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					 Calculating Fracture Intensity
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					Crain’s Method The various log derived fracture indicators can be merged through
                a computer program which allows a wide variety of inputs. The
                input curves are assigned a threshold value, a median value, and
                a maximum probability as a fracture detector. In addition, each
                input is weighted according to its correlation to natural fracturing
                in the specific area. This form of program lends itself to a small
                rule based expert system.
 In
                most areas, the major weighting is assigned to the shear attenuation
                from the sonic waveforms and to dipmeter differential conductivity.
                Lesser weighting is assigned to compressional attenuation, caliper
                rugosity, density correction, deep to shallow resistivity ratio,
                and uranium content. Where oblique fracturing are expected, the
                shear input may be weighted lower and the compressional input
                weighted higher. The output of the program is a fracture probability
                curve.  A
                    simple form of the equation would look something like this1.
                            CFI = ((RESS<RESD) + (PHID>PHIN+0.05) + (DTC>200)
                            + (GR>150) + (PE>5.5) + (CAL>250)
 + (DCOR>250)
                            + DELTA_CAL>50)) / NTEST
 Where:CFI = calculated fracture index (fractional)
 RESS = shallow resistivity
 RESD = deep resistivity
 PHID = density porosity
 PHIN = neutron porosity
 DTC= sonic travel time
 GR = gamma ray
 PE = photo electric effect
 CAL = caliper
 DCOR = density correction
 DELTA_CAL = differential caliper
 NTEST = number of thresholds tested
 This
                equation is written for a specific case; curves can be added or
                deleted and thresholds adjusted to suit the circumstances. 
 
 
			In the 
			above sample, units are Metric – CAL in mm, DTC = usec/m, and DCOR 
			in kg/m3.Whether 
			RESS is higher or lower than RESD will depend on mud resistivity and 
			zone is wey or oil/gas. If zone is wet, fresh mud gives RESS > RESD 
			as the mud invades the fracture. Fresg mud in fractures in oil zone 
			– usually RESS < RESD. Salt mud and oil-base muds would behave 
			differentlt.
 The equation is trying to quantify the fracture location rules shown 
			in the examples of how each log curve responds to fractures.
 
 You need to look at the logs to see what they are doing – are RESS 
			spikes lower or higher than RESD? Do all resistivity curves spike to 
			lower values? Set CAL, DCOR, and DELT trigger levels apptopriately 
			for the log response and log scales.
 
 
 In the example shown
				above, all curves have equal
                weight, and the amount of excursion of a curve beyond its threshold
                is not considered. The result is normalized between 0.0 and 1.0
                by the value of NTEST. More elaborate fracture intensity indicators
                are common, using the amount of the curve excursion above the 
			thresld to weight that vurve's contribution to the total fracture 
			intensity.
  
  Open hole fracture indicator (CFI) compared to FMI results
 The CFI curve and micro-scanner
                fracture intensity (frequency or fractures per meter, labeled
                FREQ) track each other reasonable well. There is a strong correlation between the FMI data, which
                represents ‘ground truth’, and the CFI curve. This
                does not always happen and the CFI must be calibrated to each
                specific case. Note
                the Fracture Aperture (APER) and Fracture Porosity (PHIf) curve
                values are very small, but typical of most fractured reservoirs.
                Matrix porosity (PHIe) is significant and overwhelms the fracture
                pore volume. It
                is sometimes possible to relate the sum of CFI over an interval
                to drill stem test flow capacity (KH) or to well productivity
                (IPR or AOF). CFI can also be compared and calibrated to fracture
                intensity (fractures per meter) from formation micro-scanner processing.
                This is useful when only a few wells have FMS or FMI data while
                others do not.
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