Kajari Ghosh (email here) of HRP collaborated with Nicholas Harvey (CEO of HRP) and Robert Gales (California Resource Corporation) to present a poster at the AAPG ACE, April 2017 on a unique method of characterizing fracture from borehole image log and its impact in reservoir characterization. Fracture characterization from borehole image log is most commonly used to derive fracture count (commonly as 1D measurement) and orientation. In some cases, it is also used to investigate height, continuity and average fracture aperture. Given the precise resistivity measurement gathered in borehole image, the log can be used for more advanced analysis. Integrating the new analysis with basic geometry of fracture and well bore, the 1D measurements can be transformed into 3D information that provides a more powerful tool address reservoir heterogeneity.
One of the critical fracture dimension that is difficult to measure from borehole image is the aperture. The paper published in AAPG focus on the improved process of analyzing fracture aperture and its uplift in reservoir evaluation. Aperture calculation from image log relies on the resistivity contrast between fracture trace and the surrounding rock. Traditionally fracture aperture is represented by a single value which works well for “parallel plate” fractures but falls apart in the real world where aperture varies continuously along the trace of the fracture. Fracture aperture being the key parameter for evaluating porosity and/or permeability in type 1 or type 2 fractured reservoir it is critical to get a thorough measurement of this property along the entire trace.
To address this issue, we have developed an algorithm that delivers a continuous measurement of aperture along the trace of the fracture to capture the pinch and swell (or parallel plate) nature of the fracture. The figure summarizes an integrated approach to use (multiple point) aperture measurement in identifying zones of dissolution.
In the workflow above, the continuous data is analyzed to identify the outliers in aperture population. The outliers may be due to breakouts or some secondary processes. Based on the genetics of fracture, the aperture variation along the trace can have a wide range with high standard deviation or a narrow range with a low standard deviation.
Using this method on a few reservoirs we worked on shows that standard deviation of of apertures along fracture trace is a reliable indicator of aperture profile. The aperture profile being influenced by various process (like dissolution, breakout or cementation) can be used to classify various groups of fractures that can be investigated against its relation to facies hosting the fracture. Once the relation is established, this workflow provides a more robust means to distribute fracture porosity/permeability by facies in static model.
The method is especially beneficial in carbonate or mixed carbonate system where facies are more likely to be altered by later diagenetic processes causing destruction or enhancement of aperture due to dissolution, recrystallization or filling. Characterizing and classifying the aperture will add to a predictive tool for evaluating fracture porosity/permeability over the field.