The overall industry trends force companies into toughening their requirements to accuracy and validity of estimations at the stage of conceptual design. As a rule, the estimation involves application of aggregate per unit indicators which do not achieve the required result. A lack of scalable estimations, technical flexibility, as well as high estimation sensitivity to the involved similar facilities demands a review of the standard approaches and application of combined solutions. As an alternative to aggregate per unit indicators the authors propose a comprehensive application of cost data bases of modular comparable facilities (for on-site facilities), and parametric cost models (for linear objects). Due to standardized classification and ability to determine detailed per unit indicators a data base is flexible and adapted to cost modelling for new facilities. Cost models allow to numerically express dependence between the key factors affecting the costs.
This paper gives criteria for developing successful comprehensive expenditure estimation models, tools available to improve the estimation accuracy, and describes a practical case where the proposed method was used. The analysis of differences between initial estimates on the basis of aggregate per unit indicators and results of estimation where the proposed method was applied that the authors conducted allowed, on the basis of available actual construction cost figures, to conclude that a comprehensive approach is efficient. Efficiency was assessed through not only enhanced accuracy, but also the speed of capital expenditure estimation. Thus, an integrated technical and economic upstream CAPEX modelling at a pre-FEED stage allows: 1) to adjust the estimation to the peculiarities of each particular project; 2) to analyze the impact of the estimation and cost parameters for certain facilities at the level of technological blocks; 3) to increase the accuracy of the project estimation and benchmarking, as well as reduce the investment decision risks even with no full input data for technical characteristics of construction facility.
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