We are happy to announce that the 12th annual meeting of the Streamsim/Stanford History Matching JIP will take place May 3rd and 4th (Tue/Wed), 2016 at Stanford University. This meeting is the last meeting of Phase IV and the beginning of Phase V (2016-2019). All Streamsim clients are invited to attend, but preference is given to current JIP members. Please email us to reserve your spot.

The HMJIP started in 2004 with the ‰ЫПsimple‰Ыќ question as to how streamlines may help reservoir engineers improve well-level history matching while maintaining geological realism. It has since evolved to encompass uncertainty quantification, screening of geological models, field level and well level history matching, generalized sensitivity analysis, probabilistic representation of forecast ensembles, economics, and more.

The upcoming meeting will focus on the EVOLVE workflow, a result of the JIP work and composed of 4 steps:еК(1) screening and selection of geological models; (2) calibration to field-scale measured data; (3) local calibration using well-level measured data; and (4) applying differing forecast scenarios on the resulting ensemble of models. The EVOLVE workflows is depicted below.

The EVOLVE workflow is linear. It evolves and reduces models ensembles in a cascading fashion to create a final ensemble that is robust and practical for forecasting. The triangles represent the reduction of models from an initial set to a smaller set, while the circulating arrows for each step represent the possibility to iterate within each step to tune model selection process.

The meeting will also address potential developments for Phase V, such as

  • Data Assimilation Using Tracer Data

  • Alternative Well-Level Calibration Algorithms

  • Customized Optimization Algorithms and Multi-Objective Function Optimization

  • Forecasting Infrastructure

  • Probabilistic Representation of Ensembles

  • Algorithms, Robustness, UsabilityеК

  • Value of Information

An important addition to Phase V will be AR2Tech (www.ar2tech.com) joining the JIP. AR2Tech is a company with deep expertise in geostatistics and spatial data integration and run by Stanford PhD‰ЫЄs Alexandre Boucher and HervМ¬ Gross.

The second day of the JIP will be reserved for hands-on training and application of the technology developed as part of the JIP. Bring your laptop and data to get the maximum benefit from this second day.еК