FeCO3 Mineralization and Solubility – A Guiding Factor CO2 Corrosion and Storage

Marine oil pipelines are critical for the transportation of oil and gas from offshore production facilities to onshore processing plants. However, exposure to seawater, salt, and other environmental factors can cause corrosion in these pipelines, which can lead to costly and dangerous leaks and spills. Therefore, predicting and managing corrosion in marine oil pipelines is essential for ensuring safe and efficient operation. Uniform/general corrosion, pitting corrosion, and microbiologically influenced corrosion (MIC) are the most common forms of corrosion found in marine oil pipelines. These corrosion mechanisms can lead to thinning of the pipe walls and the formation of pits, which can significantly weaken the structure of the pipeline. To detect and monitor corrosion in marine oil pipelines, various in-line inspection (ILI) tools are available. Some of the most commonly used ILI tools for marine pipelines include magnetic flux leakage (MFL)[1], ultrasonic thickness measurement (UTM), and eddy current inspection (ECI). However, the existing tools are not efficient because of low accuracy. Therefore, a corrosion rate model was developed for the future rate of corrosion in marine oil pipelines. The developed model accounts for various factors such as line diameter, line temperature, line pressure, CO2 concentration, H2S concentration, Volatile fatty acid concentration, Bacteria count(SRBs), Material of construction, service life, bicarbonate ion concentration, chloride ion concentration, sulphate ion concentration, pH, clamp/repair history and details, oil, water and gas flow rate, flow velocity and regime, Inhibitor/biocide frequency, Oil characteristics and Kinetics of reaction to estimate the expected corrosion rate over a given time period [2]. Also the developed model combines the both linear corrosion growth rate, and non-linear corrosion growth rate. The model was trained on historical data of corrosion rates for different conditions and validated on new data to ensure accuracy. Additionally, the model could be updated in real-time with sensor data from the pipeline, allowing for continuous monitoring and prediction of corrosion rates. This could help operators proactively manage and maintain the pipeline to prevent corrosion-related failures and minimize downtime. A validation study was conducted on the developed model using a dataset of real-world pipeline corrosion data. The model was trained on a subset of the data and tested on a separate subset. The results showed a high level of accuracy, with an overall accuracy of 96%. This level of accuracy suggests that the model is reliable and can be used to inform pipeline integrity management and planning with a high degree of confidence.

Limits to Paris compatibility of CO2 capture and utilization

Predicting CO2 corrosion in fluid transmission pipelines is crucial for oil/gas company in upstream applications. This paper applies Light Gradient Boosting Machine (LightGBM) and Multiple Layer Perceptron Neural Network (MLPNN) models for the prediction of CO2 corrosion in aqueous pipelines with different pipe bending angles. To build the predictive models, a data set with total of 77,745 data points was generated parametrically by a computational fluid dynamics (CFD) model. Since different environmental conditions and geometries of the pipeline may cause non-uniform corrosion, a total of seven variables, including flow velocity, pH value, CO2 concentration, pipe inner diameter, pipe bend angle, radius and temperature are taken as the input features with the corrosion rate as the target variable. The CFD model was then used to compute the electrochemical processes occurring at the metal surfaces to predict the corrosion rate. Knowing that these features have nonlinear relationship with the target, tree based LightGBM, and neural network based MLPNN were chosen. LightGBM can control the overfitting issues, deal with comparative scales of the features and learn non-linear decision boundaries via boosting. The most significant findings are that these two types of machine learning (ML) algorithms have higher efficiency and can predict new results in microseconds in contrast to hours or even days using CFD. The R square of the LightGBM model is 0.9985, which is slightly higher than that of the MLPNN model at 0.9931. The k-fold cross validation results also show the stability of the two models. These ML models are 5 to 6 orders of magnitude faster than CFD models with similar accuracy therefore significantly saving time and cost. We further built a web application based on these predictive models as a tool for pipeline design and monitoring applications.

