Calibration of Casing/Tubing Design Criteria by Use of Structural Reliability Techniques

Abstract

Summary This paper reviews the state-of-the-art in casing/tubing structural reliability analysis, and the knowledge gained from it to date. Results are presented to show that, as previously suspected, burst design based on casing full of gas is over-conservative for noncritical wells. However, the risk-calibrated design criteria are strongly dependent on the design philosophy for underground blowout loads. It is demonstrated that well control is the largest single factor in reducing risk; gaps in current knowledge are identified, and recommendations made for future work. Introduction Quantitative risk analysis (QRA) of well casing/tubing systems has undergone rapid development in recent years. The more notable projects have included a risk comparison of steel and corrosion-resistant alloy completions;1 methodology and software development, including a pilot study;2 a design code calibration using working stress design;3,4 application of QRA methods to casing seat selection;5 development of reliability-based design criteria for HPHT wells;6 a design code calibration using load and resistance factor design (LRFD);7,8 and preparation of improved design equations for casing collapse.9 The first stage of development of the subject is largely complete, in that the analysis models and software tools are now reasonably mature, and initial results are available. A review of these results shows that QRA has, as hoped, given answers to many of the important questions remaining in the subject, such as cost benefit and the appropriate selection of design criteria. Equally, however, it has raised other questions that should have been asked at the beginning. This paper is written from the fortunate position of being, at long last, wise with hindsight. It reviews:The state-of-the-art in well system QRA modeling.The knowledge gained from it to date.The questions which still need to be addressed.The development required to gain this knowledge. The authors emphasise that, while a consensus is developing in many areas of the subject, the views expressed are theirs alone. They are largely based on in-house work carried out at WS Atkins during 1995-1997. Well System QRA Models: The State of the Art Risk Analysis and Structural Reliability. "Quantitative risk analysis" has been used with different meanings by past authors, and it may be helpful to define exactly what is meant. Safety engineering (or risk analysis) answers the question "what is the total risk in the operation of the facility?" As such, it generally considers all the possible risks to the asset and its personnel (e.g., travel to and from the platform, equipment failure, operational errors, etc.), as determined by a hazard identification exercise. The traditional approach is for the risk to be calculated using historical incidence data for each risk type, suitably adjusted for the given facility (e.g., number of wells, frequency of helicopter landings). The various risks, and the consequences of each risk event, are then combined to establish the total potential risk to life, risk to the asset, and so on. This process is called quantified risk assessment. Note this technique generally will not consider the effect of changes in design criteria, because it uses historical failure rate data. Structural reliability can either answer the question "what should the design criteria be?," or establish the probability of failure of an existing design. It therefore only considers the risk of structural failure, which is usually a very small part of the whole. The risk is calculated by mapping the probability distribution functions (PDFs) of the various load and resistance variables to the predicted failure probability, using the ultimate limit state equations and mathematical techniques such as first/second order reliability method (FORM/SORM) or advanced Monte Carlo. A description of these techniques is beyond the scope of this paper, and the interested reader is referred to the literature.10–12 While the term QRA has been used to describe either technique, in this paper it primarily refers to structural reliability. However, recent work in structural reliability has highlighted the importance of mechanical reliability and human error risks,13 which are traditionally the preserve of safety engineers; and it is hoped that future work will address these wider issues. Analysis Methods. This section describes the various steps in a casing/tubing QRA. A consensus is developing in many areas, such as in the use of either FORM/SORM or advanced Monte Carlo to perform the probabilistic mappings. Where no consensus exists, the authors have described best current practice. While the treatment has been kept as simple as possible, some technical detail is unavoidable, and the reader interested primarily in the lessons learned may prefer to move directly to the next section. Input Variables. Field or test data is collected for each input variable, and the PDF type determined by plotting the raw frequency distributions onto probability scales. 10,12 The PDF parameters are then calculated,14 including sampling uncertainty if required.15,16 Load and Resistance ULS Equations. The equations for the load and resistance ultimate limit states ("ULS equations") are chosen by comparison of predictions from the various candidate equations against field or full-scale test data (as applicable), for a statistically significant number of cases. In general, even the best predictive equation suffers from either mean point bias or underestimation of the output COV, or both. This is usually accounted for by treating the model uncertainty as a postmultiplicative random variable, whose PDF type and parameters are calculated during ULS equation selection.10,12

Leakage Resistance Envelopes of API 8 Round Casing Connections using FE Analysis

“…Modern regulation for oil and gas exploration in marine environments demands for quantitative risk analysis of offshore installations [29]. In parallel, there is a recent trend for reliability-based design of wells and well casing, in particular under HTHP (High Temperature High Pressure) conditions [30][31][32][33]. Probabilistic models of pipe body burst and collapse strengths have been significantly studied, as reported in [34].…”

Research on a probabilistic assessment criterion of casing deformation in an incomplete borehole in deep salt formation

“…With the reliability theory widely applied in engineering fields, some authors begin to introduce it into OCTG design equations, which have attracted widely attention in oil and gas industry. [14][15][16] However, in previous studies the influence of harsh working condition of well casings was not considered, besides, the impact of formation and cement should not be ignored. To reveal the failure mechanism of well casings under salt creep conditions, a probabilistic computational model coupled with salt formation, defective cement and worn casing is established and analyzed using ANSYS/PDS, on the basis of sensitivity analysis, the most sensitive parameters are obtained, furthermore, a new assessment criterion is established and applied to evaluate the safety of well casings under salt creep conditions based on reliability theory.…”

Projeto ótimo de poços de petróleo baseado em confiabilidade

“…Em alinhamento com o recente movimento para a análise quantitativa de risco em empreendimentos de exploração e produção de petróleo, observa-se um crescente consenso para a adoção do projeto probabilístico da estrutura de poço (revestimentos externos e coluna de produção). Vários artigos publicados na literatura apontam caminhos para a realização de QRA (HINTON, 1998;SATHUVALLI;CRABTREE, 1998;GLOVER, 1998;ERIVWO;ADELEYE, 2012) ou abordam questões específicas relacionadas ao projeto probabilístico de revestimentos (ADAMS; HODGSON, 1999;DEDENUOLA et al, 2003;MOORE;PAYNE, 2003;VALIGURA;TALLIN, 2005). Desta forma, a adoção do projeto probabilístico de revestimento de poços está de acordo com tendências mundiais e atuais.…”

“…Nesta etapa, um ponto importante corresponde à definição do modelo mais apropriado para a realização das análises de confiabilidade de revestimentos. Dois modelos são possíveis: um modelo de componente, que considera a falha de cada tubular de maneira isolada; e um modelo de sistema, que considera a associação dos tubulares na composição de cada fase do poço (ADAMS; HODGSON, 1999). São discutidas as peculiaridades de cada modelo e define-se qual o mais recomendado, tendo em vista o contexto mais amplo de otimização em que as análises de confiabilidade estão inseridas.…”