Inferring fluid-filled fractures presence using S-wave attenuation on microseismic events Guillaume Bergery*, Total; Ted Shuck, Dave Diller, Nanoseis; Marc Grausem, Total Summary We disclose a method based on S-wave attenuation to infer fluid-filled fractures using microseismic monitoring. Since S-waves do not propagate through fluids, they offer a way to distinguish between wet (water or oil-saturated) and dry (gas or air-saturated) fractures within the stimulated reservoir. We applied this principle to a hydraulically fractured horizontal wellbore to indirectly map the stimulated fractures. Introduction Hydraulic fracturing optimizes the connection between reservoir and wellbore. It enables the hydrocarbons to flow more easily by creating fractures in the formation. Those are created by pumping fluids at a pressure exceeding the fracture pressure. This stimulated connected volume will participate to the production of the well. Recording the microseismicity triggered by the hydraulic treatment is one of the few tools that permit assessing the volume in which the formation was affected. Nevertheless, this “activated” volume calculated from the microseismic monitoring does not provide an exact value of the actual Stimulated Rock Volume, SRV (the one which participates to the long term well production). Microseismic monitoring will indeed image the volume stimulated by the hydraulic fracturing (induced microseismic events) as well as pre-existing faults surrounding the hydraulic fractures that will slip when the pore pressure increases (triggered microseismic events). The SRV is then embedded within the microseismic volume. Further interpretation is needed to assess the efficiency of the effective proppant treatment. In 1979 Toksöz et al. showed in laboratory the large attenuation of S-waves in cracked, saturated rock. Recently Tan et al. used the S-wave attenuation from perforation shots to map the growth of the stimulated reservoir volume in the Marcellus gas shale (2014). Here we are extending this technique to use the microseismic events as the source generating the S-waves in addition to the perforation shots. The principle can be summarized as follow: a microseismic event will generate both P and S waves that will travel within the formation. When propagating through a fluid-filled fracture, the S-wave will be strongly attenuated. Computing the S-wave attenuation will then highlight the fluid-filled fractures.

The microseismic monitoring experiment (2013) A 5 stages horizontal well has been hydraulically fractured and monitored using both a dense surface network of 30 000 mono-component geophones and a string of 24x3C geophones deployed in a nearby vertical observation well as shown on Figure 1. The two networks (surface and borehole) were clock synchronized using GPS.

The two wells trajectories are in the same vertical plane and the observation well is facing the toe of the frac’ed well. This is an ideal case for applying the S-wave attenuation method described in the following section. The waves generated by the microseismic events will indeed propagate through the formation affected during the previous stages before reaching the observation well.

Figure 1: Schematic of the microseismic network used. The black squares symbolized the geophones. The treated well trajectory is drawn in blue and the observation well trajectory in pink. Top: map view. Bottom: 3D view.

Inferring fluid-filled fractures presence using S-wave attenuation on microseismic events

The surface network recorded continuously the 5 stages when the borehole array had to be pulled out of the hole for stages 2 to 4. As a result only stages 1 and 5 where monitored using both the surface and borehole arrays. Observation A microseismic event recorded by the borehole array is presented on Figure 2 to illustrate the S-wave attenuation effect. This attenuation is observed for individual events that rays passed through the reservoir zone. The amplitudes have been corrected for the radiation pattern of the microseismic event as described in the next section.

Methodology The first step was to detect and locate the microseismic events recorded by the surface array. This was done using a Source Scanning Algorithm (from Honn Kao and Shao-Ju Shan, 2004) accounting for the focal mechanism polarity reversal. As a result the moment tensor was retrieved, including its non Double-Couple part. An example is shown on Figure 3. Once the location and moment tensor inverted, it is possible to compute the theoretical radiation pattern in 3D as described by B.L.N. Kennet in 2001. An improvement to

the method would be to propagate the radiation pattern in 3D as described Graves in 1996 (see Figure 3).

The next step is to compare the amplitudes measured on the borehole records with what should theoretically be recorded. That’s why it is necessary to compute the radiation pattern as the P and S-wave amplitudes directly depend of it. In order to do this we advocate the S-wave attenuation factor which uses the ratio between the P and Sh wave amplitudes:

Sf = 𝑂𝑏𝑠𝑒𝑟𝑣𝑒𝑑 𝐴𝑃

𝐴𝑆ℎ

𝐸𝑥𝑝𝑒𝑐𝑡𝑒𝑑 𝐴𝑃𝐴𝑆ℎ

(Equation 1)

with AP the amplitude of the P wave and ASh the amplitude of the horizontal S wave. The more the S-wave gets attenuated the higher the S-wave attenuation factor. This S-wave attenuation factor is computed on the microseismic events recorded by the geophones deployed in the observation well. The traces are rotated towards the P-wave arrival direction into L,Q,T system to account for the orientation of the 3-component geophones and to maximize the P-wave amplitude. The Sh-wave amplitude is

Figure 2: Bottom: seismogram of an individual microseismic event recorded by the borehole array of 24x3C geophones; color coded by amplitude. Top: ratio between the amplitude of the P wave and the amplitude of the horizontal S-wave. The ratio is greater for the waves that traveled through the reservoir.