Carbon Capture and Storage (CCS) euphoria is turning the oil and gas operations upside down, without having any perceptible impact on atmospheric carbon dioxide (CO2) that continues to increase. It is intended to show that the current CCS regimen has serious technical and fiscal constraints, and questionable validity. Carbon Capture, Storage, and Utilization (CCUS) is also discussed briefly. There is ample data to show that the CO2 concentration in the atmosphere is unrelentingly increasing, and the annual global CCS is about 0.1% of the 40 billion tonnes emitted. As much as 30% of the carbon dioxide captured is injected/re-injected into oil reservoirs for oil production and is not CCS at all. Several CCS methods are being tested, and some are implemented in dedicated plants in the world. A number of impediments to CO2 capture are identified and limited remedies are offered. It is shown that the problem is so gigantic and has so many dimensions that limited solutions have little efficacy. For example, about one-half of the world's population lives at less than $5 a day and has no recourse to CCS technologies. Major facets of the CCS problem are: (1) Validity of the future atmospheric CO2 concentrations based on the 100+ climate models for global warming. This is not the main discussion but is touched upon. (2) Impact of the desired CO2 concentrations on coal, oil, and gas production. (3) Principal CCS methodologies, including Direct Air Capture. (4) CCS vis-à-vis carbon tax, carbon credits, and carbon trading. (5) CCS subsidies – Is CSS workable without subsidies? At this time, No. The current tax credits for CCUS do not make sense. Finally, attention is given to CCS on a world scale – showing that so long as the great disparities in the living standards exist, CCS cannot be achieved to any significant level. All of the above is seen against the backdrop of oil and gas production and achieving Net Zero. It is shown that globally CCS has not increased beyond ∼0.1% of the global CO2 emissions in the past 20 years. The problem is that in CCS, there is injection only, no production! The paper offers partial solutions and concludes that oil and gas will continue to be energy sources far beyond the foreseeable future, and oil companies will accomplish the needed CSS.

Pipelines widely used for the transportation of varying fluids from one place to another should be maintained in good condition to avoid, if possible, the occurrence of corrosion in pipelines to keep its reliability in terms of fracture and damage. The reliability of buried pipelines with corrosion defects is estimated using the failure probability. The FORM (first order reliability method) is utilized to estimate the failure probability of buried pipeline with various formulas for external stress in pipe and three different corrosion models. In this paper, it is recognized that the failure probability increases not only with increasing exposure time, operating pressure and diameter of pipe but also with decreasing wall thickness and yield stress of pipe material in three different corrosion models. And the effects of the scattering of random variables regarding reliability of pipelines on failure probability are investigated, systematically. Furthermore, the target safety level is used to determine the level of safe of corroded pipeline and the effects of varying boundary conditions on target safety level are also estimated.

Uncertainty analysis is a key element of sound techno-economic analysis (TEA) of CO2 Capture and Storage (CCS) technologies and systems, and in the communication of TEA results. Many CCS technologies are relatively novel, with only few large-scale projects constructed and in operation to date. Therefore, uncertainties in technology performance and costs are often substantial, making it imperative that they be characterized and reported. Although uncertainty analysis itself is not novel, with some methods already frequently used by the CCS TEA community, a document that provides a comprehensive overview of methods and approaches, as well as guidance on their selection and use, is still lacking. Given its importance, we seek to fill this gap by providing a critical review of uncertainty analysis methods along with guidance on the selection and use of these methods for CCS TEAs, highlighting good practice and examples from the CCS literature. The paper starts by identifying the different audiences for CCS TEAs, the different modelling approaches available for CCS technology performance and cost analysis, and the different roles that uncertainty analysis may play. It then continues to discuss established, as well as emerging, uncertainty analysis methods and addresses how and when each method is best used, as well as common pitfalls. We argue that the most commonly used method of one-parameter-at-a-time ‘local’ sensitivity analysis may often be a suboptimal choice, and that other approaches may be more suitable or lead to more insight, especially since uncertainty analysis software is becoming more widespread and easier to use. Finally, the paper discusses the benefits of advanced uses of uncertainty analysis in, for instance, the design of CCS experiments or in the design and planning of CCS infrastructure. Sound uncertainty analysis has an important role to play in TEAs of CCS technologies and systems, and there are many opportunities to bring the use of uncertainty analysis to a higher level than currently practiced. This review of and guidance on available methods is intended to help accelerate continued methods development and their application to more robust and meaningful CCS performance and costing studies.

