This paper presents an ongoing work in on the future of telemedicine in O&G. There has been a huge development in the use of video consultation between remote patients and the doctors. We believe the future of telemedicine in O&G will add to this workflow by investigating how we can transfer visual medical data between "offshore nurses" and "medical experts" at hospitals onshore in order to improve diagnostics and treatment. We will describe a decision support system that supports an optimal workflow and collaboration, between medics onshore and offshore. The goal is to make better and faster medical decisions, and improve the quality of healthcare offshore. The oil companies have much of the same structure and same challenges in remote medical treatment. We investigate an optimal workflow including how technology supports a new telemedicine work process by transmitting very high quality information (e.g. ultrasound images) to the cardiovascular medical experts. We will review our work on developing a prototype "on the go" solution between medics offshore and the medical experts onshore at the hospital. The concept will be based on a Pad/PC solution capturing the ultrasound image transmission between the user and experts, a systematic work process and a knowledge base integrated in the Pad/PC "on the go solution". With optimal workflow it should not take more than 5-7 minutes from the starting point to have a decision from the medical expert. This will improve diagnostics, medical safety and health quality on offshore installations.

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SPE Member Abstract This paper outlines a reservoir-economic approach and quantifies the microeconomic adjustment of the exploitation of different types of petroleum reservoirs by means of a numerical optimization model. The numerical reservoir-economic optimization will be presented here. In this model the microeconomic adjustment is viewed in relation to reservoir engineering. The model optimizes the exploitation of an oil or gas reservoir in terms of:Total depletion rate (production capacity, including the aspects of Maximum Efficient Rate) and,Geographical distribution of total production capacity (well density, number of production capacity (well density, number of platforms, etc). platforms, etc). The model can be adjusted (calibrated) to the reservoir simulations of a specific oil or gas reservoir. The generation of production profiles is based on a limited number of reservoir simulations. This information is used to generate a fine network of production profiles in the reservoir module. The income side is coupled with a reservoir cost module and the optimal solution is sought in the net present value surface. The model is used for present value surface. The model is used for further economic analysis in different economic, financial and taxation modules. It may serve to improve the general understanding of the effects of reservoir economics on the engineering decision-making process, and as such is a tool for communication between economists and reservoir engineers. ECONOMIC ADJUSTMENT IN A SIMPLIFIED TWO-PERIOD MODEL OF PETROLEUM EXTRACTION The purpose of this section is to study the exploitation of petroleum reservoirs by a simplified two-period extraction model in order to give some analytical background to the main ideas in this paper. paper. The capital costs are incurred in Period 1, whereas the production, and therefore the net income, are in period 2. This simplification is illustrated in Figure 1. Furthermore we assume that the amount of extracted petroleum (Q) is a concave function of factor inputs (E), illustrated in Figure 2. This resource-recovery relationship captures the first order element of the marginal reserves within the single petroleum reservoirs in relation to the geographical distribution of production equipment (number of platforms), or to more extensive investment in enhanced oil recovery methods. We disregard at this stage the second order element which has to do with the choice of production capacity and rate-sensitivity. We shall production capacity and rate-sensitivity. We shall return to this element later. We define the following variables E = factor inputs Q = F(E) = extracted amount of petroleum (resource recovery) P = price of petroleum P = price of petroleum W = price of factor input r = discount factor = profit R = revenue C = costs The oil company will make an economic adjustment in order to maximize the net present value (the profit): (1) The first order condition for maximum: (2) The second order condition for maximum is assumed by the concave function. The producer adjusts according to marginal revenue (R/ E), equal marginal costs (c/ E) or when the slope of the product function (F/ E) is equal to the price vector, illustrated in Figure 2. From an inspection of these adjustments we observe that when the economic factors (P,W,r) change, the oil company will accordingly adjust the optimal factor inputs in order to maximize profit: (3)