VULNERABILITY ASSESSMENT OF CRITICAL OIL AND GAS INFRASTRUCTURES TO CLIMATE CHANGE IMPACTS IN THE NIGER DELTA

Oil and gas infrastructures are being severely impacted by extreme climate change-induced disasters such as flood, storm, tidal surges, and rising temperature in the Niger Delta with high. There is a high potential for disruption of upstream and downstream activities as the world climate continues to change. The lack of knowledge of the criticality and vulnerability of infrastructures could further exacerbate impacts and the assets management value chain. This thesis, therefore, applied a criteria-based systematic evaluation of the criticality and vulnerability of selected critical oil and gas infrastructure to climate change impacts in the Niger Delta. It applied multi-criteria decision-making analysis (MCDA) tool – analytic hierarchy process (AHP), in prioritising systems according to their vulnerability and criticality and recommended sustainable adaptation mechanisms. Through a critical review of relevant literature, seven (7) criteria each for criticality and vulnerability assessment were synthesised accordingly and implemented in the assessment process. A further exploratory investigation, physical examination of infrastructures, focus groups and elite interviews were conducted to identify possible vulnerable infrastructures and scope qualitative and quantitative data for analysis using Mi-AHP spreadsheet. Results prioritised the criticality of infrastructures in the following order: terminals (27.1%), flow stations (18.5%), roads/bridges (15.5%), and transformers/high voltage cables (11.1%) while the least critical are loading bays (8.6%) and oil wellheads (5.1%). Further analysis indicated that the most vulnerable critical infrastructures are: pipelines (25%), terminals (17%) and roads/bridges (14%) while transformers/high voltage cables and oil wellheads where ranked as least vulnerable with 11% and 9% respectively. In addition to vulnerability assessment, an extended documentary analysis of groundwater geospatial stream flow and water discharge rate monitoring models suggest that an in-situ rise in groundwater level and increase in water discharge rate (WDR) at the upper Niger River could indicate a high probability of flood event at the lower Delta, hence further exacerbates the vulnerability of critical infrastructures. Accordingly, physical examination of infrastructures suggests that an increase in regional and ambient temperature disrupts the functionality of compressors and optimal operation of Flow Stations and inevitably exacerbate corrosion of cathodic systems when mixed with the saltwater flood from the Atlantic. The thesis produced a flexible conceptual framework for the vulnerability assessment of critical oil/gas infrastructures, contextualised and recommended sustainable climate adaptation strategies for the Niger Delta oil/gas industry. Some of these strategies include installation of industrial groundwater and water discharge rate monitoring systems, construction of elevated platforms for critical infrastructures installations, substitution of cathodic pipes with duplex stainless and glass reinforcement epoxy pipes. Others include proper channelisation of drainages and river systems around critical platforms, use of unmanned aerial vehicles (UAVs) for flood monitoring and the establishment of inter-organisational climate impact assessment groups in the oil/gas industry. Climate impact assessment (CIA) is suggested for oil and gas projects as part of best practice in the environmental management and impact assessment framework

Mathematical Fuzzy Logic in the Emerging Fields of Engineering, Finance, and Computer Sciences

Mathematical fuzzy logic (MFL) specifically targets many-valued logic and has significantly contributed to the logical foundations of fuzzy set theory (FST). It explores the computational and philosophical rationale behind the uncertainty due to imprecision in the backdrop of traditional mathematical logic. Since uncertainty is present in almost every real-world application, it is essential to develop novel approaches and tools for efficient processing. This book is the collection of the publications in the Special Issue “Mathematical Fuzzy Logic in the Emerging Fields of Engineering, Finance, and Computer Sciences”, which aims to cover theoretical and practical aspects of MFL and FST. Specifically, this book addresses several problems, such as:- Industrial optimization problems- Multi-criteria decision-making- Financial forecasting problems- Image processing- Educational data mining- Explainable artificial intelligence, etc

