Process Safety Analytics
Completed Projects

This investigation was initiated to investigate the occurrence of post-cementing flows in the client’s riserless drilling portfolio. The analysis included a detailed statistical analysis, and engineering and operations assessments to evaluate well design and risk management strategies for riserless drilling operations. The goal of this analysis was to develop engineering and operations standards to satisfy an "As Low As Reasonably Practicable" (ALARP) criterion for risk mitigation. The effort identified key challenges in deepwater environments, such as complications in cement jobs due to long open holes and narrow margins.

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The assessment provided practical and valuable insights into mitigating operational risks, which enabled a refinement in well design and operational practices. Well engineers and project managers implemented the recommendations from this work and subsequently eliminated almost all adverse post-cementing events in the riserless drilling portfolio.

In this project, numerous advanced statistical models were specified to analyze safety incidents in well construction operations, with a focus on addressing the limitations of conventional statistical methods that assume perfect reporting. The intent was to implement a method that explicitly accounts for imperfect reporting behavior (whether intentional or unintentional) by separating the processes of incident occurrence and reporting. Using an operator-provided dataset from 10 rigs over a 24-month period, the study specified probit-based models, and tested various independent variables related to work activities, equipment, supervision, and safety management systems.

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The detection-controlled models provide a practical tool for improving the accuracy of safety data analyses, which can lead to more efficient resource allocation and effective interventions in preventing incidents. Safety managers and field supervisors benefitted greatly from this work, as the insights provided actionable intelligence to refine policies and practices that led to significant and sustained reductions in the client's TRCF and HIPOs.

This investigation examined the likelihood and impact of well control incidents during offshore drilling, completion, and workover activities in the Gulf of Mexico, UK, and Norway. Utilizing a detailed, multi-operator dataset, the study analyzed adverse well control events by severity and duration, focusing on uncontrolled releases. It developed cumulative distribution function (CDF) diagrams to present probabilities, and it included cost estimates for Worst Case Discharge (WCD) scenarios in several different regions and operating environments. Additional outputs included statistical analyses, visualizations of event probabilities, and contextual notes on industry standards and data sources.

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The analysis provides decision-makers with the critical information they need to efficiently manage offshore well control risks. By quantifying the probabilities and costs of well control events, the study supports better decision-making regarding safety protocols, contingency planning, regulatory compliance, and insurance coverage.

These guidelines were developed to support implementation of the "As Low As Reasonably Practicable" (ALARP) decision criterion within the client's upstream business unit. The project involved compiling definitions, requirements, and frameworks from existing corporate standards, along with practical explanations of key concepts like risk tolerability. It delivered a comprehensive guide describing the implementation of the ALARP decision criterion in risk mitigation decisions. It developed a synthetic case study to illustrate progressive risk mitigation scenarios, while emphasizing the need for consultation with senior leadership at key points in the process.

The guidelines provide a standard to support more consistent and informed risk management practices, leading to more efficient operations and better alignment with regulatory and internal standards. The guidelines provide engineers, managers, and other decision-makers with an accessible reference for evaluating options during design and execution, helping to balance mitigation costs and benefits without unnecessary complexity.

This project analyzed safety valve (SCSSV) functionality within an asset experiencing asphaltene deposition. Advanced multivariate analysis was employed to identify factors that affect success/failure of SCSSV function tests. The investigation considered variables related to cumulative production volumes, pressures, temperatures, and mitigation program parameters. The resulting predictive models provide information for production engineers and operators to analyze and optimize the benefit/cost tradeoffs of more frequent and/or more robust mitigation programs to achieve the desired reliability. 

This project developed decision tree models to identify and assess the site-specific risk of underground venting and seafloor broach. The models incorporated key geological and project-specific factors, such as pre-existing faults, fracture propagation, rock properties, and lamination thresholds. The models provide subsurface engineers, well integrity specialists, and operations teams with a practical framework for risk assessment, enabling systematic analysis across the portfolio. The models are especially useful at the screening stage because the analysis can be completed without extensive computational resources.

This project specified multivariate models to examine the factors influencing zonal isolation outcomes (success/failure) achieved after primary cementing. The investigation also included an assessment of the accuracy of expert predictions of zonal isolation outcomes based on cement bond log (CBL) data. A large dataset of deepwater wells was assembled for the analysis and included all relevant information about the wells’ mechanical configuration, drilling history, completion history, reservoir information, and the CBL data. The analysis indicated that the most important drivers of zonal isolation success are related to fluid circulation prior to and during the cement job. Interestingly, there was no evidence that expert predictions based on CBL data were reliable indicators of zonal isolation. The analysis provides a structured approach to understanding cementing challenges as they relate to zonal isolation, providing insights that inform more effective well planning and execution. The results also shed light on the utility—or lack thereof—of CBL interpretations and how much they should or should not be relied upon for decision-making.

This project developed a probabilistic risk analysis framework to inform a critical design decision regarding wellhead pressure ratings for a subsea oil project, addressing uncertainties in geologic properties derived from a small sample of exploration and appraisal wells. The project integrated probability density functions for key geologic variables with a detailed wellbore fluid dynamics model to simulate outcomes for well kill operations under various scenarios. Both conventional probabilistic sampling—and a more efficient experimental design method—were applied to generate cumulative distribution functions for essential design parameters, such as shut-in and bullhead pressures, ultimately supporting risk-based equipment selection decisions.

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The approach developed in this project improves the analysis of geologic uncertainty in high-stakes environments, leading to more cost-effective and informed designs that balance operational flexibility with project timelines. This work established the technical standard by which similar analysis was done within the client for engineering decisions and regulatory determinations.