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tool. The MDT results from eight drawdown pretests and one tight pretest correlate closely with mobilities extracted from Stoneley-wave analysis (right). The continuous mobility log exhibits high mobility inside sand packages and low mobility near shale streaks and at the depth of the tight MDT pretest. Because the Sonic Scanner mobility results are somewhat sensitive to a few parameters that are not well constrained by logging measurements, such as mud slowness, mud attenuation and mudcake stiffness, tests were conducted to study the effect of uncertainty in these parameters on the mobility error bars. The continuous mobility log shown is the one with the least uncertainty.


0 6 0 1 .9 6


When the borehole is in good condition, continuous mobility logs from Stoneley waves can be used to obtain a quick permeability estimate for selecting sampling points and perforation intervals, and may function as a supplement to core or formation-tester permea- bility points over an extended interval. Stoneley waves can also be used to characterize permeability associated with open fractures. In the US Rocky Mountains, for example, hard-rock reservoirs depend on hydraulically induced fractures for economic production. However, the highly unequal in-situ stresses in the region give rise to natural fractures too. If natural fractures are encountered in a well, cementing and stimulation designs must be adjusted to prevent cement from entering the natural-fracture system. For example, fiber-based treatments for both cementing and stimulation can be used to reduce fluid losses.1 9


Stimulation


programs need to take into account the magnitude and direction of the principal stresses. Optimizing the completion design requires knowledge of the fracture and stress characteristics around the wellbore and in the formation. An open fracture intersecting a borehole causes Stoneley waves to reflect and attenuate.2 0 Analysis of Stoneley waveforms quantifies these changes, which are input to an inversion for fracture aperture.2 1


However, washouts, borehole


rugosity and abrupt changes in lithology also can cause Stoneley reflections, and should be considered in the analysis.2 2


An example of successful application of this method comes from Colorado, USA.2 3


In this gas


reservoir, porosity ranges from 3 to 7% and permeability is in the microdarcies. Stoneley- wave analysis


quantified the aperture and permeability of fractures that were also seen on


1


P orosity m3 / m3


0


G amma R ay gAP I


Caliper in.


Shale V olume m3 / m3


1


Density g/ cm3


2 .9 6 1 5 0 1 6


3 0 0 3 0 0


Compressional ∆T µ s/ ft


0


Shear Slowness µ s/ ft


µ s/ ft 1 0 0


Stoneley Slowness 3 0 0


1 2 0 0 3 0 0 2 4 0


R econstructed Stoneley µ s/ ft


2 0 0 1


M ud Slowness µ s/ ft


4 0 1


M DT M obility mD/ cP


Shale 1 0 ,0 0 0


M obility E rror B ar M obility E rror


Stoneley M obility 1 0 ,0 0 0


mD/ cP mD/ cP


1 0 ,0 0 0


B ound W ater Sand


O il


W ater Coal


X ,X 0 0


X ,X 5 0


> Com paring  uid-m ob ility values from MDT pretests w ith those from Stoneley -w ave processing in a Statoil w ell in the Haltenb ank en area of the Norw egian Sea. In Track 3 , continuous  uid-m ob ility values ( b lue curve) and uncertainties ( gray shading) estim ated from Stoneley -w ave analy sis correlate w ell w ith discrete m ob ility values ob tained from MDT draw dow n pretests ( red dots) . The tw o m easures of m ob ility m atch even at the tight MDT pretest at X , X 4 2. 15 m , w here the Stoneley m ob ility also show s an ex trem ely low value. Porosity , gam m a ray , density , caliper and shale volum e are plotted in Track 1. Track 2 show s acoustic slow nesses. Track 4 display s relative volum es of lithology and  uids.


26


Oilfield Review


Depth, m


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