Subsea fluid sampling to maximise production asset in offshore field development

The acquisition of representative subsea fluid sampling from offshore field development asset is crucial for the correct evaluation of oil reserves and for the design of subsea production facilities. Due to rising operational expenditures, operators and manufacturers have been working hard to provide systems to enable cost effective subsea fluid sampling solutions. To achieve this, any system has to collect sufficient sample volumes to ensure statistically valid characterisation of the sampled fluids. In executing the research project, various subsea sampling methods used in the offshore industry were examined and ranked using multi criteria decision making; a solution using a remote operated vehicle was selected as the preferred method, to compliment the subsea multiphase flowmeter capability, used to provide well diagnostics to measure individual phases – oil, gas, and water. A mechanistic (compositional fluid tracking) model is employed, using the fluid properties that are equivalent to the production flow stream being measured, to predict reliable reservoir fluid characteristics on the subsea production system. This is applicable even under conditions where significant variations in the reservoir fluid composition occur in transient production operations. The model also adds value in the decision to employ subsea processing in managing water breakthrough as the field matures. This can be achieved through efficient processing of the fluid with separation and boosting delivered to the topside facilities or for water re-injection to the reservoir. The combination of multiphase flowmeter, remote operated vehicle deployed fluid sampling and the mechanistic model provides a balanced approach to reservoir performance monitoring. Therefore, regular and systematic field tailored application of subsea fluid sampling should provide detailed understanding on formation fluid, a basis for accurate prediction of reservoir fluid characteristic, to maximize well production in offshore field development

Managing, Controlling And Improving The Treatment Of Produced Water Using The Six Sigma Methodology For The Iraqi Oil Fields

Produced Water (PW) is the largest volume of waste that is normally generated during oil and gas production. It has large amounts of contaminants that can cause negative environmental and economic impacts. The management method for PW relies highly on types and concentrations of these contaminants, which are field dependent and can vary from one oil field to another. Produced water can be converted to fresh water if these contaminants are removed or reduced to the acceptable drinking water quality level. In addition, increasing oil production rate and reducing amounts of discharged harmful contaminants can be achieved by removing dissolved hydrocarbons from PW. In order to identify the types of these contaminants, effective tools and methods should be used. Six Sigma, which uses the DMAIC (Define- MeasureAnalyze- Improve- Control) problem-solving approach is one of the most effective tools to identify the root causes of having high percentages of contaminants in produced water. The methodology also helped develop a new policy change for implementing a way by which this treated water may be used. Six Sigma has not been widely implemented in oil and gas industries. This research adopted the Six Sigma methodology through a case study, related to the southern Iraqi oil fields, to investigate different ways by which produced water can be treated. Research results showed that the enormous amount of contaminated PW could be treated by using membrane filtration technology. In addition, a Multi Criteria Decision Making (MCDM) framework is developed and that could be used as an effective tool for decision makers. The developed framework could be used within manufacturing industries, services, educational systems, governmental organizations, and others. iv This work is dedicated to my scholarship providers and supporters wi

An analysis for providing safety in the cooking oil production process through FMECA approach

This study attempts to apply Failure Mode Effects and Criticality Analysis (FMECA) to improve the safety of production system, espe-cially on the production process of an oil company in Indonesia. Since food processing is a worldwide issue and the self management of a food company is more important than relying on government regulations, so the purpose of this study is to identify and analyze the criticality of potential failure mode on the production process, then take corrective actions to minimize the probability of making the same failure mode and re-analyze its criticality. This corrective actions are compared with the before improvement condition by testing the significance of the difference between before and after improvement using two sample t-test. Final result that had been measured is Criticality Priority Number (CPN), which refers to severity category and probability of making the same failure mode. Recommended actions that proposed on the part of FMECA give less CPN significantly compare with before improvement, with increment by 48.33% on coconut cooking oil case study

Econometric framework for electricity infrastructure modernization in Saudi Arabia, An