The last decade has seen a significant increase in the research and development of CO2 capture and storage (CCS) technology. CCS is now considered to be one of the key options for climate change mitigation. This perspective provides a brief summary of the state of the art regarding CCS development and discusses the implications for the further development of CCS, particularly with respect to climate change policy. The aim is to provide general perspectives on CCS, although examples used to illustrate the prospects for CCS are mainly taken from Europe.The rationale for developing CCS should be the over‐abundance of fossil fuel reserves (and resources) in a climate change context. However, CCS will only be implemented if society is willing to attach a sufficiently high price to CO2 emissions. Although arguments have been put forward both in favor and against CCS, the author of this perspective argues that the most important outcome from the successful commercialization of CCS will be that fossil‐fuel‐dependent economies will find it easier to comply with stringent greenhouse gas (GHG) reduction targets. In contrast, failure to implement CCS will require that the global community agrees almost immediately to start phasing out the use of fossil fuels; such an agreement seems more unrealistic than reaching a global agreement on stringent GHG reductions. Thus, in the near term, it is crucial to initiate demonstration projects, such as those supported by the EU. If this is not done, there is a risk that the introduction of CCS will be significantly delayed. Among the stakeholders in CCS technologies (R&D actors in industry and academia), the year 2020 is typically considered to be the year in which CCS will be commercially available. Considering the lead times for CCS development and the slow pace of implementation of climate policy (post‐Copenhagen), the target year of 2020 seems rather optimistic. © 2011 Society of Chemical Industry and John Wiley & Sons, Ltd

Effects of sub-seabed CO2 leakage: Short- and medium-term responses of benthic macrofaunal assemblages

Infrastructure development is currently taking place rapidly. Designing a dwelling or premises is currently implemented quickly while controlling construction costs in addition to providing guidance on planned development. The architecture uses steel as a main part of the pile and drainage system is connected from sources to consumer. This study focuses on steel pipes that are exposed to corrosion. This problem is considered serious because steel pipes are used not only for the delivery of water supply but also for the delivery of gas and oil to the oil and gas sector, where the same problem occurs. Impacts of the problem of corrosion of steel pipes contribute to the risk of loss to the owner of the premises or industry. An overview of leakage problems, which cause a reduction in the volume of materials or hazards to the environment and consumers, is given, and the occurrence of corrosion in pipelines is evaluated. Monitoring methods use ultrasonic tomography as a major contribution to the implementation of monitoring and assessing the status of pipe durability and ability. This paper looks at the concept of diverse ultrasonic tomography inventions used to assist the process of monitoring of the level of pipeline capacity that will suffer corrosion.

Pertamina Hulu Energi - Offshore North West Java, also known as PHE-ONWJ, owns 426 subsea pipelines from which only 185 are active operating to support PHE-ONWJ's production activity and the rest, 241 pipelines, are inactive which status is either remain idle or being preserved. Need to be noted that 67% or 284 pipelines aged more than 30 years, which is more than its design life. From which, 120 pipelines are still actively operating distributing fluids such as Oil, Gas and 3-phase. Multiple events of leak have occurred which implicates PHE-ONWJ's production activity. Based on observation, more than 90% of leak events occurred, were caused by internal corrosion. The specific cause is that PHE-ONWJ pipelines transports such fluids that contains corrosive agents such high CO2 content, sands or solid particles, SRB and water. The existing integrity management plan such as in-line inspection, fluid sampling, chemical injection and others have been performed onto several pipelines. However, since the size of PHE-ONWJ's pipeline network facility is complex and massive, to perform in-line inspection to all pipelines is not economically beneficial. Moreover, performing in-line inspection induced high risk and not all of the pipelines are piggable either because of its design or operating condition. Therefore, by considering such conditions mentioned previously, an effective and efficient pipeline integrity management developed based on corrosion rate prediction from topside piping within corrosion circuit with pipeline. It is clear unwanted event such leak shall interrupt PHE-ONWJ production activity, moreover the age of most pipeline facility are old which means it has probability to fail, even though not all leak event associated with the age of the pipeline. To maintain and predict failure event such as leak or even rupture, a corrosion model has been developed. This model is constructed from combining several parameters which are; fluid sampling, In-Line Inspection of several pipelines with different services, Topside piping inspection data, Operating history and pipeline design data. The model generated in the form of an equation that associates topside piping corrosion rate and pipeline corrosion rate which both were obtained from inspection data and the boundary is operating and design history of the pipeline itself. The developed model or equation is continuously validated as In-Line Inspection (ILI) performed onto several pipelines that previously has been assessed by using the internal corrosion model. Since the model developed, an accuracy ranging from 80-99% has been achieved in predicting maximum internal corrosion rate of PHE-ONWJ's pipeline. Which later on, this corrosion model become as a basis in determining pipeline's integrity status, remaining life and assisted in assessing the pipeline risk which outcome are mitigation / action plan. All of these were obtained by only using topside inspection data. Even though the corrosion model developed is able to represent PHE-ONWJ's pipeline internal corrosion rate, further study should be done to be applicable onto other facility or even company pipelines. Therefore, a joint study may be made to create such corrosion model for pipelines. The goal is to have an in-depth approach in managing matured and unpigable pipeline integrity that operates across the world with such effectiveness and ensure all stakeholders that the pipeline is safe to operate.

