, delays, or influence the deployment cost of CCS infrastructure. Although these strategies are solutions to reduce carbon emissions, the entire supply chain itself needs to align with sustainability policy. While some previous studies have addressed mitigation strategies or the combination of social objective and CCS technology, the impact of social objectives on reservoir openness has not been explored. This article contributes to the literature by illustrating the effect of social objectives on reservoir openness and the total cost of the CCS supply chain. Through the development of a two-stage mixed-integer linear programming model, we optimize the supply chain network design. In the first stage, a single-objective model minimizes capture, transportation, and sequestration costs along with CO2 emission costs to the atmosphere, considering various carbon tax prices. In the second stage, a bi-objective model maximizes social acceptance towards CO2 injection wells (reservoirs) to analyze the impact of cultural dimensions. Our findings reveal that maximizing the social objective leads to increased costs compared to the economic optimum, and it significantly influences the openness of reservoirs based on cultural dimensions. Furthermore, we demonstrate that an increase in the CO2 tax enhances the amount of captured carbon and the complexity of the pipeline network in the supply chain. This insight has implications for governments and decision-makers who can encourage industries to adopt CCS technology by setting appropriate carbon tax prices. To validate the model, we apply it to a case study in the European Union cement industry, one of the major carbon emitters among all industries. Our results not only confirm the model's effectiveness but also show its potential for practical application. Overall, our study presents a comprehensive framework for designing a two-stage sustainable supply chain network for CCS technology that optimizes economic and social objectives while considering CO2 pricing.

Guidelines for the selection of corrosion resistant alloys for CCS and CCUS injection wells

Carbon capture and sequestration (CCS) and carbon capture utilization and storage (CCUS) projects continue to develop as an effective method to reduce anthropogenic CO2 emissions. Injection wells for these projects are often required to retain integrity over long operational lives, sometimes 50 years or longer. When it is determined from process conditions that free water may or will be present, either condensing from the CO2 injectate itself or due to injection into a water-bearing formation, the need for a corrosion resistant alloy (CRA) is required to ensure sufficiently long service life. For well designers and operators, there is a growing need for comprehensive guidelines for the selection of suitable corrosion resistant alloys (CRAs). This paper summarizes important parameters developed through the Plains CO2 Reduction (PCOR) Partnership that need to be considered for general materials selection for use within CO2 injection wells based on available data.

Lesson learned from the assessment of planned converted CO2 injection well integrity in Indonesia – CCUS project

The risk of CO2 leakage from carbon capture, utilization, and storage (CCUS) wells and geological storage sites must be properly assessed before the implementation of CO2 injection. According to ISO 27914 and ISO/FDIS 27916, the design and construction of an injection well needs to guarantee safety and ability to contain the stored CO2 over a long-term period. However, these standards alone were inadequate to evaluate the well integrity due to the need to specify criteria, duration of measurement, and range of measurement parameters of the available tools according to industries’ best practices.The methodology used in the study adapted applicable and readily-available international standards, field experiences, and lessons learned that could be used to support the construction of new and/or the conversion of existing oil and gas wells into CO2 injection wells. This study focused on Jepon-1 in Gundih field, Indonesia, an abandoned oil and gas well. Its actual conditions, well integrity, capabilities of the equipment used in the workover and logging operations, and its limitations in checking the conditions of various crucial aspects of integrity, were evaluated. The results showed that the application of the international standards could not fulfill all the detailed requirements of integrity evaluation of the JPN-1 well due to its particular condition and situation. Other field experiences needed to be adapted, improved, and incorporated in the integrity evaluation of this well. Additionally, longer duration of measurement and more accurate and sensitive logging evaluation tools, combined with temperature logging tools, are required to detect leakage that could not be identified by the commercial tools used in this well.The result of this well integrity study will be used as a fundamental basis for constructing CCUS well regulations by the Government and stakeholders.

Analytical expression for the skin factor of the salt deposition zone around a CO[formula omitted] injection well: Extension to the case of ternary miscible displacement

