Simulation of Multi-Echelon Logistics Network for Gazpromneft-Angara

Simulation of Multi-Echelon Logistics Network for Gazpromneft-Angara

Quantitative estimation and comparison of supply network design options for oil extraction facilities in Siberia developed by Gazpromneft. Using the simulation to select the best strategy of logistic network deployment.

Period: January 2015 – October 2015
Industry: Oil and Gas
Client / Partner: Gazpromneft-Angara / BRIGHT Group

Project objective

  • Development of the logistic network “Angara” organization plan considering the schedule of field development in East Siberia
  • Determination of the optimized logistic network development scenario

The main stages of work and characteristics of the model

  • Setting up a modeling problem
  • The simulation model concept development
  • Development of the simulation model on the AnyLogic platform
  • Verification of the model

Model input data

  • Transported objects data (materials and end-products)
  • Technical characteristics and limitations of used transport (speed of transportation, capacity by transportation categories, etc.)
  • Existing logistic network configuration (number and allocation of ports, supply bases, stacking areas, etc.)
  • Cost parameters of logistic network operation
  • Corridor of critical materials stock rate and moments of delivery
  • Profiles of end-products requirement and production
  • Regional (external) cargo flows

The main structural elements of the model

  • Input data file of scenario in MS Excel format
  • User interface which allows to customize the key parameters of scenarios
  • Simulation model with interactive presentation
  • Data aggregation module that allows to generate MS Excel files with the simulation results

Model output data

  • Average cost of delivery per piece of cargo
  • Total costs by month
  • Requirement for storage capacity on stacking areas and onshore bases by storage types
  • Transport and cranes utilization

Project result

Logistic network development options are evaluated using the operational and financial indicators