Natural gas is the noble fuel of 21st century. Consumption increased nearly 30% in last decade. Exploitation of conventional, unconventional, and contaminated gas resources are in focus to meet the demand. There are number of giant gas fields discovered worldwide and some of them with higher degree of contaminants viz. CO 2 , H 2 S and Hg. Additionally, they have operating challenges of high pressure and temperature. It becomes more complex when discovery is in offshore environment. This study presents the development and production, separation, transportation and identification & evaluation of storage sites and sequestration and MMV plan of a giant carbonate gas field in offshore Malaysia. Geological, Geophysical and petrophysical data used to describe the reservoir architecture, property distribution and spatial variation in more than 1000m thick gas bearing formation. Laboratory studies carried out to generate the rock and fluid representative SCAL (G-W), EOS and Supercritical CO 2 -brine relative permeability, geomechanics and geochemical data for recovery and storage estimates in simulation model and evaluating the post storage scenario. These data are critical in hydrocarbon gas prediction and firming up the number of development wells and in the simulation of CO 2 storage depleted carbonate gas field. Important is to understand the mechanism in the target field for storage capacity, types of storage- structural and stratigraphic trapping, solubility trapping, residual trapping and mineral trapping. Study covers methodologies developed for minimization of hydrocarbon loss during contaminants separation and utilization of CO 2 in usable products. Uncertainty and risk analysis have been carried out to have range of solution for production prediction and CO 2 storage. Coupled Simulation studies predict the production plateau rate and 5 Tscf recovery separated contaminants profile and volume > one Tscf in order to have suitable geological structure for storage safely forever. Major uncertainties in the dynamic and coupled geomechanical-geochemical dynamic model has been captured and P90, P50, P10 forecast and storage rates and volumes have been calculated. Results includes advance methodologies of separation of hydrocarbon gas and CO 2 like membrane and cryogenics for bulk separation of CO 2 from raw gas and its transportation in liquid and supercritical form for storage. Study estimates components of sequestration mechanism, effect of heterogeneity on transport in porous media and height of stored CO 2 in depleted reservoir and migration of plume vertically and horizontally. Generation of chemical product using separated CO 2 for industrial use is highlighted.

For any given Exploration oil and gas portfolio and associated opportunities, successful business decisions can only be made on the basis of technically robust estimates of the subsurface risk versus the resource potential and estimate of the associated upside(s). Ideally, these estimates should incorporate the entire spectrum of opportunities for the complete portfolio and they should be made in a consistent and comparable way. However, as Explorers, we are often faced with data that is incomplete, limited, of variable quality, and/or inconsistent. As a result, subsurface evaluation may be seen more as educated guessing rather than a robust science of evaluation grounded in facts and defensible logic. In their January 2020 paper "Randomness, serendipity, and luck in petroleum exploration" authors Milkov and Navidi (Ref 1 .) go quite a bit further and demonstrate that luck is a significant factor in the exploration success equation. They also showed a general lack in long-term consistency in exploration results of individual companies. Indeed, after we looked at PETRONAS’ own historical POSg versus actual technical success rates and observed only a fair to poor relation between actual technical success rate and the pre-drill POSg estimate. A similar—albeit less worrisome—observation was made for volume ranges and fluid phase predictions. Clearly, there is, and always has been, a phenomenal challenge for the Petroleum Geoscientists to provide the sought after estimates as accurately as possible, and we were no exception. In a bid to improve on this PETRONAS set out on a more disciplined approach to characterizing subsurface uncertainties on its conventional exploration efforts. Over time, more accurate characterizations of such exploration risk and resource potential have followed from a series of procedural guidelines, enhanced capability training program and careful governance of exploration workflows. With improved capabilities and workflow consistency, our evaluation teams have delivered substantially better subsurface evaluations. This in turn has led to more confident decision-making on e.g., individual drilling decisions and new play entries. While our newly implemented workflows are not groundbreaking in isolation, in combination they have delivered notable success and an improved ability to shape the future growth for PETRONAS. In this article, we will highlight the main contributing changes and demonstrate that the overall improvements are indeed impactful. We are not directly challenging the article of Milkov et. al., but are convinced that professionalism and scientific discipline is the deciding factor in the Exploration success equation .

The objective of this paper is to share the holistic approach to managing aging fleet for offshore fixed steel structures. PETRONAS is currently operating a fleet of more than 200 fixed offshore structures in Malaysian water. More than half of it has exceeded the original design life. With enhanced oil recovery and other developing technologies, offshore platforms often than not are required to continue operating beyond its original design life. A holistic approach for life extension of fixed offshore structures are being developed to ensure safe operations of the facilities. PETRONAS has started SIM journey since 2007. The approach of Data, Evaluation, Strategy and Programme in line with API RP 2SIM set the basis for managing the integrity of the offshore fleet. An integrated solution was developed to manage both topsides and substructures. The Structural Integrity Compliance System (SICS) which houses the integrity management of topsides deteriorations to prioritize resources through risk based anomalies management. Risk based underwater inspection also formed part of the solutions, addressing mainly extreme storm in the region. Other Major Accidental Hazards (MAHs) risk ranking included in SICS are vessel collision and seismic. Management of facilities with minimal redundancy such as guyed wire monopod is addressed through time based inspection. A regional hazard curve is also developed to ensure the facilities are meeting the acceptance criteria set forth by the industry. Besides aging, other integrity triggers including shallow gas and subsidence required a different scheme in managing the integrity of the facilities, primarily addressed through a comprehensive monitoring programme. There is no one size fit all recipe in managing the aged platforms for life extension. The data plays a crucial role in ensuring the right methodology is deployed in support of digitalization and data driven decision making. Implementation of the system is proven to be reliable in ensuring the offshore fixed structures are intact to support safe and continuous operations to the operator in a cost optimum manner. The data analytics help to enhance the predictive model to optimize the inspection and maintenance programme. Strong ownership and commitment of the structural integrity engineers in ensuring the data integrity maintain the challenge in sustainability of the system and provide reliable source for data driven decision making to the operator. Category: Operational Excellence (136 - Managing Aging Facilities)