Anthropogenic CO2 disposal in saline aquifers is broadly acknowledged a feasible technique to mitigate climate changes. Scale deposition in the near-wellbore region can however reduce the performance of the CO2 injection wells utilized in the subsurface storage. In this study, we aim at evaluating the rate of salt precipitation and deposition and associated permeability reduction near a CO2 injection well completed in a saline aquifer. We employ a mathematical model of the CO2–H2O–NaCl fluid flow in a porous medium and take into account all relevant phase transitions. Then using a rather simple graphical construction with the fractional flow curve, we present a new analytical solution describing a radial flow of CO2 from the well. We demonstrate under certain assumptions that the solution contains two shocks traveling with a characteristic velocity and a rarefaction between them. The leading shock is the familiar Buckley–Leverett displacement front, whereas the trailing shock bounds the region of halite deposition in the near-wellbore region. We consider this region a skin zone and using the analytical solution, eventually derive a new simple relationship for the skin factor. We show that the skin factor caused by the halite deposition is most sensitive to the brine salinity and the relative permeability of the liquid phase. For particular reservoirs, a rather high value of the skin factor can be reached after injecting just several thousand tons of CO2. We show that the injection into reservoirs characterized by a high brine salinity and a large critical water saturation can cause the skin factor to be as high as four at an early stage of injection and as high as seven at a later stage. The proposed relationship can be useful for an instantaneous quantification of the skin and in reservoir simulations of the CO2 storage.

Improved delineation of the Gassum Formation reservoir zones using seismic impedance inversions: implications for exploiting the Stenlille aquifer gas storage facility as a CO 2 storage demonstration site, onshore Denmark

A quantitative seismic interpretation of the Gassum Formation at the onshore aquifer gas storage near the Danish town of Stenlille is presented with its implications for exploiting the gas storage facility as a potential CO 2 demonstration site. Our objective was to better outline the reservoir heterogeneity of the Gassum Formation based on a 3D seismic volume and 20 wells available from the Stenlille gas storage facility. We derived new absolute and relative P-impedance inversion products, which are useful for delineating lithological distributions of thin sandstone reservoirs and shaly beds within the Gassum Formation. Our results broadly agree with previously published seismic interpretations, and build upon these by the identification of deviations in parts of the Gassum interval that should be considered in any subsequent development of a static reservoir model. Hence, this work is an important contribution to the planning of drilling new CO 2 injection wells as part of the development and management of the Stenlille CO 2 storage demonstration site. Nevertheless, we also recommend a modern seismic reprocessing of the 3D seismic data combined with newly acquired 2D data from the Stenlille structure as input into further quantitative seismic interpretation studies to refine reservoir characterization and reduce associated uncertainties. Supplementary material: video is available at https://doi.org/10.6084/m9.figshare.c.6662413

Selecting representative geological realizations to model subsurface [formula omitted] storage under uncertainty

Carbon capture and storage (CCS) is one of the quickest and most effective solutions for reducing carbon emissions. The majority of subsurface storage occurs in saline aquifers, for which geological information is lacking which in turn results in geological uncertainty. To evaluate uncertainty in CO2 injection projections, the use of multiple geological realizations (GRs) has been practiced very commonly. In this approach, hundreds or thousands of high-resolution GRs is used that quickly becomes computationally expensive. This issue can be addressed with representative geological realizations (RGRs) that preserve the uncertainty domain of the ensemble GRs. In this study, we propose the use of unsupervised machine learning (UML) frameworks, including dissimilarity measurement, dimensionality reduction, clustering and sampling algorithms ta select a predetermined number of RGRs. We compare the simulation outputs of the RGR sets and the ensemble using the Kolmogorov–Smirnov (KS) test to select the best UML. The UML frameworks and their associated selection processes are evaluated using a saline aquifer with a single CO2 injection well and 200 GRs with varying uncertain petrophysical characteristics. The best UML framework is selected to use only 5% of the GRs while maintaining the uncertainty domain of the ensemble GRs. In addition, the best UML framework is tested using a saline aquifer with three CO2 injection wells and varied GRs. The results show that our proposed UML framework can be used to choose RGRs, capturing the whole uncertainty domain. Our approach leads to a significant reduction in the computational cost associated with scenario testing, decision-making, and development planning for CO2 storage sites under geological uncertainty.

Optimization of CO2 injection and brine production well placement using a genetic algorithm and artificial neural network-based proxy model

CO2 injection during geological CO2 storage (GCS) can result in large pressure build-ups that can limit the injection and reactivate existing faults. The extraction of resident brine from storage formations can alleviate such pressure rises. One critical challenge in applying an extraction well is determining the optimal well locations with reservoir simulation that could be an accurate approach but computationally inefficient. This work proposes the application of an Artificial Neural Network (ANN)-based proxy model in well-placement optimization problems involving pressure management of GCS. The effectiveness of the proposed approach was assessed by optimizing the placement of the CO2 injection and brine extraction wells in the upper aquifer of the Pohang Basin. Several ANN models with different input features were developed for the optimization study, and the best-performing model on the test data was selected. ANN integrated with a genetic algorithm was used to determine the optimal CO2 injection and brine production well locations that maximize the cumulative CO2 injected. Optimization was demonstrated using a full physics reservoir simulator to verify the results. Six hundred and twenty-two simulation runs were needed to reach the optimal solution using the simulator. Instead, with the proposed workflow, comparable results were achieved with only 120 simulation runs, reducing the number of simulation runs by 80.7%. Employing the ANN-based proxy model in the optimization study proved effective with good accuracy by providing a fast approximation to the full physics reservoir model.