Carbon capture and storage (CCS) technology is an important way to slow down the continuous increase in atmospheric CO2 concentration and to achieve the dual carbon target. Carbon capture and storage through biomass ash is a secure, permanent, and environment friendly way. To better understand the characteristics of biomass ash carbon capture and storage, we summarized progresses on biomass ash carbon capture and storage, clarified the mechanisms of biomass ash carbon sequestration, analyzed the influencing factors, and explored its applications in various domains. The capacity of CCS by biomass ash mainly derived from alkaline earth metal oxides of CaO and MgO. The actual carbon sequestration efficiency is affected by factors such as biomass source, chemical composition, temperature, humidity, pressure, and CO2 concentration. However, the underlying mechanism is unclear. The CCS capacity of biomass ash significantly impacts its potential applications in building materials reuse, soil quality improvement, and adsorbents carbon capture and storage absorbent preparation. Long-term research is critically needed. For future studies, we should strengthen the research on the carbonization efficiency of biomass ash from multiple sources, establish a database related to the impact of biomass ash carbonization, build a methodological system to promote scientific management of biomass ash, develop biomass ash carbon capture and storage technologies, and quantitatively assess its role in carbon sequestration.

Oil and gas production in FPSOs (floating, production, storage, and offloading) faces a dual challenge: meeting variation in energy demand while decreasing its negative environmental impact. The present article integrates thermodynamic analysis of oil and gas processing plants and screening analysis to determine the most important operational parameters to lower energy demand and increase efficiency and production. Therefore, the main goals of this study are to identify the contribution of the total effect of the operating parameters in an FPSO with CCUS (CO2 capture, utilization, and storage). Twenty-seven thermodynamic and structural design variables are selected as input parameters for the sensitivity analyses. Four machine learning-based screening analysis algorithms such as smooth spline-analysis of variance (SS-ANOVA), PAWN, gradient boosting machine (GBM), and Morris are adapted to achieve the following objectives: (1) overall power consumption of FPSO, (2) CO2 removal efficiency of carbon capture and storage (CCS), (3) power consumption of CCS, and (4) total oil production. The influence of three real crude oil compositions with variations in gas–oil ratio (GOR) and CO2 content is assessed. The combination of thermodynamic and screening analyses showed that the optimal operating pressure parameters of CCS significantly reduce the energy consumption and exergy destruction of the key main and utility plants. Furthermore, the results indicated that total power consumption, CCS efficiency, and CCS power consumption are much more sensitive to the CO2 content of the fluid reservoir than GOR, while the total oil production is influenced only by the GOR content. Finally, for scenarios with high CO2 or GOR content, the effect of design variable interactions is decisive in changing the separation efficiency and/or the compression unit performance.

Carbon Capture and Storage (CCS) has been highlighted as a potential method to enable the continued use of fossil-fuelled power stations through the abatement of carbon dioxide (CO2). A complete CCS cycle requires safe, reliable and cost effective solutions for the transmission of CO2 from the capturing facility to the location of permanent storage. This publication presents a detailed review of the integrity risks posed to dense-phase CO2 pipelines in the form of internal corrosion. To begin, the current worldwide experience in handling dense-phase CO2 and the anthropogenic stream compositions expected from the different combustion techniques currently available are discussed. The anticipated compositions are then related to a number of tentative CO2 stream compositions available in open literature proposed by research institutes and pipeline operators. In subsequent sections, early laboratory and field corrosion experience relating to natural dense-phase CO2 transport for the purposes of enhanced oil recovery (EOR) are summarised along with more recent research efforts which focus on identifying the role of anthropogenic impurities in the degradation processes. For each system impurity, the reaction rates, mechanisms and corrosion product composition/morphology expected at the steel surfaces are discussed, as well as each component’s ability to influence the critical water content required to initiate corrosion. Potential bulk phase reactions between multiple impurities are also evaluated in an attempt to help understand how the impurity content may evolve along a long-distance pipeline. The likelihood of stress-corrosion cracking and hydrogen-induced cracking is discussed and the various corrosion mitigation techniques which exist to control degradation to acceptable levels are reviewed. Based on the current research performed in the context of impure dense-phase CO2 corrosion, issues associated with performing laboratory experiments to replicate field conditions and the challenges such limitations present in terms of defining the safe operating window for CO2 transport are considered.

