Training

This free 1-day session is for exploitation engineers working with mature water, polymer, or miscible floods who want to learn how our studioSL pattern surveillance software can help in mature flood optimization. In today's economic climate of limited capital budgets, there are opportunities to optimize ongoing IOR/EOR floods through low-cost means by applying basic reservoir engineering surveillance work steps.  But to do this, engineers need the correct diagnostics, which is where streamlines and studioSL can make an important difference. This workshop will cover:

• Using studioSL for reservoir surveillance.
• Basics of streamline surveillance and flow simulation.
• Building a surveillance model from production data and maps.
• Surveillance diagnostics including; patterns, allocation factors, and conformance plots.
• Applying material balance to dynamic patterns to generate ROIP maps.
• Rapid forecasting of existing well scenarios such as shutins, reactivations, and prd-inj conversions.
• Setting rate targets for improved sweep and reduced fluid cycling.
• All participants will receive a free copy of our book: "Reservoir Pattern Surveillance of Mature Floods Using Streamlines."

Participants are encouraged to bring a Windows laptop to install our demo software, training notes, and example datasets.

The Date and Location of workshops are provided separately.

The total number of attendees is limited, with a maximum of two participants per company. Priority is given to existing Streamsim customers.  Please contact info@streamsim.com to reserve a spot.  Streamsim reserves the right to cancel a workshop at any time if needed.

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.

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.

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. 
 

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This course assumes students are familiar with reservoir surveillance using studioSL and base reservoir flow simulation concepts.