Production forecasts provide fundamental input to upstream business decisions, for example in resource volume reporting, field development and production planning. Very often in mature fields, having sufficient cumulative production, field forecasts are performed based on aggregating type curves for new wells and decline curve analysis for existing wells. Conventionally, they are derived by manual trend fitting which is subjective and any iteration incorporating new data is time consuming. The advanced analytics approach presented in this paper can provide rapid and credible forecasts along with more robust quantification of uncertainties as compared to the conventional manual approach. The first step involved in the forecast automation using advanced analytics is data integration in which the production, geological, and surveillance data are combined. Then integrated dashboards are created to infer trends in production behavior. Based on these trends at the most granular forecast level, petroleum engineering based algorithms are developed to automatically select the decline period. Thereafter, multiple scenarios of historical data are generated based on historical allocation and measurement uncertainty. Through each set of these historical scenarios, best fits curves following Arp's equation are extrapolated into the future to generate multiple forecast scenarios. Finally, field level forecast is generated by probabilistically aggregating individual granular level forecasts. The automated forecast program developed is computationally very fast as 500 forecast scenarios at the well level can be generated in 30 seconds, while the full field forecast with 50 wells takes about 30 minutes to generate. Automation of decline period selection and curve fitting eliminates the subjectivity by standardizing the process and reduces the chances of manual errors. Abandonment criteria, discounting and uptime variations can easily be accommodated in the automated process. Visualizations are utilized at each step for quality check and analysis. Forecasts from alternate methodologies are used to validate the forecast ranges coming out from this method. Uncertainties quantification in this approach is found to be more quantifiable and consistent compared to the conventional deterministic approach. Production dashboards created in this workflow by integrating production, surveillance, geological data and forecasts are a very effective tool to perform field reviews and communicate outcomes. The approach described above for decline curve analysis can easily be extended to any type-curve based forecasting. Automation of performance-based decline curve and type curve forecast methodologies has the potential to reduce huge manhours involved in their periodic updates by an order of magnitude that can be utilized to carry out other critical analysis. It is very useful in mature assets with large well inventory, huge dataset and where continuously new data are being added. Standardization of workflow, implementation ease and accuracy will tempt practitioners to use it and thereby develop skills in data analytics.

Manual Material Handling (MMH) activities (i.e. lifting, lowering, pushing, pulling, and carrying) pose the risk of injury to the musculoskeletal system of the workers. The injuries may lead to decreased work performance, and increased errors, absenteeism and health care cost. Therefore, it is necessary to know whether the workers of one of the Oil and Gas Company in Thailand are facing with the injury problem and to find the solutions for preventing those injuries. The procedure of the solution is walk-through survey of hazards and risks of Work-Related Musculoskeletal Disorders (WMSDs) among the workers (both onshore and offshore platforms) whose works involved in MMH tasks and providing the recommendation and followed up by Medical and Occupational Health team of the Company together with the physical therapists from one of the famous academic institute in Thailand who are collectively called "the research team". The research team conducted a walk-through survey and performed preliminary physical examination at an onshore and all offshore platforms. The survey included characteristics of each work, intensity and frequency of workload, work environment and potential risk factors. Physical fitness assessment including muscle power and weakness was also determined. The findings from the walk-through surveys, work procedure were analyzed to identify risk factors of work-related musculoskeletal injuries. The findings from preliminary physical examination in approximately 300 operating workers, upper cross and lower cross syndromes were found, indicating muscle imbalance in MMH workers. Task activities were analyzed on each procedure which has risk factors including awkward posture, repetitive movement, manual handling, forceful exertion, work environment, equipment, and cognitive and psychosocial issues. The research team reported risk factors with consequences and provided recommendation for each factor regarding engineering, administrative, and individual controls. For example, offshore platform has many floors which are designed for particular function (office, bedroom, dining room, etc.). Offshore workers regularly perform high repetitive stepping up and down stairs making them prone to hip and leg muscles imbalance. There is high compression at knee joint which may lead to early degenerative joint or knee pain. The recommendation is to provide properly work break and training with principle of ergonomics in workplaces including ergonomic risk factors; risk prevention; and strengthening exercise. Findings on this study lead to the specific designed exercise program and training to counteract the effect of heavy musculoskeletal activities related to MMH in daily work. The study will also serve as a guide for developing of MMH guideline for the company.

