Automated Reservoir Model Calibration Applied to a Complex Multizone Heavy Oil Field
This paper presents an automated calibration process, probabilistic infill well ranking, and location optimization for a major heavy oil field in Colombia with original oil in place of more than 5 million STB.
Fully integrated reservoir modeling for field-development optimization under subsurface uncertainty has been a major challenge so far for Rubiales, a major heavy oil field in Colombia with original oil in place of greater than 5 billion STB. An automated reservoir characterization work flow was developed to generate multiple history-matched models on the field and well level. The developed methodology and work flow successfully delivered field-development evaluation under subsurface uncertainty. The work-flow design is applicable for other fields with similar characteristics and delivery objectives.
The Rubiales field is in the southeast of Puerto Gaitán, approximately 310 km from Bogotá. It is the most important oil field in Colombia in terms of extension, original volumes, and production but also is one of the country’s most complex fields, with a variety of technical challenges. Lithologically, the field is an unconsolidated sandstone reservoir with stratigraphic complexity that includes a high degree of vertical and lateral heterogeneity.