Many of today's well construction projects are technically and economically challenging. Examples include deepwater exploration wells in the Gulf of Mexico, offshore field development projects such as Hibernia, Newfoundland, Canada and onshore field development projects in tectonically active regions such as the Cusiana field in Colombia. Minimizing non-productive time associated with wellbore instability and unexpected pore pressure regimes reduces the risk of dangerous accidents and is required to complete the well on time and within budget. Minimizing non-productive time is a complex task that requires thorough pre-spud planning to identify drilling risks and geological hazards and to develop contingency plans for handling those risks. Building a mechanical earth model during the well planning phase and revising it in real time has proven to be extremely valuable in delivering complex wells safely while minimizing unplanned well construction costs. Monitoring and revising the model while drilling requires geomechanics expertise, teamwork, data management and excellent communications among service companies and their client. This paper defines a mechanical earth model, explains why it is important, how it is developed and how it is applied to well construction and field development. We will discuss sources of information and the multi-disciplinary team approach required to: generate, revise and maintain an earth model. Three examples of the application of the earth model concept are discussed. Introduction More of today's well construction and field development projects are both technically and economically challenging. Understanding the geomechanics of well construction is becoming increasing important in order to drill technically and economically challenging wells on budget. Wells with hostile pore pressure and fracture gradient profiles require a good pre-drill pore pressure and fracture gradient prediction in order to design a suitable casing program. A casing program designed on a profile significantly less hostile than that encountered may compromise the attainable TD of the well. The cost of materials and rig time spent running extra casing significantly adds to the cost of the well. The risk of taking kicks which can be both costly and dangerous can also be reduced by a more rigorous pre-drill pore pressure prediction coupled with real-time pore pressure analysis from LWD measurements. In the deepwater Gulf of Mexico there are examples of wells which require a good mechanical earth model (MEM) in order to be drilled at all. Despite decades of industry attention, wellbore instability is responsible for many costly stuck pipe incidents. Stuck pipe is responsible for lost BHAs and considerable NPT spent freeing pipe, performing additional wiper trips and hole cleaning. In cases where wellbore stability problems are severe, the economics of developing a field can become challenging, for example the Cusiana field in Colombia, S.A. Other fields where lesser wellbore stability problems may still challenge the field economics are found where the cost of drilling is very high, e.g. the Hibernia field offshore Canada and or fields in the North Sea.
Within conceptual design changes occur rapidly due to a combination of uncertainty and shifting requirements. To stay relevant in this fluid time, trade studies must also be performed rapidly. In order to drive down analysis time while improving the information gained by these studies, surrogate models can be created to represent the complex output of a tool or tools within a specified tradespace. In order to create this model however, a large amount of data must be collected in a short amount of time. By this method, the historical approach of relying on subject matter experts to generate the data required is schedule infeasible. However, by implementing automation and distributed analysis the required data can be generated in a fraction of the time. Previous work focused on setting up a tool called multiPOST capable of orchestrating many simultaneous runs of an analysis tool assessing these automated analyses utilizing heuristics gleaned from the best practices of current subject matter experts. In this update to the previous work, elements of graph theory are included to further drive down analysis time by leveraging data previously gathered. It is shown to outperform the previous method in both time required, and the quantity and quality of data produced.
Until now, SPC had represented a poorly understood and remains a questionable clinical practice intervention. Education initiatives are required that alert mental health practitioners to the dangers of SPC for patients and practitioners alike, and to present alternative interventions containing less risk.
Objective: This study examined the relationships between appraisals of the physical environment with the subjective experience of consumers, and work satisfaction of clinicians, in Child and Adolescent Mental Health Services (CAMHS). Design, setting, and outcome measures: A survey of clinicians, parent/guardians, and child/adolescents was conducted across eight community CAMHS in Western Australia. Respondents evaluated the waiting room and therapy rooms on a number of environmental attributes, and factor analysis was carried out to confirm that these ratings loaded on an overall appraisal of the physical environment measure. This measure was thencorrelated with self-reported subjective experience of consumers, and overall work satisfaction of staff members. Results: Clinicians were found to be much more critical of the physical environment compared with consumers. Moderate associations were found between appraisal of the physical environment and subjective experience of consumers. A strong positive association was found between clinician appraisal of the physical environment and overall work satisfaction. Conclusions: The present study adds to the limited existing research arguing for the important role that the physical environment can have upon both consumer and staff experience in mental health settings. The present study provides empirical evidence to justify steps being taken to enhance the physical environment in mental health clinics. The inter-relationship between physical environment attributes suggests there is potential for managers to improve the overall perception of clinic space via relatively small actions (e.g., adding a nice piece of artwork). Abbreviations: CAMHS – Child and Adolescent Mental Health Services.
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