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.

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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.

As an offshore asset approaches its designed life, and hydrocarbon production tends to decrease to a non-economic level, the operators have two options: extend the field's life or decommissioning. Decommissioning is the removal or abandonment of the field's assets. The process is complex and can be divided into five main pillars: wells’ plugging and abandonment, subsea structure decommissioning, umbilical/risers/flowlines decommissioning, topside removal, and jacket/hull decommissioning. The processes and alternatives depend on the field's characteristics, such as water depth, distance to coast, the weight of subsea equipment, wells’ history and condition, type of hull, as well as local legislation. All these nuances require comprehension regarding the decommissioning processes to target the most cost- effective alternative. Decommissioning is a costly process. It is necessary to understand the whole development, calculate time for each step and map the daily rate of the infrastructures (boats and equipment) required to estimate the cost by its availability. Depending on the equipment's integrity assessment, the field's life extension can be feasible and should be considered a viable alternative. Based on that, the development of an integrated model based computational system can help abstract the enormous complexity faced in real life, allowing operators to choose the most economically attractive option for a brownfield. This study aims to propose a methodology developed as a digital solution for analyzing alternatives of decommissioning based on user's input. The methodology consists of gathering the possibilities for decommissioning or life extension, applied to each of the main pillars. Based on the results, it is expected that the present work will deliver an important contribution to the industry regarding the adoption of integrated design practices for the technical and economic analysis of brownfields.