Currently, decisions involving a huge amount of money and resources are based on the outcome of simulations. Consequently, an increase in the computational resources has attracted engineers and scientists to increase the complexity of the mathematical models and their numerical algorithms to design or analyze various systems. On the other hand, the transparency of these models has decreased and the sensitivity of the outcome of these simulations on, for instant, certain assumptions or input parameters is often not known a priori. Furthermore, validation of the models for complex systems in which full scale measurements are limited or even impossible, gives more challenges to the decisions made based on these numerical simulations. Additionally, robust design to consider off-design conditions in a systematic manner is of great importance in oil and gas industry. Therefore, it would be essential to develop a systematic procedure to quantify the sensitivities and errors associated with each set of simulations in an objective manner. Uncertainty quantification (UQ) could be used as a tool to provide the validity of a performed simulation. This study describes the current research and opportunities for parametric analysis and uncertainty quantification in the flow assurance such as in performance prediction and validation, risk assessment, decision making and robust design. Additionally, we describe the importance and benefits of probabilistic analysis instead of deterministic analysis. Uncertainty quantification increases the computational expenses and effort of performing deterministic simulations. Therefore, an efficient method to quantify the uncertainties such as probabilistic collocation or surrogate models are required to reduce the computational costs without losing the accuracy of the analysis. Parametric analysis and uncertainty quantification will give more insights in the validity of simulation data than traditional methods. For instance, using the newly proposed methods will expose the sensitivity of the simulation results to off-design conditions and consequently leads to a systematic decision making based on the probability of an event occurrence. These methods could be used to quantify the most sensitive parameters in the system and the effect of their propagation to the outcome of the model. It is shown that performing non-deterministic analysis in some cases is a necessity.

There is an ever increasing need to extend the life of aging offshore structures beyond their original design life. Whether these structures are fixed offshore rigs or floating facilities, operators are continually looking for requalification and extension of the service life aimed at ensuring the integrity of the structure. With a continued requirement to produce oil or gas, either from the original fields or as a base for neighbouring subsea completions, many of these respective offshore installations are likely to remain operational for a period of time in the foreseeable future. The ageing offshore infrastructure presents a constant and growing challenge. Ageing is characterised by deterioration, change in operational conditions or accidental damages which, in the severe operational environment offshore, can be significant with serious consequences for installation integrity if not managed adequately and efficiently. In order to ensure technical and operational integrity of these ageing facilities, the fitness for service of these structures should be maintained. Maximising the availability and productivity of the field, whilst operating safely and with minimal impact on the environment, is a major concern for requalification and life extension. Structural integrity management (SIM) and inspection campaigns are important inputs in the Asset Integrity Management and the maintenance of structural integrity is a significant consideration in the safety management and life extension of offshore installations. Detailed integrity assessments are needed to demonstrate that there is sufficient technical, operational and organisational integrity to continue safe operation throughout an extended service life. Information on history, characteristic data, condition data and inspection results are required to assess the current state and to predict the future state of the facility and the possible extension of service life. However unique environmental conditions, type of structures, fabrications and installation methodologies used in Middle East required attention in particular, development of hazard curves and risk mitigation of the potential regional degradation mechanisms. During the life-cycle of an offshore structure the ultimate capacity is also an important attribute that affects the life expectancy, requalification and life extension of the facility, and can significantly influence the reliability levels and operational costs. This paper presents state of art practices in life extension of existing offshore structures and an overview of a regional hazard curves evaluation methodology and proposed regional correction factors represented risk to the integrity of a facility and the required procedures and re assessment criteria for deciding on life extension in particular the one with the importance for Middle East region. This paper also provides an overall view in the structural requirements, justifications and calibrations of the original design for the life extension to maintain the safety level by means of a maintenance and inspection programs balancing the ageing mechanisms and improving the reliability of assessment results

Uncertainty quantification on reserves estimation is a fundamental task for project validation on offshore green fields and also for the selection of a development plan that is robust to those uncertainties. To test the robustness of several development plans is then fundamental to be able to evaluate the impact of this uncertainty with low computational cost. Structural, geological and dynamic uncertainties are integrated in a new workflow based on a set of embedded response surfaces. The first step consists in building an experimental design with only structural and geological parameters to evaluate the impact of such uncertainties on static responses such as oil initially in place. In the second step, this experimental design is completed with additional dynamic parameters. The novelty of the static and dynamic design merging is to incorporate the previously obtained static response surface in addition to the uncertain parameters. By embedding the static response in the variables we obtain a response surface on the reserves more regular and more predictive. In this workflow, mainly applied to green fields, the impact of local geological uncertainty is usually of second order respect to other global uncertainties and it is taken into account as random noise whose variance may depend on the static response. The method is applied to a real green field with complex multi-level heterogeneities and it is compared to more standard approaches such as Monte Carlo. We manage to obtain a very good response surface quality for the static response (oil in place) that is then embedded in the reserves response surface. The final accuracy of this response surface is sensibly increased respect to a classical approach considering only static and/or dynamic parameters at minor costs in terms of reservoir simulations. The new approach reduces sensibly the number of reservoir simulations needed for an accurate uncertainty and risk assessment when applied to select the more robust development plan selected from a set of possible candidates. It also provides useful sensitivity analysis measures to guide possible data acquisition campaign in order to reduce risks and take better decisions.

