Outcrop Groundwater Prospecting, Drilling, and Well Construction in Hard Rocks in Semi-arid Regions

This chapter presents some recommendations for prospecting, drilling and well construction in hard rocks in semi-arid regions. Considering that these conditions are present in many countries where technology is not always available, the chapter concentrates on the most basic and simple methods to plan where best to drill and maximize success through the direct observation of rock types, weathering and fracturing. The advantage for the geologist and hydrogeologist in an arid or semi-arid environment is that vegetation is normally scarce and the weathering layer thin, allowing a direct view of the rock in circumstances impossible in other climate regions of the world. The close observation of the weathering material, and especially of the fracture network, mainly the fracture density, dip, extension and interconnection, can provide important information for a field hydrogeologist who can then plan the best place for drilling. The most appropriate drilling technique, if available in the area, is rotary percussion, also designated as down-the-hole drilling, with drilling rates that can achieve 100 m per day in normal circumstances. This allows a well to be constructed in about two days, essential in the case of disaster relief. Finally, some information is given about well construction, careful planning of the work, protection to preserve the water quality, avoiding problems of partial or total collapse of the hole during construction or of the well and after completion, and how to avoid direct contact between the surface or sub-surface waters with the aquifer along the walls of the well to protect the well and the aquifer against contamination

Referral and collaboration between South African psychiatrists and religious or spiritual advisers: Views from some psychiatrists

Background. Referral between psychiatrists and spiritual workers (e.g. Christian pastoral care workers, traditional healers, imams, rabbis and others) in the heterogeneous South African (SA) society is complicated and requires investigation to establish appropriate norms.  Objective. To capture the views of some local psychiatrists on referral and collaboration between SA psychiatrists and religious or spiritual advisers.  Methods. This explorative qualitative study involved indepth, semistructured interviews with 13 local academic psychiatrists selected through purposive sampling. Each participant had a single interview with the aim of exploring themes related to the referral and collabora­tion process between psychiatrists and spiritual advisers. Theme content analysis of interview transcripts was done. Results for one of the six identified themes are reported; other results are reported elsewhere.  Results. Within the theme ‘referral and collaboration between psychiatrists and spiritual professionals’, three subthemes were identified: facilitating appropriate referral and intervention for individual users; information sharing and mutual awareness between disciplines; and addressing stigmatisation of users with psychiatric conditions. Conclusion. Dialogue between psychiatrists and religious or spiritual advisers should be developed on an individual practitioner and facility basis, as well as on an organised basis between representative societies. The process of formalising a relationship between local psychiatrists and different spiritual workers may, however, still have some way to go

How to select the best portfolio of oil and gas projects

The traditional analytical tool for selecting portfolios of financial assets is Markowitz's mean-variance model. The final product of this model is the efficient frontier. Markowitz's approach comes up with an infinite set of optimal portfolios in terms of risk and return (called the efficient frontier), but the mean-variance model does not recommend the best portfolio. This paper proposes an extension of the mean-variance model by the inclusion of a three-step approach: i) an estimation of the risk and return of each project; ii) the estimation of a correlation between returns of each pair of selected prospects; and, iii) the i inclusion of corporate goals beyond simple economic return; that i is, budget and operational constraints. We show that the selection of the optimal portfolio depends on the diversification level, of the investor and the costs of financial distress faced by the oil company.475273

How to Select the Best Portfolio of Oil and Gas Projects

Abstract The traditional analytical tool for selecting portfolios of financial assets is Markowitz's mean-variance model. The final product of this model is the efficient frontier. Markowitz's approach comes up with an infinite set of optimal portfolios in terms of risk and return (called the efficient frontier), but the mean-variance model does not recommend the best portfolio. This paper proposes an extension of the mean-variance model by the inclusion of a three-step approach:an estimation of the risk and return of each project;the estimation of a correlation between returns of each pair of selected prospects; and,the inclusion of corporate goals beyond simple economic return; that is, budget and operational constraints. We show that the selection of the optimal portfolio depends on the diversification level of the investor and the costs of financial distress faced by the oil company. Introduction The oil industry has currently been facing high volatility in price, plus technological and geological uncertainties that reduce cost predictability. Since these uncertain factors are all present in most oil and gas projects, they represent a clear motivation for the development of new tools for improving the rationality of decisions in the process of capital allocation. Some of these tools are for the selection of the best portfolio of upstream projects when the main difference between any two portfolios is risk and return. At this point, we wish to make it clear that the screening or selection of oil projects is a previous step and will not be considered in this paper. We assume that the problem consists of finding the best portfolio of already screened oil and gas projects. Not long ago, the selection of portfolios was based on indicators such as ranking and cut, internal rate of return and payback period. When we use any or all of these indicators, the conflicting, but necessary, risk-return trade-off is not considered, so that the optimal decision could have a very high return. On the other hand, however, its risk level may be unsupportable by management. In the past, in the job of finding and producing hydrocarbons, risk was always present, but there was not a systematic pressure policy towards its understanding, modelling and quantification. Presently, in most oil and gas companies, management is not only under pressure to deliver good indicators for the shareholders, but also to estimate the associated risk level. In the context of this paper we consider risk analysis as an integration of three steps. First is the identification of uncertain variables. Second is the probabilistic modelling of these uncertain variables. Third is the use of Monte Carlo simulation in order to get the frequency distribution of response variable, such as net present value (NPV). One reason for the widespread demand for risk analysis in the upstream industry is that trends of resource availability have pointed out that the largest remaining reserves of hydrocarbons are primarily situated in ultra-deep environments where the potential for return is higher but the risk is also huge. </jats:sec

How to select the best portfolio of oil and gas projects?

Conteúdo online de acesso restrito pelo editorThe traditional analytical tool for selecting portfolios of financial assets is Markowitz's mean-variance model. The final product of this model is the efficient frontier. Markowitz's approach comes up with an infinite set of optimal portfolios in terms of risk and return (called the efficient frontier), but the mean-variance model does not recommend the best portfolio. This paper proposes an extension of the mean-variance model by the inclusion of a three-step approach: i) an estimation of the risk and return of each project; ii) the estimation of a correlation between returns of each pair of selected prospects; and, iii) the i inclusion of corporate goals beyond simple economic return; that i is, budget and operational constraints. We show that the selection of the optimal portfolio depends on the diversification level, of the investor and the costs of financial distress faced by the oil company