2017 Summer.Includes bibliographical references.The electricity infrastructure in Saudi Arabia is facing several challenges represented by demand growth, high peak demand, high level of government subsidies, and system losses. This dissertation aims at addressing these challenges and proposing a multi-dimensional framework to modernize the electricity infrastructure in Saudi Arabia. The framework proposes four different scenarios—identified by two dimensions—for the future electric grid. The first and second dimensions are characterized by electricity market deregulation and Smart Grid technologies (SGTs) penetration, respectively. The framework analysis estimates global welfare (GW) and economic feasibility of the two dimensions. The first dimension quantifies the impact of deregulating the electricity market in Saudi Arabia. A non-linear programming (NLP) algorithm optimizes consumers surplus, producers surplus, and GW. The model indicates that deregulating the electricity market in Saudi Arabia will improve market efficiency. The second dimension proposes that allowing the penetration of SGTs in the Saudi electricity infrastructure is expected to mitigate the technical challenges faced by the grid. The dissertation examines the priorities of technologies for penetration by considering some key performance indicators (KPIs) identified by the Saudi National Transformation Program, and Saudi Vision 2030. A multi-criteria decision making (MCDM) algorithm—using the fuzzy Analytic Hierarchy Process (AHP)—evaluates the prioritization of SGTs to the Saudi grid. The algorithm demonstrates the use of triangular fuzzy numbers to model uncertainty in planning decisions. The results show that advanced metering infrastructure (AMI) technologies are the top priority for modernizing the Saudi electricity infrastructure; this is followed by advanced assets management (AAM) technologies, advanced transmission operations (ATO) technologies, and advanced distribution operations (ADO) technologies. SGTs prioritization is followed by a detailed cost benefit analysis (CBA) conducted for each technology. The framework analysis aims at computing the economic feasibility of SGTs and estimating their outcomes and impacts in monetary values. The framework maps Smart Grid assets to their functions and benefits to estimate the feasibility of each Smart Grid technology and infrastructure. Discounted cash flow (DCF) and net present value (NPV) models, benefit/cost ratio, and minimum total cost are included in the analysis. The results show that AAM technologies are the most profitable technologies of Smart Grid to the Saudi electricity infrastructure, followed by ADO technologies, ATO technologies, and AMI technologies. Considering the weights resulting from the fuzzy AHP and the economic analysis models for each infrastructure, the overall ranking places AAM technologies as the top priority of SGTs to the Saudi electricity infrastructure, followed by AMI technologies, ADO technologies, and ATO technologies. This dissertation has contributed to the existing body of knowledge in the following areas: • Proposing an econometric framework for electricity infrastructure modernization. The framework takes into account technical, economic, environmental, societal, and policy factors. • Building an NLP algorithm to optimize a counterfactual deregulation of a regulated electricity market. The algorithm comprises short run price elasticity of electricity demand (ε), level of technical efficiency improvement, and discount rate (r). • Proposing an MCDM model using AHP and fuzzy set theory to prioritize SGTs to electricity infrastructures. • Adapting a Smart Grid asset-function-benefit linkage model that maps SGTs to their respected benefits. • Conducting a detailed CBA to estimate the economic feasibility of SGTs to the Saudi electricity infrastructure, This work opens avenues for more analysis on electricity infrastructure modernization. Measuring risk impact and likelihood is one area for future research. In fact, risk assessment is an important factor in determining the economic feasibility of the modernization. Probabilistic economic analysis can be applied to assess the risk associated with the implantation of the previously mentioned dimensions. The parameters used for the economic analysis, such as economic life of a project, and the discount rate, are usually deterministic. However, a probabilistic method can be applied to capture the uncertainty of the parameters. Another area for future research is the integration of both dimensions into one model in which GW resulted from market deregulation and SGTs insertion are summed