Abstract Geohazard can be described as local and/ or regional site and soil conditions having a potential of developing into failure events causing loss of life or damage to health, environment or field installation. PETRONAS Carigali Sdn Bhd (PCSB) is confronted with various geohazards challenges, both in our domestic and international projects. These geohazards includes but are not limited to different types of soil stratigraphy, shallow gas, shallow channel systems, faults, pockmarks, mudflows, corals etc. In order to address these Geohazard issues, PCSB has developed a comprehensive Geohazard Assessment Model (GAM) for institutionalization within the company a governance process to manage geohazard risks. The aim of Geohazard Assessment Model is to: Provide a comprehensive integrated geohazards risk assessment framework to ensure geohazards risks are identified and management is given advance recommendations on the mitigation solutions and Ensure all requirements for the Geohazard Analysis such as technical; pre, during and post operations and health, safety and environmental (HSE) are within code compliance and assets are being safeguarded at all times. The importance of GAM can be reflected in terms of monetary, time, quality and HSE whereby substantial cost savings can be achieved via a risk assessment perspective. GAM utilizes an integrated approach requiring expertise in geotechnical, geophysical and geological disciplines to rationally identify, assess, quantify and mitigate these geohazards for the eventual selection of final field development concept, optimum asset sitting and approaches. This paper shall present how jack-ups suitability are studied from a risk assessment perspective using GAM. The importance of proactive measures to mitigate geohazards are also elaborated on projects undertaken by PCSB. Adopting a systematic approach to quantifying geohazard risk can minimise time and cost impacts upon any field development.

Abstract In 2010, a risk analysis taking into account both uncertainties in reservoir parameters and at the same time accounting for real time pore pressure measurements during a drilling operation on the Norwegian continental shelf (NCS), was completed. The plan was to drill through seven reservoirs, each independent of each other with a vast amount of uncertainties in the pore and fracturing pressure due to years of injection and production. The risk analysis was first made as an input to the drill plan, using best reservoir parameters available as well as expert judgments. Simulations were performed within a Monte Carlo (MC) framework. Results like for instance probabilities for fracturing and kick for drilling through the next reservoir(s) or tripping out, as well as an optimum mud weight for reducing risk, were obtained. The analysis was updated real time as the pore pressures were logged during the drilling phase, providing the best possible risk picture and giving the decision takers a possibility to update the drill plan before drilling through the next reservoirs. This paper describes how the main characteristics of the reservoirs were modeled and how the risk analyses were performed. Simulations obtained, both before and during the drilling operations, are presented. Results like the probabilities of fracturing and kicks as a function of reservoir parameters and number of reservoirs drilled, as well as optimum mud weight for risk reduction, are emphasized. Introduction Risk analyses are widely used by operators on the Norwegian continental shelf (NCS) to manage risk during drilling and completion phases. The analyses should reflect potential hazards and unwanted events during the operations, and are mainly based on pre-assumptions and best available information. Uncertainties of well specific parameters are usually dealt with in a conservative manner. However, risk analyses taking into account real time pore pressure measurements have, to the author's knowledge, not previously been performed. Considerable geologic uncertainty introducing potential narrow pressure margins were key issues in the planning of drilling a sidestep in a mature oil and gas field on the NCS. The field has been produced for some time, and several reservoirs had been subject to injection. Forthcoming decisions related to selection of mud properties and operational procedures were a challenge, and the overall risk level of the drilling operation was unclear. It was originally decided to undertake a quantitative risk analysis (QRA) to improve the overall risk picture and to form a stronger basis for decision-making in the development of the drilling program. Later in the project, one clearly saw the advantage of having the risk picture re-evaluated as the pore pressures were measured. The objective of this paper is to present the stages of the QRAs in the well planning process, the results and their applicability as decision support for the project. The QRAs was performed by use of the KickRisk analysis tool. This tool is based on a pressure control model, where factors influencing the bottom hole pressure (BHP) throughout the various phases of the construction of a well section are decomposed. The model includes down hole, fluid, equipment and operator-related aspects and their impact on hydrostatic, friction and surge/swab pressure effects. The analysis implies gathering of input on the uncertainty of these quantities in terms of probabilities and probability distributions. By Monte Carlo simulation, the resulting probabilities of entering a state of underbalance with the pore pressure (kick) and of exceeding of the fracturing pressure (fracturing) are derived, and the factors that are main contributors to the risk are identified.