Review of Integrity Loss Detection and Quantification Due to Cracking in Cemented Wells

Summary The loss of well integrity in oil and gas and CO2 injection wells provokes leaks that potentially pollute underground water reservoirs and the surrounding environment. The present publication reviews the existing literature investigating the loss of well integrity due to damage development in the cement sheath, focusing on qualitative and mainly quantitative information regarding cracks, effective permeability, and leak flows. Methods applied for leak detection on-site are reviewed, and the difficulties of these methods in providing quantitative results are highlighted. The outputs of laboratory experiments and computer simulations, considered essential to complement on-site measurements, are also reported. The review of the existing literature shows that for most of the damaged cement sheaths the observed crack widths range between 1 and 500 µm, the permeability ranges from 10−17 to 10−12 m2, and the leak rates range between 10 and 10 000 mL/min for gas leaks and between 1 and 1000 mL/min for oil leaks.

On the suitability of premium OCTG tubing connections for CCS CO2 injection wells – a full scale physical evaluation

Carbon Capture and Underground Storage (CCS) is a rapidly emerging solution to significantly reduce CO2 emissions into the atmosphere. CCS aims to capture CO2 at the emission source and then transport it to an underground permanent storage location. Wells will be used to inject CO2 into these storage locations. The wells are constructed using casing and tubing strings, similar to conventional oil and gas wells. Because the downhole conditions in CCS wells can differ significantly from the conditions in conventional oil and gas wells, suitability of the components needs to be verified. This study addresses the suitability of premium threaded connections for casing and tubing tubulars for CCS wells. An experimental program was executed during which a connection and small-scale samples were exposed to realistic downhole conditions as can occur in CCS wells. No difference of sealability or surface degradation was observed between the tests performed with CO2 at low temperature and tests performed with nitrogen at higher temperatures. Based on these results it is proposed that premium OCTG connections can be used for CCS service, provided the materials are suited for CCS service.

Bayesian averaging sensitivity analysis of reservoir heterogeneity and anisotropy of carbon dioxide assisted gravity drainage of a large clastic oil reservoir

Identifying the specific reservoir properties that influence oil production is an essential part of field development planning. Distinguishing the relative influence of variables and eliminating those that have no influence assists the design of enhanced oil recovery processes. The conventional approach to identify the most influential variables is the multiple linear regression (MLR) step-wise elimination. Bayesian averaging (BA), a stochastic method, offers a novel alternative approach by generating fifty models compared to each other to select the best one with of the most influential parameters based on the highest R2 and posterior probability with the lowest value of Bayesian information criterion (BIC). BA and MLR step-wise elimination are compared in the evaluation of a simulated immiscible carbon dioxide-assisted gravity drainage (CO2-AGD) system applied to the multi-layered, heterogeneous, upper sandstone oil reservoir of the South Rumaila field. A history-matched compositional simulation covering the nearly 57 years of prior production is used for sensitivity analysis of reservoir variables in relation to CO2-AGD implementation over 10 future years with 22 additional CO2 injection wells and 11 new production wells. Oil is displaced downwards towards the new horizontal production wells installed above the oil water contact. The influential variables evaluated are permeability (K), permeability anisotropy (Kv/Kh) and porosity (ɸ) considered separately across multiple heterogeneous reservoir layers. BA and step-wise elimination methods identify K as the most influential variable in all reservoir layers. Kv/Kh is moderately influential in the production layers and underlying water zone but not in injection or transition reservoir layers. ɸ in all reservoir layers has no influence on oil recovery from the CO2-AGD producing wells. More specifically, the BA-based influential parameters were determined after selecting the best model among the fifty generated models. The best model achieved that highest values of R2 of 0.848 and posterior probability of 0.234, and the lowest value of BIC of −149 with 12 identified influential geological parameters across the reservoir layers. Based on validation tests, varying K, Kv/Kh. and ɸ substantially across all reservoir layers confirms these findings and agrees more closely with the BA-derived reduced variable models than those generated by MLR step-wise elimination.

