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 floods. Because the streamline paths themselves yield well drainage regions and well-pair allocation factors, engineers can reduce complex production data down to the pattern level by determining injector/producer fluid allocations. 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 also provides the basis of flood optimization via updated well rate targets.
The elegance of a streamline-base surveillance model is that it accounts for historical flow rates, well geometry, and any level of field geology; it introduces a systematic approach to measuring the efficiency of patterns as opposed to more common engineer's "best guess" of implied patterns. The simplicity of streamline-based surveillance models means that they are quick 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, Ph.D, P. Eng., is co-founder of StreamSim Technologies where he is currently involved in commercialization of new technologies for streamline-based simulation, and additionally provides consulting services and short courses world-wide. He is also a technical editor for SPE Reservoir Evaluation and Engineering Journal and Journal of Canadian Petroleum Technology, a member of SPE, and a registered P.Eng. with APPEGA. Prior to forming StreamSim, he was awarded the SPE Cedrick K. Ferguson Medal. Previously, he worked as a reservoir engineer with Shell Canada.
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.