As the search for hydrocarbons necessitates the exploration of everdeeper waters and remote locations, operators who wish to plan well construction in the most credible and cost-effective way, and who demand the most efficient execution, are increasingly employing probabilistic methods. One of the most compelling features of probabilistics is that, as opposed to the traditional deterministic "best guess" scenario, plans are based on finite uncertainty. Uncertainty will always remain a feature of operations involving people and equipment in a changing environment. Excellent planning incorporates uncertainty and allows better preparation at all stages of well execution. Model BuildingProbabilistic methods are a powerful tool to make useful and credible models of well-construction activity. Full implementation of a probabilistic approach will enhance the ability of a team to manage performance.Planned and Unplanned Events. A probabilistic well-construction model comprises not only the desired sequence of planned events but also should include unplanned events. The process may start with a group "brainstorming" session to identify the nature of all events that could occur during operations. The brainstorming sessions can be productive and inclusive if the focus is maintained on the steps required to progress the well. Following an unplanned event, for example, the group would be asked what additional steps or mitigating steps should follow to return to the planned sequence. The brainstorming approach generates a good qualitative model from which a quantitative model will follow.Visualization. The definition of a planned sequence of events and the discipline of visualizing unplanned events are key distinguishing features of the probabilistic process. Unplanned events are defined as anything that you do not intend to do but are required to do anyway. Unplanned events are often characterized as "nonproductive time." The probabilistic model can be used to visualize all of the events that could have an impact on the detailed program. People often refer erroneously to a sequence of unplanned events as a "worst-case scenario." It is a fact that having described a series of unplanned events, one can imagine an escalation into an even worse scenario. The threshold for inclusion of an unplanned event in a probabilistic model is to determine: (a) Can we exert some control over the frequency of the event occurring? (b) Can we exercise any control over the sequence of events that follow an unplanned event? (c) Is there anything in the drilling program that we will change as a result of modeling these events? For example, a tsunami or helicopter crash would not be included in a well-construction model. Lost circulation, stuck pipe, and well control would all be candidates for inclusion.Anticipation of Events. One of the most disruptive features of well construction is the occurrence of unanticipated events. The traditional deterministic method of writing down a proscribed sequence virtually guarantees that the detailed plan will n...
Management If a man tells you he knows a thing exactly, then you can be safe in inferring that you are speaking to an inexact man. —Bertrand Russell In “The Difficulty of Assessing Uncertainty” (SPE 5579, 1976) E.C. Capen described how oilfield engineers struggled to quantify variables. Capen asked groups of SPE members to estimate 10 quantities (e.g., dates, distances, times) using ranges with a prescribed confidence level. What he found (and others before and afterward confirm) is that very few people are good at this exercise. Probabilistic methods and in particular Monte Carlo Simulation (MCS) are often thought to solve the problems presented by Capen. However, MCS can make matters worse if a misleading estimate appears to be backed up by a detailed process, voluminous research, and specialized software. All estimates need to be calibrated, that is, substantiated by reference to reality. For clarity, it is worth defining the terms uncertainty and risk. Uncertainty is used here to describe the fact that for any future project a range of outcomes exist. Risk is used to describe less-desirable outcomes; typically risk relates to a project running late and over-budget. The purpose of this article is to suggest that a calibrated estimate of well project duration and cost should be a standard part of the investment decision-making process. A calibrated estimate will substantiate a wide range of possible outcomes and improve the quality of information available prior to allocating capital. Communicating information related to risk is also an area where the E&P industry can learn from others. Rating and Describing Risk Rating systems exist to describe in broad, concise terms the nature of risks associated with particular financial investments. The risk being rated is the less desirable outcome that the borrower defaults on the money invested. Standard and Poor (a credit-rating agency) use the term “AAA” to describe the lowest investment risk to capital. In the Standard and Poor system, 13 basic levels of long-term credit risk are described using a scale from AAA to D. With the potential project costs faced by the E&P industry, it seems strange that standard tools have not been established so that risk can be measured and communicated. The credit-risk system has been through a difficult period and is thought to have contributed to a large number of bad investment decisions. The fact that the risk of collateralized debt obligations (CDOs) was thoroughly underestimated reflects badly on the system. But lessons can be learned from the financial industry. First, although the system was flawed, it has not been abandoned and will be improved. Secondly, so much has been written and published about financial risk that it would be irrational not to use knowledge gained from these expensive lessons. Thirdly, the cost of poorly understood risk is illustrated well by public errors such as the CDO fiasco.
