fax 01-972-952-9435. AbstractOrocual field is one of the largest growing onshore opportunities in North of Monagas basin, eastern Venezuela. The field is planning to increase its production potential to more than 500% in the next five years. Business plan involve new expansion opportunities with improving field economics. These opportunities include massive development of the shallow heavy oil horizons by steam injection and development drilling in the deeper light and condensate reservoirs. To accomplish such a challenging goal, it was necessary to estimate new requirements for surface facilities while considering both reservoir uncertainties and multiple development scenarios. This paper presents a unique and innovated method and a case-study for integrating multiple-reservoir forecasts with a surface facilities network, with economics and uncertainty. Subsurface responses from five Orocual formations were obtained from ten different reservoir simulation models with their associated well constraints. One single surface network model was used to gather production information from all the reservoirs and likewise was used to develop alternate production scenarios. An automated workflow handled the integration of reservoir production uncertainty, drilling schedule compliance, workover success, economics and varying surface facilities capacities.The procedure that we have developed in this effort permitted the visualization of a more realistic asset performance compared to requirements in the long-term. The procedure also identified future needs for artificial lift.The methodology developed also served as a platform for the exhaustive optimization of wellbore and surface equipment sizing in the presence of uncertainties based on front-endloading (FEL) methodology. The procedure allowed the evaluation of parameters that affect uncertainty in well productivity, drilling schedule compliance, workover success, and varying surface facilities capacities, such as project execution time, workover success, facilities uptime, and facilities spare capacity. SPE 107259uncertainty, drilling schedule compliance, workover success, and varying surface facilities capacities.In general, the automated workflow, developed in this effort, permitted the visualization of a more realistic asset performance in the long-term identification of future requirements for artificial lift. The methodology developed also serves as a platform for the exhaustive optimization of wellbore and surface equipment sizing in the presence of uncertainties.

Located at the northern area of Monagas state, Venezuela is the Santa Barbara and Pirital Fields; known to be two of the principle hydrocarbon fields in the country. Since their discovery, several characterization studies have been done for improving the understanding of its complex geologic structure and fluid column distributions; which vary greatly within each of the eight, independently modeled, sectors of the two fields. Opportunities for improving exploitation plans, of these fields, have been identified based on characterization studies. Accordingly, It was realized the importance of evaluating different scenarios of hydrocarbon production, considering the unique characteristics of each of the eight reservoir sectors, as well as the surface installations capacities for handling production in the short, medium and long terms; taking into account the different levels of risk and uncertainties. This article presents the development of a subsurface-surface model for the evaluation of multiple production scenarios, taking into account the reservoir characteristics, well bore design and surface installations in an integrated manner scoping the unexpected out of plan deviations that was not considered in the initial planning process, as well as the inherent uncertainties of the models used for designing the exploitation plan. This model allows the selection of the most adequate infrastructure for handling Oil and Gas production, based on the reservoir behavior over time and considering the margin of error as a function of the possible risk and uncertainties at the reservoir level as well as delays in drilling future wells and variations in the produced hydrocarbon densities. The results of this model will finally be used for the economic evaluation that decides on the profitability of the projects associated to these fields. This article will focus on the procedure of integrating the different surface-subsurface model components supported by a case history from the area. Introduction During oil and gas fields exploitations plans generation, different kinds of uncertainties are presented wich make a challenge taking proper decisions. According to some authors the uncertainties are associated to technological, economic, political and environmental variables. Each one of those uncertainties can impact in a different way, in different parts of the project; however, certain standards obtained coming from several statistical studies indicate that the ones corresponding to technical variables play the most important place in the total uncertainty of the system. PDVSA has implemented a planning methodology to select the optimal field exploitation strategy, which considers an integrated automatic workflow and involves uncertainties models, called MIAS (sustainable integrated asset modeling) [Acosta et al., 2005; Khan et al., 2006]. MIAS Santa Barbara and Pirital project's objective is to assure optimal short-termfield operating strategies in agreement with long-term reservoir management objectives with social and environmental responsibility.