Price: 0
Number of applications: 8
13.02.26 (inclusive)
by agreement of the parties
Idea
R&D Tasks
Extraction and processing of hydrocarbons raw materials
New production technologies
Software/ IS
The Kyzyloy and Akkulovskoye fields are complex distributed systems, including wells, crane units, gas treatment plants and compressor stations. Their effective operation is complicated by a number of factors: 1. Unsteadiness of processes: pressure, temperature and flow rate change due to falling reservoir pressure and seasonal factors, which leads to unstable production. 2. Interconnectedness of facilities: changes in one well affect the operating modes of other gas facilities. 3. Corrosion and wear of equipment: the gas-liquid mixture accelerates corrosion, leakage and hydrate formation. 4. Limitations of classical calculations: traditional methods do not allow accurate prediction of optimal operating modes of gas wells. 5. Lack of monitoring: at the Kyzyloy and Akkulovskoye fields, data is collected manually, which reduces the efficiency of analysis and eliminates the use of predictive analytics.
The immediate result of the project will be an intelligent predictive management system for gas assets with the following effect: Reduction of accidents and downtime, Increased efficiency of gas production, Reduction of corrosion damage and hydrate deposits, Digitalization of previously manual processes, and increased industrial safety of personnel through automated monitoring and accident prevention. Reducing the energy consumption of compressor stations through predictive control algorithms is a direct reduction in the carbon footprint. Creation of high-tech jobs and development of competencies in the field of artificial intelligence and big data analysis. Transparency of technological processes: all data is available in real time to regulators and shareholders. Contribution to the scientific and technical reserve of Kazakhstan: creation of unique hybrid models (physics + AI) for gas production. The possibility of publishing in international journals, patenting the developed algorithms and software. Training of specialists in industrial AI and digital modeling.
Malybaev T.
Purpose and description of task (project)
The aim of the project is to develop and implement a digital platform with elements of artificial intelligence (machine learning, predictive and prescriptive analytics), providing: • creation of a digital twin of the field at 35 gas facilities; • construction of hybrid models for forecasting flow rate, pressure and energy efficiency; • predictive diagnostics and prediction of equipment life; • early detection of anomalies by streaming data; • optimization of gas production, transportation and treatment in real time; • automatic generation of management recommendations; • self-learning of models to improve forecast accuracy; • cost reduction and increased reliability of infrastructure.
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