Petrophysical Properties Modeling Using the Geostatistical Approach: Case Study of Barito Basin, Indonesia

Abdul Haris, Brianto Adhie Setya Wardhana, Grace Stephani Titaley, Agus Riyanto

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

The Salemba Field is the largest productive oil field in Barito Basin. This field is located in the north-eastern area of Barito Basin. An improvement was required for the Field development, either from the geology, reservoir, or production aspect. The aim of this study is to build a reliable static reservoir model that can match the production history when it was simulated in the simulation reservoir. In this study, the targeted reservoirs were in the A and B zones, which have the biggest oil production. The A and B zones represent the most productive units in the synrift filling sequence in Tanjung Formation, which mainly comprises medium to coarse grained sandstone, well to moderately sorted volcanic litharenitic and feldspathic litharenitic sandstone, and volcanic pebble-dominated conglomerates. These reservoir zones are separated by a continuous shale break indicating differences in the depositional event. Modeling the distribution of A and B zones was guided by a detailed well-to-well correlation, tracer data and production history as a data constraint. The integrated interpretation of these data was then used to derive net sand maps which were used as trends to guide geomodel facies and properties modeling. After building the conceptual reservoir element distribution model, geostatistical analysis for facies parameter population was conducted. Probability distributions for net sand maps and vertical proportion curves for facies distribution variability were also constructed. The reservoir rock type is defined by Flow Zone Index (FZI) equation combined with geology facies interpretation. The rock type will guide to generate permeability transform and J-function equation to distribute permeability (k) and water saturation (Sw) in the model. Our experiment shows that the model has a good agreement with the geological interpretation and production data. In addition, the base case model represents the best estimation. This model has been analyzed using a dynamic model and has shown a good simulation.

Original languageEnglish
Title of host publicationAdvances in Petroleum Engineering and Petroleum Geochemistry - Proceedings of the 1st Springer Conference of the Arabian Journal of Geosciences, CAJG-1 2018
EditorsSantanu Banerjee, Reza Barati, Shirish Patil
PublisherSpringer Nature
Pages33-37
Number of pages5
ISBN (Print)9783030015770
DOIs
Publication statusPublished - 2019
Event1st Springer Conference of the Arabian Journal of Geosciences, CAJG-1 2018 - Hammamet, Tunisia
Duration: 12 Nov 201815 Nov 2018

Publication series

NameAdvances in Science, Technology and Innovation
ISSN (Print)2522-8714
ISSN (Electronic)2522-8722

Conference

Conference1st Springer Conference of the Arabian Journal of Geosciences, CAJG-1 2018
Country/TerritoryTunisia
CityHammamet
Period12/11/1815/11/18

Keywords

  • Barito basin
  • Dynamic model
  • Facies
  • Geostatistical
  • Indonesia

Fingerprint

Dive into the research topics of 'Petrophysical Properties Modeling Using the Geostatistical Approach: Case Study of Barito Basin, Indonesia'. Together they form a unique fingerprint.

Cite this