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Energy infrastructure design system for oil and gas assets

The solution is designed to form tactical and strategic plans for the development and optimization of energy management at new and existing assets

Client

Vertically integrated oil company

Problem

The main problem

The labor-intensive process of calculating electricity consumption and designing power supply for new projects (fields, well pads, assets). The lack of a suitable solution leads to:

Preconditions

Tasks

Key objectives of the project

01.

Increase project efficiency by reducing CAPEX and OPEX

02.

Reduce the labor intensity of processes by reducing the workload on employees and increasing the speed of decision-making

03.

Implement the existing mathematical model and new algorithms

04.

Visualize objects on an interactive map

Technologies

CLIENT

HTML5, CSS3, Angular

SERVER

.NET 6, Python, KeyCloak, container microservice architecture

DATA

PostgresPro, Greenplum

INTEGRATION WITH PRODUCTS

1С, SAP, Geoserver, Scada, SIEM (Arcsight, MaxPatrol)

INTEGRATION MECHANISMS

Kafka, NiFi, API

MONITORING

Prometeus, Grafana

ARCHITECTURE MODELING

ARIS

Solution

To develop innovative system algorithms, the specialized institute St. Petersburg Electrotechnical University “LETI” was involved; these algorithms formed the basis of the solution.

We proposed implementation in three stages:

Functionality

The design system performs:

To develop innovative system algorithms, the specialized institute St. Petersburg Electrotechnical University "LETI" was involved

Project Awards

Winner of the Best Digital Solutions for the Oil and Gas Industry competition in the nomination Best Solution Using Digital Twins of Processes

IX Federal Forum on IT and Digital Technologies of the Oil and Gas Industry of Russia Smart Oil & Gas 2023

Project results

Result of implementation

The system forms tactical and strategic plans for asset development, scenarios for optimal energy management at new and existing assets. Plans are formed by designing or reengineering the energy infrastructure of the asset.

The system implements:

Effects

by 3%

capital expenditures on infrastructure were reduced

by 2 times

risks and errors in processes have been reduced

by 5 times

the speed of calculations has been increased

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