Abstract This paper presents various techniques/ tools used to demonstrate the major Health, Safety and Environment (HSE) risks involved in the tight gas appraisal program, especially in designing the surface facility for the Trial Production Operation (TPO), has been reduced to As Low As Reasonably Practicable (ALARP). In the challenging environment of central Sichuan basin i.e. local hilly terrain and densely populated farm land, the paper looks at the local requirement and importance of the analysis right from the design phase for a safe and efficient operation of the TPO facility. The techniques covered include Hazard Identification (HAZID) Study, Hazard and Operability Study (HAZOP), Safety Integrity Level (SIL)/Instrumented Protective Function (IPF) study, Fire and Explosive Risk Analysis (FERA) and Fire Protection Analysis (FIREPRAN) study. The paper covers the documentation of ALARP demonstration into a Design HSE Case. Major Accidents Hazards (MAH) in the TPO facility are identified using the Risk Assessment Matrix (RAM). A systematic and structured Hazards and Effects Management Process (HEMP) is applied in the design of the TPO facility and the risks associated with MAHs are actively and systematically reduced to ALARP. The effectiveness of all barriers and controls for each MAH are evaluated and complied with the set criteria (Bow-tie assessment). If the HEMP assessment determines that a barrier or risk management of a MAH is only partially effective, further remedial action and effort is done to close the gap. Besides, Safety Critical Elements (SCE) and their performance standards are identified and developed as a key input to the Asset Integrity Process Safety Management (AIPSM) in the operations phase. Finally, the TPO facility design on a plot size of 70m x 70m pad was accepted for construction and trial production. Further improvement study and optimization has been ongoing including taking other unconventional gas (UCG) best practices and learning into the development planning.

Abstract Kuwait Oil Company (KOC) has 85 crude oil aboveground storage tanks in its Tankfarms for the storage of crude oil prior to export. These tanks have storage capacities ranging from 162,000 to 597,500 bbl. (US). Hydrocarbons leaks / spillages resulting from tank failures, if any, could be very expensive and could pose serious fire hazards apart from major environmental issues. Therefore, in order to carry out a comprehensive assessment of the tanks to prevent any impending failure, KOC decided to adopt Risk Based Inspection (RBI) approach to evaluate the risks associated. With the aging tankfarm facilities and the changes in oil production processes, it became even more important to ensure the reliability of to ensure the reliability of tankfarm facilities from the viewpoint of "just in time maintenance" and regulatory requirements. The outcome of the evaluation enabled formulation of inspection strategies to mitigate these risks for improving asset integrity. A qualitative RBI methodology was established and the procedure was developed in-house based on the guidelines in international standards (API, NFPA). The procedure was then used to perform the RBI study of each individual tank in KOC Tankfarms. A workbook was developed to carry out the risk assessment of the tanks as per API RP 581 and the RBI assessment results were presented in a risk matrix. For carrying out the risk assessment, the tank is divided into three sections viz. the Bottom Plate, the Shell and the Roof and each section is subjected to risk assessment separately. Relevant damage mechanisms are considered for each of the sections. The RBI analysis includes the information on original design, operation & maintenance, damage mechanisms, timing the failure of individual evaluated components, condition inspections, process condition, NFPA (National Fire Protection Association) rating for service fluid and current operating conditions. RBI study recommendations include the suggested improvements to the inspection program and maintenance schedules to enhance the asset life-cycle. This paper describes the entire Tank RBI process adopted at KOC, some interesting findings of the RBI study and the recommended Asset Management Strategy for the Tankfarms. 1. Introduction 1.1 Brief of KOC Facilities Crude oil from oil wells is transported to the Gathering Centre (GC) via a number of flowlines. The Gathering Centre processes fluids to separate gas, water and salt associated with oil before pumping to the Tankfarms. The crude oil processed at various Gathering Centers of Kuwait Oil Company is transported through the transit pipelines to the Tankfarms. Over 85 tanks in the Tankfarms receive crude oil with a minimum API of 30.5 from the incoming transit pipelines via a Central Mixing Manifold. The tanks are equipped with automatic level gauges, Motor Operated Valves, firefighting facilities and manual oily water disposal system. The crude oil is stored at these Tankfarms prior to export. KOC sets the production targets on the basis of continuous market demand.