The corrosion of oil and gas pipelines represents a significant factor influencing the safety of these pipelines. The extant research on intelligent algorithms for assessing corrosion rates in pipelines has primarily focused on static evaluation methods, which are inadequate for providing a comprehensive dynamic evaluation of the complex phenomenon of corrosion in buried oil and gas pipelines. This paper proposes a novel approach to predicting the corrosion rate of buried oil and gas pipelines. The method is based on the combination of an improved Beluga Optimization algorithm (IBWO) and Random Forest (RF) optimization with BiLSTM and gated cycle unit (GRU), which are used to classify corrosion rates as high or low. Initially, a feature screening of corrosion factors was conducted via RF, whereby variables exhibiting a strong correlation were extracted. Subsequently, IBWO was employed to optimize the feature selection process, with the objective of identifying the optimal feature subset to enhance the model’s performance. Ultimately, the BiLSTM method was employed for the purpose of predicting the occurrence of low corrosion. A GRU method was employed for prediction in the context of high corrosion conditions. The RF–IBWO-BiLSTM–GRU model constructed in this paper demonstrates high prediction accuracy for both high and low corrosion rates. The verification of 100 groups of experimental data yielded the following results: the mean square error of this model is 0.0498 and the R2 is 0.9876, which is significantly superior to that of other prediction models. The combined model, which incorporates an intelligent algorithm, is an effective means of enhancing the precision of buried pipeline corrosion rate prediction. Furthermore, it offers a novel approach and insight that can inform subsequent research on the prediction of corrosion rates in buried oil and gas pipelines.

_ This article, written by JPT Technology Editor Chris Carpenter, contains highlights of paper SPE 214950, “Limitations and Fallacies of Carbon Capture and Storage and Impact on Oil and Gas Production,” by S.M. Farouq Ali, SPE, and Mohamed Y. Soliman, SPE, University of Houston. The paper has not been peer reviewed. _ In the complete paper, the authors write that, while carbon capture and storage (CCS) initiatives are affecting oil and gas operations profoundly, such efforts have had little perceptible effect on atmospheric CO2, which continues to increase. The paper aims to show that current CCS regimens have serious technical and fiscal constraints and questionable validity, stating that, globally, CCS has not increased beyond approximately 0.1% of global CO2 emissions in the past 20 years. The paper offers partial solutions and concludes that, while oil and gas will continue to be important energy sources beyond the foreseeable future, oil companies will accomplish the needed CCS. Introduction The authors write that, while CCS efforts have been pursued for 4 decades, little has been achieved. For the past 20 years, the percentage of CO2 captured and stored is less than 0.1% of the CO2 emitted worldwide, if one considers CO2 enhanced oil recovery (EOR) projects to be CSS—which, the authors write, is a fallacy. They emphasize that CCS means injection with no production. The key to CCS success, they write, is major governmental subsidization, by whatever terminology it is known, and that means taxpayer money. Sweeping decisions that have a profound effect on oil and gas production and petroleum engineering education are being made based on predictions of an increase in CO2 concentration in the atmosphere in various time frames. Magnitude of the Problem The problem of world CO2 emissions capture is gigantic. To appreciate the magnitude of the problem, imagine that 1 year’s CO2 emissions (40 billion tonnes) are captured, compressed and liquified, and injected into a reservoir the size of the Ghawar oil field, the largest reservoir in the world, with the entire pore space (approximately 0.5 Tcf) available for storage. In this hypothetical, nine such reservoirs would be required every year. Presumably, such storage space can be found, but collecting the CO2 and bringing it to a storage site is a highly complex task. For example, in a sequestration effort in a building complex in New York, the CO2 is separated, liquified, and trucked to a storage site to be injected underground, which is impractical. Often, the example of the Nordic countries (mainly Denmark, Sweden, and Norway) is cited as evidence of successful emissions reduction. But the total population of these countries is approximately the same as that of metropolitan Mumbai in India. Definitions Carbon capture use and storage (CCUS) implies that the CO2 produced by various processes is captured and used for EOR. This accounts for approximately 30% of the 230 mtpa of CO2 captured globally. CCS means that any CO2 produced by the process is captured and injected into a suitable geological formation for storage for thousands of years. Net-zero emissions (NZE) implies that all the CO2 produced is captured and stored. In Canada, “absolute zero emissions” is discussed, meaning that no CO2 is produced in the first place, pointing to total fossil-fuel phaseout.