Management Much has been written to explain the origins of the credit crisis that has engulfed the international financial system. At the heart of each explanation is the failure to quantify commercial risks. The companies at the centre of the crisis were often long-established, considered profitable, and were endowed with great resources to make mathematical models of their activities. Despite this, it is safe to conclude that many of their models were wrong. Risk is a feature of financial transactions and drilling wells that no amount of engineering will completely remove. From the crisis in banking it is obvious that the skills required to build a credible model of activities inclusive of risk are in short supply. It would be convenient to assume that because the energy industry employs lots of numerate people it is good at quantifying uncertainty; unfortunately, many of the time and cost models used for well planning can be easily disproven. The reasons for this go beyond the tools available to the human bias toward optimism. There is a tendency to treat each well project as unique and disregard the fact that past performances will not only inform us about averages but also about uncertainty. A Suitable Benchmark The budget for new well projects will often first be defined with little detailed engineering information. There are perfectly valid reasons for this; out of a basket of many prospects an operator is unlikely to develop every one. Early budgetary estimates play a part in the selection of the best prospects to drill. Irrespective of the method used to define a budget figure, and irrespective of the maturity of the estimate, some guidance on confidence should accompany the result. In common with any other forecasting discipline, well cost estimation never is and never will be an exact science. The very best that can be done is to describe the probability of a particular scenario and to use the results from similar previous wells to back this up. If a model of well project duration cannot be substantiated with empirical evidence it must be treated with extreme caution. The inputs to the model matter much less in this respect than the output; it is surprisingly easy to make a poor probabilistic model from good information. In many mature drilling provinces such as the UK, public data can be used to provide the justification necessary for models of project duration which in turn can be used to model cost.
A well failure model is constructed as a matrix that identifies the most common modes of well failure seen by the Well Operator. For specific well types, well anomalies are assessed before they happen, in a what-if risk assessment. A traditional well failure model (WFM) includes a subset of possible anomalies and is based on subjective judgement. Total E&P Denmark's (TEPDK) new WFM uses quantitative analysis with an objective approach to risk assessment. This gives detail and clarity of actual risk (as a product of probability and severity) from well integrity anomalies not previously available. This Analytical WFM assesses well integrity barrier compliance and risk. It uses individual component failure mode probabilities and severities and analyses thousands of potential leak paths throughout wells. It includes potential flow from multiple pressure sources and to multiple pressure sinks, providing a comprehensive understanding of all possible failure cases, and their associated impact on risk. Quantitative Risk Assessment (QRA) was used to calculate maximum Safe Service Life for wells following component failure. Outputs from the analysis were used to build a detailed WFM. Immediate and long-term actions were developed in workshops and suitable response times agreed based on the Safe Service Life calculation. Engineers now spend 85% less time in well integrity risk assessments and failure management when anomalies arise because this work has been done in advance. This means engineers' time is freed for other valuable tasks. The company also saves management time, onshore and offshore, cutting down the need for management challenge and action justification. All personnel involved have a more consistent understanding of well issues, with routine anomalies dealt with much more efficiently. This means decisions are made at a lower level, including whether to continue to operate a well or shut it in. TEPDK has reduced the probability of process safety incidents from wells. This is because it has a far more sophisticated, clearer understanding of well risks, and actions and timeframes for anomaly response. It has also improved production efficiency, safeguarding on average 2,700 boepd, through a reduction in well shut-in time. This has an equivalent value of approximately $50 million / year.
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