This reference is for an abstract only. A full paper was not submitted for this conference. Primary Category: Managing Risks and Uncertainties Abstract The Chemical, Petrochemical and Oil& Gas industry has had an excellent safety record when compared with industry as a whole1. Nevertheless few major incidents like MIC gas leak in Bhopal, LPG plant explosion in Mexico etc. with heavy loss of life led to public concern about the hazards of process industry, resulting in legislations requiring manufactures to demonstrate that appropriate safety measures are taken. This led the industry to resort to predictive Quantitative Risk Assessment Technique (QRA) The Piper Alpha and Alexander Kielland accidents led to prescriptive regulations on use of QRA in process industries in both UK and Norwegian sector of North Sea. As a result, interest in use of QRA technique for assessing safety of process plants has grown considerably. Overall use of Quantitative Risk Assessment has continued to increase although some countries still remain skeptical about of the value of use of QRA. A major difficulty faced by industry in using QRA is setting Risk Tolerance/acceptance Criteria. What is the Target Risk Acceptance Criteria to be followed? Is there a Universal Risk Acceptance Criteria? A literature search reveals that different regulatory bodies world over have recommended different acceptance criteria for Individual Risk. The Criteria for few important countries are presented in Table-1. There is wide variation in Acceptance Criteria for Societal Risk also as presented in Figre-1. As it is evident from the Figure, different nations have adopted different risk aversion factors. UK and Hong Kong did not consider any risk aversion factor and slope of the lines is -1. Netherlands and Denmark have adopted a more stringent risk aversion factor as indicated by the slope of -2 for these lines. Australia has adopted moderate risk aversion factor as the slope of the line is between -1 and -2. On the contrary certain developed countries like USA, France, and Germany etc. do not prescribe any Risk Tolerance Criteria both for individual and Societal risk. Further, there are great uncertainties in risk estimation.2, 3 In view of the above problems, industry finds it difficult to arrive at a Risk Criteria. In general, the industry looks for advice from QRA consultant on risk criteria and consultant seeks guidance from industry to define the risk criteria. Most industries, particularly in developing countries, are not well equipped to understand the complexities involved in risk estimation and selection of appropriate Risk Tolerance Criteria relevant to local political, social and economic conditions. The Criteria recommended by the consultant may be very stringent with little relevance to the local conditions leading to problems for the industry with recommendations requiring heavy demand on scarce resources. Knowledge of complexities involved risk estimation, the end use of the risk estimates, the origin, basis and development of Risk Acceptance Criteria are prerequisite for the Industry to be able to decide on the Risk Acceptance Criteria in an effective manner relevant to the local conditions. In order to assist the industry, this paper Analyses the problems with quantitative risk estimation and uncertainties associated in the estimation, Critically reviews the Risk Acceptance Criteria recommended by different regulatory bodies, and Provides guidelines, based on author's experience, for path forward in setting appropriate Risk Acceptance Criteria relevant to the industry objectives. It is expected that the guidelines along with the discussion on risk estimation and uncertainties will make the life of operator a lot simple in making a decision on Risk Acceptance Criteria. Literature cited Institution of Engineers, UK, Risk Assessment in Process Industries, (Ed… Robin 1996). Kurt Lauridsen, Igor Kozine, Frank Markert Aniello Amendola, Michalis Christou, Monica Fiord, Assessment of Uncertainties in Risk Analysis of Chemical Establishments The ASSURANCE project Final summary report, Risø National Laboratory, Roskilde, Denmark, May 2002. D. Veeranna, "Quantitative Risk Assessment - A Decision Making Tool in Process Industry on Safety Issues", Fourth International Professional Development Conference on Occupational Health, Safety, Environment and Loss Prevention, American Society of Safety Engineers, Kuwait Chapter, Kuwait, 15- 17 April 2007.

Abstract In the planning of a new appraisal well on an HPHT field on the Norwegian shelf, pressure control was at an early stage identified as a challenge. The pressure margin was expected to be narrow and pore and fracturing pressures were uncertain. This represented risks related to fracturing and losses and to kick and ultimately loss of well control. To explore the extent of the risk, understand the most important factors contributing to risk and provide a basis for reducing risk through decisions in the operation planning, a quantitative risk analysis was commenced. Pressure control physics and the impact of uncertainties were explored through Monte Carlo simulation using the KickRisk analysis tool. With this tool probabilities are used to describe the uncertainty related to a number of operational, equipment related and geological pressure components. The output from an analysis reflects the ability to stay within the safe operational window during drilling, in terms of well specific kick and fracturing probabilities. The relative risk contributions from the different operational phases and from different kick and fracturing mechanisms in each phase are included. This paper describes the application of the KickRisk analysis tool on the HPHT well. Specific attention is drawn to how the analysis supported the identification and selection of measures aiming at minimising pressure control risk. Such measures include risk-based mud weight selection, reinforcement of procedures and preparation of decision rules with respect to the outcomes of formation integrity testing and pore pressure measurement during drilling. 1. Introduction Pressure control was a key issue in the planning of the reservoir section of an HPHT appraisal well on the Norwegian Continental Shelf. Narrow pressure margins and considerable geologic uncertainties involved risk of mud loss, kick and ultimately blowout. Forthcoming decisions related to selection of mud properties and operational procedures would be a challenge, and the overall risk level of the drilling operation unclear. It was decided to undertake a quantitative risk analysis (QRA) with focus on pressure control in order to improve the understanding of the risk picture and to obtain a stronger basis for decision-making in the development of the drilling program. The objective of this paper is to present the stages of the QRA in the well planning process, the results and their applicability as decision support for the project. The appraisal well was to be drilled with a jack-up rig, i.e. excluding heave effects on the bottom hole pressure (BHP). The reservoir section was planned drilled with 8 ½" drill bit, with the 9 5/8" casing set above the reservoir formation. Originally, tripping out of the well was planned with a slug and no circulation. It was first assumed that the well would be completed with screens. Later it was decided to run 7" liner. At the time of writing this paper, the drilling of the well was ongoing, but the reservoir section was still not commenced. The QRA was performed by use of the KickRisk analysis tool. This tool is based on a pressure control model. Factors that influence the BHP throughout the various phases of the construction of a well section are decomposed. The model includes down hole, fluid, equipment and operator-related aspects and their impact on hydrostatic, friction and surge/swab pressure effects. The analysis implies gathering of input on the uncertainty of these quantities in terms of probabilities and probability distributions. By Monte Carlo simulation the resulting probabilities of entering a state of underbalance with the pore pressure (kick) and of exceeding of the fracturing pressure (fracturing) are derived, and the factors that are main contributors to risk may be identified. The analysis was performed in 3 stages. Most of the input was gathered in the first stage and an overall risk picture was established. The two latter stages were updates on decisions on equipment, design and procedures introduced through the project. Some more details on the analysis tool are included in Section 2. Section 3 expands on the analysis process and the analysis results. Conclusions are summarised in section 4.

