# Evaluating the Cost Efficiency of Systems Engineering in Oil and Gas Projects
## 1 Introduction
The results of quantitative research in the defense and aerospace industries indicate a relation between systems engineering and success in project management, expressed in time and budget [15; 16; 17; 18]. The results of this [PERSON]'s research [15], based on a study of 43 projects using SE at the amount of 1% to more than 25% of the total funding, show a correlation between the efforts of SE and the success of projects in terms of the budget and time. This fact indicates a positive profitability investment in SE. In joint research of [PERSON] with [PERSON] and [PERSON], the effect of using SE in the development of software systems was calculated based on data from 161 software projects from the COCOMO II database [18]. The effect of using SE in small-sized projects was 18%, and in very large projects it was 92%. Researchers assess the value of innovations in different domains using related assessment methods and a system of economic indicators [19; 20]. In the oil and gas industry, the most famous tool for calculating the profitability of a field is Merak Peep, developed by Schlumberger. However, methods and tools for calculating the value of systems engineering in the oil and gas sector have not been implemented yet. The recognition of systems engineering is growing in many realms of academia and manufacturing. Some universities are currently offering SE courses, which reflects the growing demand for these skills [21; 22; 23]. However, systems engineering is still not widespread in the oil and gas industry, despite the potential benefits. To date, work is underway to study the applicability of systems engineering and assess the benefits of adopting SE practices at different stages of an oil and gas project [24]. Studies into the global experience of assessing SE efficiency based on projects of various types revealed the lack of a universal assessment method; however, individual studies have the potential to be used in developing a method for quantifying the value of SE in oil and gas projects. International experience in the economic evaluation of high-uncertainty oil and gas projects relies on a decision tree used to calculate the expected value of the project, its EMV (Expected Monetary Value). This article presents the results of applying the method based on calculating and comparing the EMV for project options with and without using SE. Based on the general data on project performance, we built a decision tree and a mathematical model, which we used to perform calculations taking an oil and gas project as an example. This allowed us to predict the effect of introducing SE to an oil company's capital project. The results obtained demonstrated the model's performance capability and its possible applications in project resource planning stages. The article includes the following points:  
1. Collecting and analyzing data on the success of projects without using systems engineering and with using systems engineering;
2. Describing the method for constructing a decision tree and a mathematical model for calculating the economic effect;
3. Carrying out a predictive calculation of the effect of using systems engineering in a large oil and gas project in an automated model.