A Method for the Modified Estimation of Oil Shale Mineable Reserves for Shale Oil Projects: A Case Study

Sergei Sabanov, Abdullah Rasheed Qureshi, Zhaudir Dauitbay, Gulim Kurmangazy

Research output: Contribution to journalArticlepeer-review

1 Citation (Scopus)

Abstract

The amount if oil shale resources throughout the world has been roughly estimated in accordance with various resource estimation methods. However, in some instances, detailed and comprehensive supporting methodologies for the estimation of commercial shale oil reserves have not been presented. The goal of this study is to develop a comprehensive method for the modified estimation of oil shale mineable reserves for shale oil projects. The methodology characterises oil shale according to its calorific value, oil content, conditional organic mass, and ash content by utilising a Monte Carlo simulation. Based on the results of the case study, the developed method proposes considering the relationships of the in situ oil shale grade and tonnage material (oil shale + limestone) to the oil retorting feed material grade and tonnage by taking into account the retorting plant oil recovery. For this purpose, a Monte Carlo stochastic modelling algorithm was developed. Based on the data analysis, a modifying factor to convert mineral reserves to petroleum reserves was produced. The results of this study are useful for feasibility studies that estimate oil shale reserves in relation to justifying their utilisation fields. Some oil shale deposits have good potential for development but need to be re-estimated in accordance with the most sophisticated extraction and processing technologies.

Original languageEnglish
Article number5853
JournalEnergies
Volume16
Issue number16
DOIs
Publication statusPublished - Aug 2023

Keywords

  • a modifying factor
  • calorific value
  • oil reserves
  • oil shale
  • retorting

ASJC Scopus subject areas

  • Renewable Energy, Sustainability and the Environment
  • Fuel Technology
  • Engineering (miscellaneous)
  • Energy Engineering and Power Technology
  • Energy (miscellaneous)
  • Control and Optimization
  • Electrical and Electronic Engineering

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