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The key to finding the highest-value concept in deepwater full-field development is by making high-quality decisions during the Concept Select stage of a project. One of the critical elements to achieve this is by considering a broad range of conceptual alternatives and evaluating them rapidly, providing timely feedback, and facilitating an exploratory learning process. However, concept-select decisions are challenged by competing objectives, significant uncertainties, and many possible concepts. Further, deepwater full-field developments require strong connectivity and interfaces across multiple disciplines, which include reservoir, wells, drilling, flow assurance, subsea, flowlines, risers, topsides, metocean, geotechnical, marine, costing, and project economics. Key challenges to the current methodology include a lack of capacity to consider multiple concepts, slow evaluation turn-around for each concept generated, continuous evaluation and revisions with new data and information, lack of ability to integrate processes across multiple disciplines, and poor risk management driven by technical/commercial uncertainties and unavailable data. This paper addresses these challenges by combining concepts from the Decision Quality (DQ) framework and FLOCO® (Field Layout Concept Optimizer), which is a metaheuristic model-based system-engineering software, to efficiently identify the highest value field development concepts among several possible alternatives. This novel approach applies a new framework to an offshore deepwater full-field development. Specifically, we explore the trade-space, evaluate the trade-offs between risk and reward, perform integrated techno-economic analysis, and identify the best concepts. Key outputs are the identification of development concepts that meet the given constraints and functional requirements for further optimization, while eliminating those that do not meet such requirements. The results demonstrate that the challenges in the current Concept Select phase can be simplified and that the proposed approach offers a quick, logical, and insightful means of selecting the highest-value concept. The case study demonstrates that the proposed improvement to the concept-select stage of deepwater full-field development process can lead to significantly improved project economics, as it fully explores the decision-space, key uncertainties, multiple technically feasible concepts, and key performance indicators such as net present value (NPV) and capital expenditures (CAPEX). This paper addresses the development of economic oil and gas projects through decision making enhanced by rapid digital prototyping and analysis. The integration of Decision Quality methodologies with systems-engineering decision-support tools is novel and is likely to become more important as the industry explores and develops more complicated targets in the future.

The proper development of an offshore oil and gas field relies on a project's ability to deliver the maximum economic benefits while maintaining safety and environmental targets. In this sense, offshore oil and gas companies have continually evaluated ways to optimize system designs and streamline operations to ensure the achievement of these objectives. A set of technological alternatives that have been highlighted is subsea processing, which requires moving a processing system from the topsides to the seabed. The assessment of subsea processing systems has become an important step during the field development strategy definition, especially in terms of flow assurance by mitigating hydrate and wax formation. When combined with mature subsea production technologies, the potential benefits of deploying subsea processing include enhanced reservoir recovery improved facilities availability, reduced topsides processing requirements, and reduced overall field development cost resulting in improvement of project economics. In addition, depending on the subsea architecture chosen, subsea processing can contribute to reducing the carbon footprint, which is in line with the industry's decarbonization goals. Due to the potential benefits of the subsea processing architectures, new technologies are emerging to overcome the technical challenges to enable this transfer of strategic processes from the topsides to the subsea. The objective of this paper is to present and discuss the mapped subsea processing system archetypes that may significantly increase hydrocarbon production in a cost-optimized way for new fields, tiebacks, and operating facilities. The mapped archetypes are implemented in an Expert System that integrates all technical areas for offshore field development, providing hundreds of conceptual alternatives to understand the impact of using subsea processing systems. This paper provides an overview of promising technologies that have the potential to increase the scope of subsea processing, leading to the identification of the most favorable architectures for each project. This study incorporates a detailed analysis of 27 different subsea archetypes, combining processes such as liquid boosting to host, gas compression to host, two-phase and three-phase separation, produced water reinjection or disposal, seawater injection with sulphate removal, dense phase (natural gas or CO2) boosting to reinjection, gas dehydration, and gas compression. Such analysis indicated that equipment with different technological maturity levels can be combined to create a subsea processing arrangement that meets the project requirements.

