Sustainable Waste Management Drilling Process in Fuzzy Environment

Abstract

Sustainable management issues of waste during drilling oil wells in marine conditions, the process of disposal of drill cuttings in the conditions of deficiency, and fuzzy initial information using fuzzy inference system are investigated. Based on the conducted system analysis, the main criteria for controlling the process of re-injection of suspended drill cuttings were analyzed and selected. We described the technology of preparation and injection of drill cuttings slurry into the underground horizon. The method of modeling and management of the process of disposal of drilling cuttings in the marine environment in a fuzzy environment with the use of fuzzy inference system, which helps to overcome the problems of scarcity and fuzziness of the original information due to the knowledge and experience of experts are proposed. The scheme and structure of the elements of the fuzzy inference system based on the Mamdani algorithm are given. The implementation of the fuzzy output system procedure was carried out in MatLab using Fuzzy Logic Toolbox. For the purpose of sustainable waste management in the process of oil production of marine fields, waste management tasks are formulated as a fuzzy mathematical programming problem, which takes into account economic and environmental criteria and many production constraints that may be fuzzy. Since the vector of such criteria is characterized by inconsistency, the developed methods for solving the set tasks of sustainable management are based on various tradeoff schemes modified to work in a fuzzy environment. The novelty and originality of the developed methods lies in the fact that, unlike the well-known methods of similar methods for solving fuzzy problems, they are set and solved without conversion to a system of equivalent deterministic problems, with-out losing the main part of the collected fuzzy information. This allows, through the full use of the original fuzzy information, to obtain a more adequate solution to the fuzzy problem of the real problem under production conditions.

Models for Oil Refinery Waste Management Using Determined and Fuzzy Conditions

“…, β L ) constraints. Then, by combining various compromise decision-making schemes for criteria and constraints and modifying them to work in a fuzzy environment, it is possible to formulate and solve various MD problems in a fuzzy environment [25,33].…”

“…The main idea of the heuristic approach to solving problems in conditions of scarcity and fuzziness of the initial information is that the knowledge, experience and intuition of a person (DM, expert) is taken into account and used in solving the problem, i.e., formalized fuzzy information using fuzzy set theories [19,[21][22][23][24][25].…”

“…This is because in conditions of uncertainty of the fuzzy nature of the information, the possibility of conducting experiments under the same conditions are not satisfied [21,22]. In this regard, the development and application to solve problems of optimisation and waste management in a fuzzy environment is currently a promising and relevant direction [23][24][25]. Interesting results were obtained in sustainable waste management when drilling oil wells in marine conditions using a fuzzy inference system [25].…”

“…In this regard, the development and application to solve problems of optimisation and waste management in a fuzzy environment is currently a promising and relevant direction [23][24][25]. Interesting results were obtained in sustainable waste management when drilling oil wells in marine conditions using a fuzzy inference system [25].…”

Environmental governance investment and Air Quality: Based on China’s provincial panel data

“…World Health Organization (WHO) has released air quality guidelines (AQG) 2021 for short and long term exposure to various air contaminants, approximately 15 years after the 2005 AQGs, such as particulate matter (PM2.5 and PM10), ozone (O3), nitrogen dioxide (NO2), sulfur dioxide (SO2) and carbon monoxide (CO) (Amini, 2021;Kan, 2022). Air pollution consists of various particles, including sulfur oxides, nitrogen oxides, and carbon monoxide, these particles result from factory emissions, dust, transportation, as well as several other pollutants (Husain T et al, 2021), and is rising due to industrialization, urbanization, rapid population expansion, and other causes (Nagdeve, 2006;Orazbayev et al, 2019). However, air quality is not only related to gas emissions, but also to solid waste production, the indirect determinants of air pollution have also received increased attention.…”