• January 2023 2nd Meeting: SPE Distinguished Lecturer Dr. Rod Batycky

    We have another talk this month! Dr. Rod Batycky, an SPE DL and a cofounder of Streamsim Technologies, Inc, will speak about Streamline Reservoir Surveillance Models to Improve Mature Floods by Low-Cost Actions The talk is at 3:30 PM on Friday, Jan 27 in Room 104 (1st floor) in the Green Earth Sciences Building at Stanford University. Dr. Batycky's bio and talk abstract are listed below. 


    Please RSVP by Jan 25, 2022, to Professor Roland Horne: 

    Speaker bio  

    Dr. Rod Batycky is a cofounder of Streamsim Technologies, Inc., and an expert in reservoir flow simulation with more than 25 years of industry experience.
     He is involved in the development of new simulation technologies, teaches reservoir simulation courses, and he has consulted on the reservoir modeling of water, polymer, CO2 and WAG floods world-wide. Prior to Streamsim, he was a reservoir engineer at Shell Canada.  He has authored several publications in SPE, was awarded SPE’s Cedrick K. Ferguson Medal and the SPE Canada Region Reservoir Description and Dynamics Award.  He is a past associate editor for SPEJCPT, a current associate editor for SPEREE, and an SPE Distinguished Lecturer. He holds a BSc from the U. of Calgary, and MSc and PhD degrees in petroleum engineering from Stanford University.




    In today's economic environment, operators must work to extend the lives of mature fields using low-cost measures. However, identifying reservoir opportunities and forecasting scenarios prior to implementation typically relies on reservoir flow simulation, yet most operators do not have time to build or calibrate such models. Instead, streamline-based surveillance (SLSV) modelling - which has matured greatly over the past few years - offers a practical solution. SLSV models are easier to build and significantly faster to compute than simulation models, and require minimal or no calibration. SLSL models are driven directly by historical production and injection data, can incorporate large scale geological features, and generate unique well-pair metrics for low-cost improvements. For example, while it is easy to identify high water cut/water rate producers, it is challenging to identify the offending offset injectors. Since streamlines naturally define well-pairs, engineers can identify offset injectors attached to producers to promote sweep and reduce fluid cycling. Recent technology enhancements allow SLSV models to additionally generate remaining oil in place maps by applying material balance to dynamic well-pairs as well as rapid forecasts of low-cost management scenarios such as new rate targets, well shut-ins, well reactivations, and/or producer-injector conversions.