Third EAGE Workshop on Naturally Fractured Reservoirs

Date
5 - 7 February
Location
Muscat, Oman
Registration
Coming soon
Call for papers
Closed

The main topics of this workshop are:

1. What makes a good analogue for calibration

Analogues for calibrating models can come from a variety of sources such as classical outcrop studies, laboratory experiments, flow modelling studies in (generic) fracture geometries, or field surveys from similar reservoirs. Each analogue will provide data at different scales that aim to reduce different types of uncertainty. A key question in this context is when we can translate learnings from analogue studies to improve the calibration of a specific reservoir model and how we can best extract generic rules that can be applied to assist the calibration of a range of naturally fractured reservoir models.

2. At what scale do we need to build a model that we can calibrate

Static and dynamic models are typically built at different scales. In addition, different data (e.g., seismic, well-logs, discrete fracture network models, analogue studies) that can be used for model calibration provide information at different scales. Using these data to translate static into dynamic models and calibrate both requires upscaling and downscaling. A key question is therefore at which scale a reservoir model should be built to best integrate the available data for model calibration and if this scale should be varied over the field life as more data become available.

 

3. How do we use dynamic data to calibrate

Increasingly, reservoirs are monitored in real-time in digital oilfields. This provides ample dynamic data, including but not limited to downhole pressures, well rates, 4D seismic, tracer tests, stress state, or produced water chemistry. These data sample the reservoir geology at different spatial and tempoThird EAGE Workshop on Naturally Fractured Reservoirs 3 ral scales. A key question is therefore how we can best use these different data, possibly in conjunction with assisted history matching workflows, to improve the calibration of naturally fractured reservoir models throughout the field life and quantify uncertainties when predicting future reservoir performance.