Abstract Escalation of per-barrel crude prices is expected to continue on an inflation adjusted basis in the foreseeable future according to most analysts. Rising prices are largely attributed to market forces fueled by surging world economy and growing demand, particularly in Asia and Middle East. Relatively flat rates of exploration and exploitation success have been unable to keep pace with that growth, leading to tight supplies. Politics, weather, speculation and other factors further contribute to supply uncertainty. International Oil Companies (IOCs) face competition from other IOCs as well as from entrepreneurial national oil companies (NOCs) aggressively looking to develop assets domestically and overseas, and reserve replacement remains a challenge as suppliers try to gain access to incremental upstream resources in order to meet growing demand. NOCs no longer remain in a simple asset management role for domestic resources; rather, many entrepreneurial NOCs have joined the fray alongside IOCs in pursuit of E&P resources outside national boundaries. Besides straight E&P initiatives, associated major projects and services are also expanding internationally. With the growing number of international ventures in the petroleum and energy market, the significance of market entry risk assessments has also increased correspondingly. Timely, objective basis for decision-making provides a distinct business advantage in a dynamic global market. Consistent application of the Rajan-Vikas model 1, 2 enables rapid screening of candidate markets as relevant to the project or initiative. Other model artifacts include risk characterization profile for the various countries, and relevance profiles for each project or initiative. Different forms of these various profiles, in turn, lend themselves to mining for opportunities once a substantial knowledgebase is built. The focus of this paper is on potential opportunities exposed when the Rajan-Vikas model is applied for market entry risk assessments. Introduction The global energy balance is changing, as growth rates slow down in the western developed nations, while countries in Asia and the Middle East are developing rapidly, and energy demand has also grown correspondingly. Oil consumption in OECD Europe, for instance, increased from 13.7 MMbbl/d in 1990 to 15.5 MMbbl/d in 2005, net 1.8 MMbbl/d. Over the next 15 years that oil consumption if expected to only increase 0.1 MMbbl/d. On the other hand, oil consumption in India, China, Russia, and FSU countries is expected to grow dramatically. These global shifts in demand growth will define the future oil markets.

Abstract With the increasing use of ALARP principles in oil and gas safety studies to reduce the tolerable risks to As Low As Reasonably Practicable level, there is a need to understand the use of those principles with respect to (a) the level of uncertainty of data and (b) the risk criteria. Because of the level of uncertainty of data it becomes unclear which tool to be used for ALARP demonstration. As far the application of numerical risk criteria is concerned, it is not always correct in some cases. Thus the demonstration of ALARP and the risk criteria used should be justified by the categorization of risk which may be qualitative, semi-quantitative or quantitative, and the available data. For quantified risks, the intensification of ALARP demonstration will depend on the available data and the level of risk reduction to be achieved. Overlooking of such issues could lead to either inadequate analysis or over-analysis of risk resulting in companies burdened with extra cost for implementation of recommendations. This paper suggests a structured methodology for the ALARP demonstration and its 'level of intensification', to address the issues stated above. Examples from previous risk assessment studies undertaken for various oil and gas companies have been taken and the proposed methodology is applied in the management/ALARP demonstration of both acceptable and tolerable risks. In the end, the paper demonstrates the benefits of using the proposed methodology. The paper also addresses some common misconceptions regarding the ALARP principle. Abbreviations Used ADNOC Abu Dhabi National Oil Company ALARP As Low As Reasonably Practicable CBA Cost Benefit Analysis DA Decision Analysis DF Disproportionate Factor EMBOT Extended Modified Bow-Tie Analysis HSEIA Health, Safety and Environmental Impact Assessment HSEMS Health, Safety and Environmental Management System IAD Intensification of ALARP Demonstration MBOT Modified Bow-Tie Analysis QRA Quantitative Risk Analysis / Quantified Risk Assessment RRM Risk Reduction Measure Introduction This paper addresses process related risk management by application of ALARP demonstration. In order to address the topic, i.e. ALARP Demonstration and its Level of Intensification, this paper begins with an explanation of the ALARP principle. It highlights some of the principles outlined by Health and Safety Executive (HSE), UK. Some misconceptions on the application of ALARP are also discussed. The paper outlines two problems faced during an ALARP study, namely, uncertainty of data and risk criteria. The points to be kept in mind while assessing such problems are discussed. Hence an assessor may find this useful while dealing with risks to be reduced on the principles of ALARP. The paper suggests that the application of ALARP demonstration tools and methods should depend on the categorization of risk. The tools used to demonstrate ALARP will vary depending on the level of risk reduction as well as the expression of risk (qualitative / quantitative). Hence the term 'intensification' is used for the assessor to know if a justified level of demonstration is being sought for the appraisal of risk reduction options. Thus the question 'how deep to dig' should be answered before proceeding with the demonstration. Some examples of the demonstration tools have been included but these are not intended to be prescriptive.