Integrated Study of CO2 Sequestration and CO2-EOR in Oil Reservoir by Compositional Simulation

Now researchers are performing extensive research work to increase the oil and gas production to meet increasing energy demand and to reduce the CO2concentration from atmosphere to reduce global worming.This study is an effort to increase oil production by CO2-EOR from an oil reservoir in Surma basin and to evaluate the oil reservoir as a candidate of CO2 sequestration. The oil reservoir rock is Bhuban sandstone and fluid is heavy oil. High salinity water is also present in the oil reservoir. A compositional reservoir simulation model has been developed for this study. Geo-cellular 3D reservoir grid structure has been constructed by block centered geometry. Reservoir rock properties such as porosity, absolute permeability and net to gross ratio have been modeled using rock properties of Bhuban sandstone. Reservoir oil composition has been determined from liquid chromatograph. Thermodynamic properties of pure components in reservoir oil have been included in the compositional reservoir simulation model. The reservoir has been developed by four CO2 injection wells arranged at the periphery of the reservoir and one oil production well kept at the center of the reservoir. The optimum CO2 injection rate is 500 MSCF/D at pressure 3100 psi by a single well and optimum oil production rate is 4900 STB/D. Dhaka Univ. J. Sci. 70(2): 23-28, 2022 (July)

Optimization of Anti-Plugging Working Parameters for Alternating Injection Wells of Carbon Dioxide and Water

In the process of oilfield development, the use of CO2 can improve the degree of reservoir production. Usually, CO2 is injected alternately with water to expand the spread range of CO2, and CO2 presents a supercritical state in the formation conditions. In the process of alternating CO2 and water injection, wellbore freezing and plugging frequently occur. In order to determine the cause of freezing and plugging of injection wells, the supercritical CO2 flooding test area of YSL Oilfield in China is taken as an example to analyze the situation of freezing and plugging wells in the test area. The reasons for hydrate freezing and plugging are obtained, the distribution characteristics and sources of hydrate near the well are clarified, and a coupling model is established to calculate the limit injection velocity and limit shut-in time of CO2 and water alternate injection wells. The results show that the main reasons for freezing and plugging of supercritical CO2 water alternate injection wells are long time shut down after alternate injection, improper operation when stopping injection and starting and stopping pumps, and slow injection speed during alternate injection. In the process of supercritical CO2 water alternative injection, in the case of post-injection, the CO2 in the formation will reverse diffuse to the injection well end. With the continuous increase of daily water injection, the initial diffusion position and the time of CO2 diffusion to the perforated hole after well shut-in gradually increase. The time of CO2 reverse diffusion to the bottom of the well is 1.6–32.3 d, and the diffusion time in the perforated hole is 1.0–4.5 d. Therefore, the limit shut-in time following injection is 2.6–36.8 d. Following gas injection, the limit shut-in time of a waterproof compound can be divided into three stages according to the change of wellbore pressure: the pressure stabilization stage, pressure-drop stage and formation fluid-return stage. The limit shut-in time of a waterproof compound following gas injection is mainly affected by permeability, cumulative gas injection rate and formation depth. The limit shut-in time of a waterproof compound is 20.0~30.0 days. The research results provide technical support for the wide application of CO2 flooding.

A prediction model for carbonation depth of cement sheath of carbon capture utilization and storage (CCUS) wells

The cement sheath of CCUS well is vulnerable to carbonization corrosion upon protracted exposure to a CO2-rich setting, which reduces the strength of the cement sheath and increases the porosity, eventually leading to CO2 leakage. Predicting the carbonation depth and regularity of the cement sheath of CO2 injection wells allows an estimation of the service life , to ensure safe operation of CO2 injection wells. However, most of the current prediction models for CO2 corrosion depth are still semi-empirical models, which are fitted to experimental data but are not universally applicable. This may be resolved by our CO2 corrosion depth prediction model supported by the law of mass conservation, diffusion convection equation, and calcium precipitation rate. The influence of seven factors on the corrosion depth was analyzed and ranked. The rise in corrosion time, temperature, chloride ion content, CO2 partial pressure, water-cement ratio, and water saturation increases corrosion depth and CO2 content, in addition to porosity and permeability, while increasingly corrosion-resistant material causes the opposite effect. The cement sheath begins to be seriously corroded by CO2 partial pressure exceeding 10 MPa, chloride ion content over 0.20 mol/L, or temperature higher than 70 °C. Water saturation significantly affects corrosion, and the CO2 corrosion depth at 0.8 is 10.16 times that at 0.6. The CO2 content at the distance of 0.2 m–0.93 m from the corroded end surface basically does not change after 7 years of corrosion. Water-cement ratio increased to 0.48 provides conditions for a large amount of CO2 accumulation in the cement sheath. The addition of corrosion-resistant materials can reduce the initial porosity and permeability of cement sheath. The seven factors is ranked in descending order of influence as water saturation, corrosion-resistant material, water-cement ratio, CO2 partial pressure, corrosion time, chloride ion content, and temperature.