Reservoir Surveillance of Mature Floods Using Streamline-based Workflows
Streamline-based (SL) flow simulation has traditionally been viewed as a modeling approach that is complementary to other flow simulation methods. However, streamlines are also ideally suited to the much more common application of reservoir surveillance of mature heavy oil water and polymer floods. Because the streamline paths themselves yield well drainage regions and well-pair allocation factors, engineers can easily reduce complex production data down to the pattern level. Streamline based patterns then highlight areas of fluid cycling vs. efficient use of injected fluids, or longer term metrics such as overall pattern production. Furthermore, knowing well pair connections and pattern efficiencies then provides the basis of flood optimization via updated well rate targets to promote sweep vs. fluid cycling.
The elegance of a streamline-base surveillance model is that it accounts for historical flow rates, well geometry, and any level of field geology, meaning it is not subject to an engineer's "best guess" of implied patterns. These are data-driven models that are easy to build and easy to run, yet are surprisingly robust when compared with more detailed history match flow simulation models. In fact, given the ease with which streamline-based surveillance models can be constructed, any large mature water or miscible flood should have a streamline-based surveillance model, as another way to interpret the production/injection data.
At the end of the course, participants will be able to:
- Distinguish between streamline-based dynamic patterns and fixed (geometric) patterns
- Build a streamline-based surveillance model and use it to identify injector patterns, fluid cycling, and flood efficiency
- Use streamline-derived surveillance models to compute “next month’s rate targets” that promote efficient use of injected fluids vs. fluid cycling
Introductory to intermediate
This course teaches engineers that for mature water/miscible floods, recovery is more complex than simple pattern analysis, and that tools are available to quantify the complex flow relationships between injectors and producers. Once flow-based injector patterns and allocation factors are known, it is then possible to determine next-month’s well rate targets that promote ‘good’ connections and demote connections that are cycling fluids.
Who Should Attend
Engineers and technologists in reservoir monitoring, surveillance and exploitation of mature water and miscible floods
Students are encouraged to bring their own dataset exported from either OFM or geo SCOUT, and then to build a surveillance model and well-target model in software used during the training class.
0.8 CEUs (Continuing Education Units) will be awarded for this 1-day course.
To receive a full refund, all cancellations must be received in writing no later than 14 days prior to the course start date. Cancellations made after the 14-day window will not be refunded. Send cancellation requests by email to email@example.com; by fax to +1.866.460.3032 (US) or +1.972.852.9292 (outside US); or mail to SPE Registration, PO Box 833836, Richardson, TX 75083.
Rod P. Batycky, is an expert in reservoir simulation with nearly 20 years of experience in reservoir engineering, flow simulation, and software development. He is a co-founder of Streamsim Technologies, Inc., which was founded in 1997 based on successful research he was involved with while at Stanford University. Today, Streamsim is the industry leader in streamline-based reservoir simulation and streamline-based engineering workflows for oilfield management. Batycky continues to be involved in development of new software workflows, engineering consulting projects, lectures, and training. He has worked first-hand on projects ranging from reservoir surveillance of mature fields, to full-field simulations of CO₂, WAG, and polymer flooding for some of the largest fields in the world.
Batycky received MS and PhD degrees in petroleum engineering from Stanford University, during which time he was also awarded SPE’s Cedrick K. Ferguson Medal. Previously, he worked as a reservoir engineer with Shell Canada on a variety of projects including naturally fractured gas fields, mature waterflood revitalization, and source rock production. Prior to Shell Canada, he obtained a BS in chemical engineering from the University of Calgary. He is currently an associate editor for SPE-JCPT, a member of SPE, a registered Petroleum Engineer with APEGA, and an author or co-author of several publications within the reservoir simulation community.
Marco R. Thiele, Ph.D, P.E, co-founded StreamSim Technologies in 1997 to develop and promote the use of streamline-based reservoir simulation technology as powerful reservoir engineering methodology. He is president of StreamSim Technologies where he is directly involved in the ongoing technology development program as well as training, consulting, and marketing aspects of the business. In 2006, Thiele was named a consulting professor in the Department of Energy Resource Engineering at Stanford University.
From 1994 to 1997 he was an acting assistant professor at Stanford teaching graduate-level courses on reservoir simulation, thermodynamics of phase behavior, and applied mathematics in reservoir engineering. His research at Stanford focused on streamline-based flow simulation, uncertainly in reservoir forecasting, and integrated reservoir management.
Thiele was the recipient of the 2012 SPE Lester C. Uren Award, 1996 SPE Cedric K. Ferguson Medal, winner of 1994 International SPE Student Paper Contest, and a 1991 distinguished SPE speaker invited by the SPE Adriatic section. He is a technical editor for the SPE Reservoir Evaluation and Engineering Journal, and serves on the SPE Primer Series committee.
Thiele has published widely on reservoir flow modeling and application of streamline-based flow simulation to reservoir engineering, and is a frequent speaker on the topic at international conferences and symposiums.