Abstract The paper will give an overview of how health risk assessment as input to design can contribute to better and safer work places with low health risk. This is based on the current practice in the Norwegian petroleum industry, focusing on health risk assessment and challenges in the working environment from the early design phases. Furthermore the paper describes how possible health risk and future working environment conditions at the plant during operations are assessed systematically during design and construction. Experience from operational activities and development projects are used to reduce risk and create safer and more efficient solutions. The methods used are based on company standards, national and international standards and authority regulations. The paper will give a summary of the engineering practices and tools used in Statoil ASA 1 . The following issues will be addressed: Some facts about the Norwegian Offshore petroleum industry. Requirements to Health Risk Assessment Use of standards and company requirements to the working environment An integrated follow-up during project development Experience from recent projects covering offshore field development and onshore LNG plant. 1. Introduction There is a strong focus on HSE matters in the oil and gas industry today and attention to indicators that measure our results. Safety and environmental issues related to prevention of major accidents gain the highest attention internally and from the media, but the focus on the employees' health is equally important and there are recent examples on how this focus has increased, especially related to chemical health risk. In our company we have a philosophy that zero harm to people is possible. We have still not reached this level, but we work towards this goal to control the health risk and avoid negative health effects, injuries, diseases, chronic diseases and death. 2. Some facts about the Norwegian offshore petroleum industry The oil and gas industry is the single most important industry in Norway and it has a high attention from the authorities also with respect to HSE results. The upstream activities are offshore based and field development on the Norwegian continental shelf started in the early 1970ties. The authorities have been aware of the importance of developing Norwegian expertise within all areas. Severe weather conditions were demanding advanced technological solutions and a strong focus on safety (HSE). The petroleum industry today has a very good reputation and record, despite some tragic accidents, severe incidents and a working environment which may represent risk of considerable exposure to noise, chemicals and heavy manual handling. In fact the offshore oil and gas industry has a considerable better HSE performance than the land-based industry in Norway. A worker protection act 2 was launched in Norway in 1977 and was made valid offshore from 1979. It was a modern act with functional and goal setting requirements. The objectives of the Act are; to secure a working environment which affords the employees full safety against harmful physical and mental influences and which has safety, occupational health and welfare standards that are concurrent with the techno­logical and social development of society at any time, to secure sound employment conditions and meaningful work situation for the individual employee, to provide a basis whereby the enterprises themselves can solve their working environment problems in co-operation with the organizations of employers and employees and with control and guidance from public authorities.

Abstract The quantitative assessment of the risk associated with the economic exploitation of a hydrocarbon field is mandatory to support, in an efficient and comprehensive way, the decision process guiding the development management system of an oil company. The Full Range Risk Analysis (FRRA) approach developed in Eni E&P Division allows the identification of uncertainties arising from each step of an integrated reservoir study, and the evaluation of their impact on recoverable reserves and on the economic value of a project. This methodology has already been successfully applied in the concept selection and concept definition phases of field development projects. Recently it has been further improved to be employed both in the evaluation stage, of a new discovery, and in the revamping of mature fields with production history. Introduction The Full Range Risk Analysis is aimed at investigating the whole range of possible reservoir development combinations. Its main objectives are: the support of the sanction of an economic discovery, considering an acceptable and accepted risk; the estimation of the value of information (VOI) of new data acquirement and the comparison between different appraisal strategies; the choice of the best development plan taking into account the main impacting reservoir uncertainties (mainly during concept selection phase); the quantification of downside/upside potential of the reservoir and of residual risk associated to field with production history. The presented workflow is a valuable tool in assessing the risk associated to a particular development scenario taking into account the entire surface and sub-surface uncertainties and therefore a methodology to support decisions in development projects. The FRRA methodology is fully based on Montecarlo approach and massive simulations of 3D reservoir models. Full Range Risk Analysis Workflow The current paper describes in detail the standard FRRA workflow along with the latest developments of the methodology, starting from the uncertainty definition phase up to the frequency distribution of the target variable, i.e. ultimate recovery, plateau length, NPV.

Abstract Understanding the impact of subsurface uncertainties on production responses is an integral part of the decision making process. A more accurate quantification of the uncertainty band around production forecasts contributes to better business decisions. Traditional experimental design workflows, where a limited set of models represent the key uncertainties in subsurface parameters, might be well suited for new field developments. However, when a field has been produced for several years, all models have to be conditioned to available production data in order to obtain meaningful predictions. Data integration and uncertainty assessment of future performance of the reservoir are indivisible processes that cannot be generally addressed by simple techniques. In this paper we present a method to tackle such complex inverse problems where highly non-linear responses are involved. The goal is to minimize an objective function that stands for the goodness-of-fit of the history-match. The key idea is to use high quality proxies of the objective function to accelerate the search for solutions. An efficient experimental design stage allow for the selection of key parameters while an optimization routine involving Genetic Algorithms (GA) is used to determine the best combinations of parameters. The models that reasonably honor the historical data are selected and provide an estimate of future production. The final distribution of the prediction variables defines the range of uncertainty conditioned to production history. The practicality of the methodology is demonstrated with a study of an off-shore field in West Africa that has several years of complex production history. Introduction Quantifying uncertainty in production forecast for a real field with complex history is a difficult task. Monte Carlo simulations coupled with probabilistic inverse theory is in general not practical due to the large number of simulations required. Efficient alternatives involving proxies and various optimization algorithms have been investigated. The fitness of the model to the observed data (history-match error function) is modeled using response surfaces of various nature, polynomial, kriging or spline for instance.