Mapping oil spill human health risk in rivers state, Niger Delta, Nigeria

Oil pipelines play a significant role in crude oil transportation and bring danger close to communities along their paths. Pipeline accidents happen every now and then due to factors ranging from operational cause to third party damage. In the Niger Delta pipeline system, interdiction is common; therefore, every length and breadth of land covered by a pipeline is vulnerable to oil pollution, which can pose a threat to land use. Weak enforcement of rights of way led to encroachment by farmers and human dwellings, thereby bringing people in close proximity to pipelines. Considering the impact exposure can have on human health, a method was developed for identifying vulnerable communities within a designated potential pipeline impact radius, and generic assessment criteria developed for assessing land use exposure. The GIS based model combines four weighted criteria layers, i.e. land cover, population, river and pipeline buffers in a multi-criteria decision making with analytical hierarchy process to develop an automated mapping tool designed to perform three distinct operations: firstly, to delineate pipeline hazard areas; secondly, establish potential pipeline impact radius; and thirdly, identify vulnerable communities in high consequence areas. The model was tested for sensitivity and found to be sensitive to river criterion; transferability on the other hand is limited to similar criteria variables. To understand spatial distribution of oil spills, 443 oil spill incidents were examined and found to tend towards cluster distribution. Meanwhile, the main causes of spills include production error (34.8%) and interdiction (31.6%); interdiction alone discharged about 61.4% of crude oil. This brings to light the significance of oil pipeline spills and the tendency to increase the risk of exposure. The generic assessment criteria were developed for three land uses using CLEA v 1.06 for aromatic (EC5-EC44) and aliphatic (EC5-EC44) fractions. The use of the model and screening criteria are embedded in a framework designed to stimulate public participation in pipeline management and pipeline hazard mitigation, which policy makers and regulators in the oil industry can find useful in pipeline hazard management and exposure mitigation

Fuzzy-based Condition Assessment Model for Offshore Gas Pipelines in Qatar

Condition assessment of offshore gas pipelines is a key player in pipeline operations and maintenance. They are used to ensure better decisions for repair and/or replacement and reduce failure possibilities. Information obtained from pipelines assessments are regularly used for scheduling upcoming maintenance and inspection activities. Therefore, it is valuable to have effective condition assessment of pipelines because failure incidents could lead to catastrophic economical and environmental consequences. Furthermore, current practices of assessing gas pipelines condition are considered too primitive and simplified. They mainly depend on experts' opinions in interpreting inspection data where the process is influenced by the human subjectivity and reasoning uncertainty. In another way, they need the detailed knowledge on translation of raw inspection data into valuable information. This will surely lead to decisions lacking thorough and extensive review of the most influential aspects on pipelines condition. To redress the weaknesses of the current practices and promote the performance of assessing offshore gas pipelines condition, this research proposes a new fuzzy-based methodology that utilizes hierarchical evidential reasoning (HER) for meticulous condition evaluation under subjectivity and uncertainty. The principle behind the posed structure is to establish an enhanced mechanism for the aggregation of different evidence bodies at multiple hierarchical levels in order to attain a reliable and exhaustive pipeline condition assessment. The essential characteristics of the proposed methodology are recapped in the following points. Firstly, the new approach suggests a more comprehensive hierarchy of the most influential factors affecting pipeline condition under three categories: physical, external, and operational. Secondly, this methodology is designed to consider the relative importance weights of all assessment factors in the hierarchy and to account for interdependencies among compared attributes. Thirdly, a hierarchical belief structure that utilizes evidential reasoning and fuzzy set theory is applied to grasp the uncertainty in pipeline evaluation. A model that utilizes HER can help combine different bodies of evidence at different hierarchical levels using Dempster-Shafer (D-S) rule of combination to obtain a detailed pipeline assessment. Fourthly, a condition assessment scale associated with rehabilitation actions is introduced as a framework for professionals to plan for future inspection and rehabilitation works. Finally, an automated, user-friendly, tool is developed for the propounded model to assess pipeline condition. Multiple sources of data were reached to provide a reliable assessment of pipe condition through the use of a structured questionnaire distributed among professionals in oil and gas industry in the studied region. This proposed model is compared and validated with historical inspection reports that were obtained from a local pipeline operator in Qatar. It is found that this model delivers satisfactory outcomes and forecasts offshore gas pipeline condition with an Average Validity Percent (AVP) of 97.6%. The developed fuzzy-based methodology is believed to offer a reliable condition assessment that optimizes data interpretation and usage of structured algorithms. Additionally, the introduced model and tool are compatible to researchers and practitioners such as pipeline engineers and consultants in order to prioritize inspection and rehabilitation for existing offshore gas pipelines. This immensely pictures the essence of infrastructure management to ameliorate cost and time optimization