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Reservoir Surveillance using Streamlines
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 pattern surveillance of mature 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 reservoir pattern level. Streamline based patterns then highlight areas of fluid cycling vs efficient use of injected fluids, or longer term metrics such as remaining oil in place (ROIP) from material balance. 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, meaning it is not subject to an engineer's "best guess" of implied patterns. These models can be 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.
Purpose of course: This course is meant for users that are new to studioSL. We outline the theory of streamline-based surveillance. How to build a streamline-based surveillance model in studioSL. How to build a well-rate target workflow of a surveillance model in floodOPT.
Data required: Geoscout /AccuMap exports (.inj, .prd, .xy, .csv, .std) or OFM exports (.cnt, .dev, .ev, .vol) of your field data. Reservoir geological maps (in Zmap format) like Tops and static properties. Examples will be provided for the class.
Reservoir Simulation with Streamlines
Streamline simulation (SL) is now accepted as a complementary tool to finite difference simulation and as a bridging tool between simple surveillance methods and finite difference simulation. Streamline simulation is particularly effective in modeling large, geologically complex heterogeneous systems where fluid flow is primarily dictated by well positions and rates--such as full-field waterfloods. When applicable SL's can yield additional engineering data, such as drainage/irrigation volumes and well rate allocation factors. Example engineering applications range from basic reservoir surveillance to assisted history matching to flood optimization through well rate rebalancing. Other uses include ranking and screening of geo-models, sensitivity studies on flow simulation parameters and assessing upscaling methods.
This course assumes students are familiar with reservoir surveillance concepts already.
Day 1 - Fundamentals of Streamline Simulation
Provides a basic understanding of streamline simulation as well as where/when to use streamlines. Many concepts are presented with multiple hands-on examples.
Day 2 - Streamlines and Flood Management
Emphasis is on mature flood management, an area that is ideally suited to streamlines. The order of the topics is in the order an engineer would use while going from simple and quick results to more complex modeling and forecasting scenarios. Ideally, we work with an in-house data set to build up a streamline model, and then use it to illustrate the below concepts. Here we work with a 'single model' of the reservoir as this is the best way to illustrate concepts in a class-room setting. However, all concepts discussed can be extended to an Ensemble of models which also introduces new issues and is addressed in our more general screening course below.
Screening, History Matching, and Forecasting
studioSL solves a longstanding and difficult problem in reservoir management: quantifying the uncertainty in NPV ensuing from uncertainties related to geological and simulation parameters, forecast scenarios, and economic conditions. The uniqueness of our workflow lies in its selective use of streamlines, distance-based generalized sensitivity analysis (dGSA), calibrating (history matching) to field- and well-responses efficiently, and the use of multidimensional scaling (MDS) with clustering to extract representative model ensembles.
Follow a four-stage, linear workflow in studioSL, that stands in sharp contrast to the traditional idea of a big loop that continuously produces new models until a stopping criteria is met. The novel idea is the repeated evolution and reduction of model ensembles in a cascading fashion as new parameters are injected at various stages of the workflow. The final ensemble is sufficiently diverse in terms of inputs yet calibrated to historical production data and allows a practical yet robust assessment of uncertainty in forecasting future reservoir behavior.
This course assumes students are familiar with reservoir surveillance using studioSL and base reservoir flow simulation concepts.
Custom In-House Short Courses
Are you interested in learning more about streamline-based reservoir simulation? StreamSim Technologies offers in-house short courses tailored to your company and to your needs. Contact us at email@example.com for rates and availability.
Course Through HOT Engineering
Interested in learning more on streamline simulation? Consider taking our 3-day short course organized through HOT Engineering. Click here for more information.
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