Figure 3: Map view. Example of microseismic events located using the semblance weighted stacked method. The beach balls represent the focal mechanisms inverted for each event. Please note how consistent the focal mechanisms are for this given cloud of microseismic events (strike-slip mechanisms).

Inferring fluid-filled fractures presence using S-wave attenuation on microseismic events

then measured on the rotated trace which is horizontally transverse to the P-wave arrival direction. The computation is done on Sh-waves because these waves do not interfere with the coda of the P wave and therefore allow for a more reliable amplitude measurement.

One S-wave attenuation factor is thus obtained for each level of the borehole array and for each microseismic event. These ratios are then averaged over all traces to form a single ratio for each microseismic event. For interpretation purposes we then represent the microseismic events sized by their respective S-wave attenuation factor, as shown on Figure 5.

Results and Interpretation As previously mentioned only stages 1 and 5 have been recorded by both the borehole and surface arrays. However all the stages have been recorded by the surface array. It allowed getting a good understanding of the fracture mechanisms that took place during the operations. Among them it was clear that the hydraulic fractures interacted strongly with natural fractures. This interpretation is based on the focal mechanisms inverted and on the direction of the microseismic event clouds (azimuth N340 and N20 on the right side of Figure 5). Indeed many of the largest strike-slip events are localized on apparent fault zones, which deviate from the trend of the hydraulic fractures and from the local maximum horizontal stress direction. The large magnitude and localization of these events strongly suggest that they are associated with reactivation of pre-existing shear corridors. The interpretation of these events can be correlated with interpreted faults from seismic reflection data. The microseismic events related to those fault reactivations represent the majority of the microseismic energy released but it does not mean that fluid has filled those fractures. The Z4 zone of left side of Figure 5 is the reference as microseismic events located in this particular area will generate S wave that will propagate up to the borehole array without being attenuated. Therefore the S wave attenuation factor is low. The microseismic events located in the Z1 zone already show a higher S-wave attenuation factor than the one from Z4. The S-wave emitted by the microseismic events from Z1 had to propagate through the fractured zone of stage 1 before reaching the borehole array, it is then logical for those waves to be more attenuated than the ones from Z4. The S-wave emitted by the microseismic events from Z2 will propagate through the zone comprised between Z2 and Z1 then through the same fractured zone as the events from Z1. The S-wave coming from the events of Z2 should therefore be more attenuated than the ones from Z1 which is clearly the case here. Moreover the S wave attenuation of the events decreases with the distance of the events from the wellbore both for Z1 and Z2. All this is in line with the assumption that the S wave attenuation shown here is due mainly to the propagation of the S-waves through fluid-filled fractures. The Figure 6 shows the same behavior as the one observed in map view. The shallowest microseismic events show a lower S-wave attenuation factor because the waves they emitted traveled a shorter distance in a fluid-filled fracture zone.

Figure 4: Section view. UX (top), UY (middle) and UZ (bottom) propagation of a double-couple with N-S / E-W fault planes. The snapshots have been taken on E-W slices at the source level after 0.1s of propagation

Inferring fluid-filled fractures presence using S-wave attenuation on microseismic events

By admitting that S-waves are more attenuated when they propagate through fluid-filled fractures one can conclude that the N340 reactivated faults are not wet. These faults do not actually attenuate the S-wave of the microseismic events from Zone 3.

Conclusion, discussion and way forward This example on real data shows that S-waves generated by microseismic events get attenuated when they propagate through fluid-filled fractures. By monitoring the hydraulic fracture operations using both a surface and a borehole

array it is possible to compute a S-wave attenuation factor per microseismic event that will highlight the fluid-filled fractures. The surface array is needed to be able to invert for the focal mechanism and therefore be able to account for the radiation pattern. This is seen as a promising technique to infer the fluid-filled fractures. However both a surface and a borehole array are needed to map the S-wave attenuation factor which definitely increases the cost of the microseismic acquisition. Also this technique is a proof of concept for now and does not allow mapping directly the propped fractures yet. The next step will be to invert the S-wave attenuation factor to accurately map those zones. It will require taking into account the ray path from every event to the well bore and further modeling also to quantify how fluid-filled fractures attenuate the S-wave. Acknowledgements The authors thank Total and the partners for the permission to publish this paper.

Figure 5: Left: Map view. Microseismic events detected by the borehole geophone for which S-wave attenuation factors have been computed. The microseismic events are sized by their respective S-wave attenuation factor. Right: Map view. Microseismic events located by the surface array and represented by summed event amplitudes. Shaped summed amplitudes are produced by summing images that are elongated along strike. For strike-slip events the strike is chosen as the nodal plane that is along apparent structure.

