Sampling biases and mitigations in modeling shale reservoirs

Field development of a shale reservoir is different from developing conventional reservoirs because of the tightness of formations and extensive use of horizontal wells. One critical consequence of horizontal wells is the sampling bias. Construction of a reservoir model for a shale reservoir must mi...

Full description

Saved in:
Bibliographic Details
Published in:Journal of natural gas science and engineering 2019-11, Vol.71, p.102968, Article 102968
Main Authors: Ma, Y. Zee, Gomez, Ernest
Format: Article
Language:English
Subjects:
Distribution
Frequency statistics
Horizontal wells
Hydrocarbon resource evaluation
Porosity spatial
Reservoir modeling
Sampling bias
Citations: Items that this one cites
Items that cite this one
Online Access:Get full text
Tags: Add Tag
No Tags, Be the first to tag this record!
Description
Summary:Field development of a shale reservoir is different from developing conventional reservoirs because of the tightness of formations and extensive use of horizontal wells. One critical consequence of horizontal wells is the sampling bias. Construction of a reservoir model for a shale reservoir must mitigate the sampling bias of well data for the model to be realistic, especially when horizontal wells are present. Although geostatistical modeling methods can be effective in modeling spatial distributions of reservoir properties, they generally do not account for a sampling bias. It is necessary to first decouple the debiasing of well data from the 3D reservoir modeling. In this paper, we first present methods to debias sample data from vertical or horizontal wells or a mixture of them. After sample data are debiased, we present reservoir modeling while coupling the honoring of the debiased frequency statistics and the modeling of spatial heterogeneities for shale reservoirs. •Developing shale reservoirs use a lot of horizontal wells or a mixture of vertical and horizontal wells.•Data from horizontal wells or a mixture of vertical and horizontal wells are generally biased.•Debiasing the data from horizontal wells or a mixture of vertical and horizontal wells is necessary to ensure an unbiased reservoir model or gas resource evaluation.•We propose methods for debiasing well data for different well patterns and geological setting.•Our modeling process decouples the debiasing well data from modeling and couples the debiased statistics and geostatistical modeling of reservoir properties.
ISSN:1875-5100
DOI:10.1016/j.jngse.2019.102968