The objective of this paper is to present and discuss the philosophy behind the integration of "Model-Based Systems Engineering" (MBSE) with metaheuristic algorithms, referred to as "Model-Based Systems Metaheuristic Engineering" (MBSME), which has demonstrated high potential of techno-economic optimization of large capital projects in oil and gas industry, notably in the automatic and integrated conceptual design and selection of offshore systems architectures. Virtual modeling has always been an important part of systems engineering to support functional, performance and other engineering analysis. The so-called MBSME allows the simulation of several specific System-of-Systems physically addressed in offshore field development, bringing all the benefits of the traditional MBSE approach, and set a stochastic characteristic in the analysis, allowing the project team to focus on a Model-Centric approach, as well as to quickly understand the influence of several combined project strategies and application of different technologies, communicated through a Tradespace exploration map. Due to the characteristics associated with and the countless number of variables of the multidimensional problem addressed in an offshore field development, the integration of "Meta-Heuristic" algorithms with "Model-Based Systems Engineering" has demonstrated a remarkable efficiency and powerful applicability in the search for optimized design solutions in oil and gas industry, especially considering the processes of generation of conceptual alternatives of offshore production systems. This method leads to a reduction of more than 2/3 of the average time currently observed, with an increase in the number of conceptual alternatives evaluated in the order of tens to an order of thousands of options, in an automatic and integrated approach. Although the digital MBSME already developed addresses the combination of all technical disciplines associated with a complete offshore field development, the current work emphasizes the latest R&D achievements, addressing the automatic design and specification of Topside Facilities architecture, combined with the automatic selection of fitting for purpose Production Unit, based on internal requirements, such as the required capacity to support total weight and footprint imposed by the topside facilities’ modules, as well as external requirements, like water depth, surface metocean, type of well completion and oil storage requirements. An example of the MBSME application is presented, demonstrating a three-dimensional Tradespace exploration, relating Net Present Value (NPV), Capital Expenditure (CAPEX) and Breakeven Oil Price, through the application of a computational package in a hypothetical project, reflecting the design conditions of an offshore development in the Brazilian Pre-Salt region. The paper communicates an efficient method to increase the scope and accuracy of conceptual analyses, leading to the identification of the most favorable techno-economic conditions to the particularities of each project, supporting significant increases of return on investments.

As the environmental impact is critical for industry sustainability, early quantifying Greenhouse Gas (GHG) emissions of offshore units represents a central role and step-change improvement across the O&G value chain. Developing an overarching realistic model to estimate GHG emissions is a challenge due to the different methodologies available, the complexity of offshore installations, and the degree of uncertainty in the estimation of emission factors. The present work focuses on the earlier stages of new development, notably in Front End Loading-1 (FEL-1) and FEL-2, i.e., opportunity identification and conceptual engineering studies, respectively. The primary objective of this study is to propose an innovative modeling methodology to quantify Greenhouse Gas (GHG) emissions in offshore production facilities. Since E&P companies consider current and future carbon dioxide equivalents (CO2e) emissions as a factor into capital projects economics, this study additionally proposes a semi-empirical model for OPEX calculation considering the impact related to emissions (on a CO2e basis). Emissions of GHG in the O&G industry typically occur from one of the following general source classes: (i) combustion sources, including both stationary devices and mobile equipment; (ii) process emissions and vented sources; (iii) fugitive sources; and (iv) indirect sources. The projection of carbon emission costs along the asset life cycle is performed to simulate the economic impact of such emission on an OPEX perspective. After estimating the CO2e emissions, the procedure consists of using the "Carbon Emission Cost Projection" to calculate the cost of the CO2 emitted and penalize the OPEX of the evaluated alternative. The proposed model can be used to estimate Carbon Footprint for each one of the several conceptual engineering alternatives evaluated during the conceptual phase of the project, improving not only the techno-economic analysis but also the decision-making process of Capital Projects in the O&G Industry.