Figure 6: Section view E-W of the microseismic events detected by the borehole array sized by S-wave attenuation factor.

References Fehler, M. ,1982,. Interaction of seismic waves with a viscous liquid layer: Bulletin of the Seismological Society of America, 72(1):55–72. Graves, R. W., 1996, Simulating seismic wave propagation in 3D elastic media using staggered-grid finite difference: Bulletin of the SSA N4, pp.1091-1106. Kennett, B. L. N. (2001), The seismic wavefield: Cambridge University Press. Oelke, A., Krüger, O., Shapiro, S., and Abakumov, I. ,2012,. Modeling reflection coefficients at a thin fluid layer representing a hydraulic fracture: SEG Technical Program Expanded Abstracts 2012: pp.1-5. Toksöz, M., D. Johnston, and A. Timur, 1979, Attenuation of seismic waves in dry and saturated rocks: I: Laboratory mea-surements: Geophysics, 44, no. 4, 681–690. Kao, H and Shan, S.J., 2004, The Source-Scanning Algorithm: mapping the distribution of seismic sources in time and space: Geophys. J. Int. (2004) 157, 589–594.

S-wave attenuation on microseismic events

Inferring the presence of

G. Bergery, M. Grausem - Total T. Shuck, D. Diller - NanoSeis

fluid-filled fractures using

Mapping

Context • Unconventional asset development:

– Optimize well placement – Optimize fracture design for each well

• Fracture design: – Create or reactivate fractures – Connect them to the well – Embed them with proppant

Well placement is mainly driven by the fracturation effectiveness

What is the fractured volume that contributes to production?

Frac’ed volume contributing to production?

3

Ulrich Zimmer, 2011 Different names: SRV, ESV, SRA, CSV, CFA Principle: Define a volume from microseismic event locations and properties

Can you map the proppant?

4

• Microseismic monitoring will map new or pre-exisiting fractures that are destabilized and slip

• Microseismic cannot distinguish between: – wet fractures: reached by frac fluid and proppant – and dry fractures: caused by local stress and pressure changes

S-waves are strongly attenuated by fluids

Microseismic experiment Surface network

Frac well

Observation well

Borehole sensors

Fractures from previous stages

Fractures

Microseismic event

Microseismic event

Radiated energy towards surface

P and S waves radiated by the microseismic event and recorded by the surface network do not cross the fracture

Radiated energy towards borehole sensors

P and S waves radiated by the microseismic event and recorded by the borehole sensors cross the fracture

Radiated energy towards borehole sensors

P and S waves radiated by the microseismic event and recorded by the borehole sensors cross the fracture But not all of them

A microseismic event will generate: • A P-wave that will not be attenuated by the fluid •An S-wave that will be attenuated by the fluid

Observation on a single event

Individual microseismic event recorded by the borehole array 24 3-component geophones

P / Sh amplitude ratio

S waves are more attenuated in the reservoir P waves as well (geometrical spreading?)

P / Sh amplitude ratio

S wave attenuation workflow • For each microseismic event:

– Location and focal mechanism inversion from surface network – Radiation pattern for both P and S waves computed in 3D for

this particular mechanism – Theoretical P / Sh amplitude ratio computed for each sensor of

the borehole – Comparison between theoretical P / Sh and observed one

The “S-wave Attenuation Factor”:

observed P/Sh ratio

expected P/Sh ratio

Ux

Uy

Uz

S-wave attenuation factor

13

Microseismic event locations and associated focal mechanism – summed amplitudes

S-wave attenuations on events recorded by the borehole sensors

Sh max

S-wave attenuation tomography Monte Carlo approach: •Attenuation model discretized in voxels. •Initial model: all voxels have equal attenuation coefficients. Thousands of iterations: •Random perturbation of the attenuation coefficient •Comparison computed attenuation with observed attenuation for all events •Keep the attenuation model if there is an improvement

S-wave attenuation tomography

15 2D tomography 2D ray density

2D tomography 2D ray density

S-wave attenuation tomography

3D

View from above Lateral view

Cold colors: low attenuation Hot colors: strong attenuation

Conclusion on S-Wave Attenuation Tomography

17

• SWAT is a proxy to map the wet fractures • It needs to account for the radiation pattern • Limitations:

– It requires surface and borehole acquisition – Longer aperture for the borehole is preferable – several boreholes? – You cannot map all the wet fractures, only the ones that are crossed by S

waves – It is not yet calibrated

• On-going improvements: – Amplitude decay in 3D model – S wave attenuation for each couple borehole sensor / microseismic event – Statics computation => Dynamic computation

• Question: How to take into account the S wave attenuation for moment tensor inversion from boreholes?

That’s all folks!