Integrated uncertainty analysis of a carbonate reservoir in the Gulf of Mexico was performed to quantify the contribution of factors such as lithofacies definition criteria, reservoir structure, total and fracture porosity, net-to-gross cut-offs, and measurement scale disparities on geologic uncertainty. An innovative approach to derive facies definition criteria and net-togross cut-offs based on k-mean cluster analysis is presented. A detailed analysis of scale up of petrophysical properties using the variance of mean concept was performed and its implication on geologic model uncertainty was assessed. Finally, innovative approaches to verify and visualize spatial uncertainty models are presented. A detailed geologic model for the fractured carbonate reservoir was available and the study objective was broken down into an assessment of uncertainty due to:structural model,sedimentary model,petrophysical model, andscaleup/ upscaling. Systematic investigation of each of these aspects as well as a fully probabilistic integration of uncertainty models was performed. Uncertainty in original oil in place was computed by sampling from the component distributions. The study results indicate that the OOIP exhibits significant sensitivity to factors such as cut-offs for lithofacies and net-to-gross definition. An important result that points to a paradigm shift in uncertainty modeling is the sizeable contribution of scale-up to the uncertainty models. The results further reveal that the determination of net-to-gross and lithofacies definition thresholds using cluster analysis vastly enhances the accuracy of the prediction of net-pay at a new well location. The paper presents a complete workflow for integrated reservoir uncertainty assessment. Besides demonstrating the use of data analysis tools such as cluster analysis for deriving more robust criteria for facies and net-to-gross definition, a fundamental contribution of this paper is to demonstrate the role of scale up on uncertainty assessment. While this has been alluded to by several researchers in the past, this paper is the first to demonstrate a modeling workflow that explicitly handles uncertainty due to scale up and promotes the notion of "soft" conditional simulation. Introduction The work for investigating the uncertainty in geologic reservoir models used the current reservoir model built using the Petrel software and developed procedures for assessing structural uncertainties from seismic, uncertainty in lithofacies models, variations in petrophysical properties within lithofacies and uncertainty due to scale-up/upscaling. The specific tasks performed included:Exploratory data analysisEvaluation of uncertainty in structural modelAssessment of sedimentary (depositional) model uncertaintyAssessment of uncertainty in petrophysical modelMultiscale rock properties modelingIntegration of structural, geologic, petrophysical and scale-up uncertainties Uncertainty assessment and reservoir modeling was performed for a particular zone E of the reservoir that is comprised of 5 carbonate facies - dolomite, packstone, grainstone, wackestone and mudstone.

The identification of remaining reserves in mature fields is of importance to extend the field life and production life of existing wells. The Alwyn field in Quad 3 of the North Sea has been producing from the Statfjord Formation reservoirs since 1987. The initial production targeted discrete sand bodies that are separated by laterally extensive shales. The initial field pressure measurements indicated the presence of vertical barriers that have led to depleted pressures in produced intervals. Identification of present-day reservoir pressure in the gas condensate reservoirs was required to determine missed production potential within the Statfjord Formation sand bodies. A candidate well was selected to estimate pressure behind casing by using an advanced analysis method. The method used pulsed neutron data and Monte Carlo stochastic simulation-based forward modelling to evaluate gas condensate reservoir depletion. Conventional thermal neutron capture cross section (Sigma) has low sensitivity to gas density variations, making it unable to detect reservoir pressure changes.

Coiled tubing drilling (CTD) technology has been widely adopted as a cost-effective re-entry strategy to sidetrack from the existing wellbores, and drill high angle/horizontal wells to maximize recovery from remaining oil columns in the Alaska Prudhoe Bay field. The oil rim in this giant field is overlain by a gas cap and has been producing for over 36 years by various recovery mechanisms such as gravity drainage, water flood and miscible injection and hence, holds a complex fluid distribution with locally variable oil-water and gas-oil contacts.Determining current reservoir fluid contacts using multidetector pulse neutron logging (MDPNL) technology is a crucial component in the overall strategy to maximize production from each well and identify future drilling targets. This technology has been widely used in the industry for reservoir evaluation and surveillance in open-and cased-hole environments using conventional wireline techniques in standard borehole sizes. However, logging tool conveyance in CTD wells has been challenged due to small hole size and high angle/horizontal/U-shape wells.An innovative deployment assembly was developed by BP Alaska and Baker Hughes to acquire pulsed neutron data while tripping out of the hole during the wellbore cleanout operation, eliminating the need for a dedicated logging run, which in turn, reduces rig time costs. This deployment assembly consists of a non-magnetic stainless steel carrier and a memory adaptor that is attached to the MDPNL tool. The carrier does not limit tripping operations or wellbore circulation, and requires no wireline for data acquisition.Another major advantage of this assembly is the additional compressional strength provided to the tool, which reduces failure rates and provides a cost-effective well logging solution in highly deviated wells.This paper presents case studies in which this coiled tubing logging technology was applied in the Alaska Prudhoe Bay field. Various aspects of the technology are discussed, including the memoryenabled, three-detector pulsed neutron tool and carrier assembly configuration. The paper also discusses identification of reservoir fluid contacts and other petrophysical properties using the nuclear attributes extracted from MDPNL data, which ultimately provides the critical information needed for optimal perforation strategy and maximize oil production in CTD wells.

No abstract

No abstract