Passive seismic analysis for reservoir monitoring September 24, 2010 Capo Caccia, Sardinia, Italy D. Gei, L. Eisner, P. Suhadolc

Outline Hydraulic stimulation of reservoirs Passive seismic monitoring Surface star array data: some examples Focal mechanism inversion of microseismic events P-wave traveltime inversion for VTI media

Hydraulic stimulation of reservoirs It is injection of fluids under high pressure in order to overcome minimum stress and open a hydraulic fractures, either by opening existing fractures or producing new ones. It increases the permeability of the rock from microdarcy to millidarcy range. The fluid injected into the formation is typically composed of brine (95%), additives, proppant (e.g. resin-coated sand, ceramic materials). The stimulated volume can extend several hundred meters around the well. The dimensions, extent, and geometry of the induced fractures are controlled by pump rate, pressure, and viscosity of the fracturing fluid. Reservoir hydraulic stimulations usually induce (significant) microseismic activity. Hydraulic stimulation is a technique to induce fractures in hydrocarbon and geothermal reservoirs.

Perforation shots (picture after API Guidance Document HF1, Hydraulic Fracturing Operations – Well Construction and Integrity Guidelines, First Edition, October 2009) Perforation shots Low permeability, hydrocarbon-rich formation Stage 2 Stage 1 Perforation shots serve to connect wellbore and formation through opening in casing ToeHeel

Fluid injection Hydraulic stimulation (picture after API Guidance Document HF1, Hydraulic Fracturing Operations – Well Construction and Integrity Guidelines, Fisrt Edition, October 2009) Microseismic events Stage 2 Stage 1

Anisotropy analysis (P and S waves) Passive seismic monitoring of reservoirs consists in “listening” to the subsoil during oilfield operations (e.g. production, hydraulic stimulation, CO 2 injection). Passive seismic for reservoir monitoring Location of events and clustering Focal mechanisms Map fracture system Cap rock integrity Fault mapping (reservoir compartmentalization) Fracture characterization Fracture orientation Fracture density and aspect ratio

Microseismic signals can be recorded by downhole sensors or surface star arrays of receivers. Vertical array of 3C geophones (8-12 receivers) in a monitoring well. Hundreds of receivers disposed in a star shaped array (from Warpinski, 2009) Monitoring wellTreatment well ~300 m Depth (kft) > source depth Easting (kft) Northing (kft) Receivers Treatment wells Microseisms

(picture from Treatment well (deviated)  Hmax

Data example Microseismic event 1 Perforation shot

Microseismic event 1 Lines Processing performed Bandpass freq filter (2,7,60,70) Hz Agc for visualization

Lines Processing performed Bandpass freq filter (2,7,60,70) Hz Agc for visualization Polarity flip Microseismic event 1

Red line: frequency peak of the spectrum for each seismic trace Data from line 10 (1C) Raw data Line 10 Polarity flip  source location Time window width: s Microseismic event 1: frequency analysis of the seismic signals

Perforation shot

Direct arrivals from the perforation shot Direct waves from the well head Surface waves from the well head Perforation shot ReceiversWell head Perforation shot

Focal mechanisms

Focal mechanisms: event 1 Focal mechanism: oblique dip-slip fault OK

Focal mechanism: strike slip fault Focal mechanisms: event 6

Vertical Transverse Isotropy (polar anisotropy) Anisotropic material: properties (e.g. seismic velocities) depend on direction. Vertical transverse isotropy can be related to fine layering in sedimentary basins or to shales. Thomsen parameters (weak anisotropy) 5 independent elasticity constants (c 11, c 33, c 44, c 66, c 13 )

picked arrival time P-wave traveltime inversion for homogeneous VTI media one-way vertical traveltime normal moveout velocity Anellipticity (Alkhalifah and Tsvankin, 1995) P-wave velocity // symmetry axis Experimental traveltimes Computed traveltimes (t 0 =  =0.1  =-0.1 ) Computed traveltimes (t 0 =0.007  =0.2  =0.3 ) Computed traveltimes (t 0 =0  =0.1  =0.22 ) * origin time offset (horizontal projection of source-receiver distance) , , V P0

Perforation shot P-wave traveltime inversion of perforation shot data P-wave velocity profile

P-wave traveltime inversion of perforation shot data Traveltimes from experimental data (layered anisotropic ? medium) , ,  Traveltimes from synthetic data (ray tracing - isotropic layered medium) , ,  Effective velocity for traveltime inversion

P-wave traveltime inversion from experimental data Experimental data Inversion results: vti t 0 = s  = ,  RMS  4.0 ms Picked arrival times Time (s) Time residuals Experimental and theoretical traveltimes - Line 1

P-wave traveltime inversion from synthetic data Picked arrival times Time (s) Time residuals Synthetic and theoretical traveltimes - Line 1 Synthetic data Inversion results: VTI t 0 = s  = ,  RMS  1.1 ms

P-wave traveltime inversion from synthetic data Experimental data Inversion results: VTI t 0 = s  = ,  RMS  4.0 ms Picked arrival times Time (s) Time residuals Synthetic and theoretical traveltimes - Line 1 Synthetic data Inversion results: VTI t 0 = s  = ,  RMS  1.1 ms

Conclusions This dataset is characterized by non-unique focal mechanism The reservoir and/or the overburden are affected by polar anisotropy

Bibliography Alkhalifah, T., and I. Tsvankin, 1995, Velocity analysis for transversely isotropic media: Geophysics, 60, API Guidance Document HF1, Hydraulic Fracturing Operations – Well Construction and Integrity Guidelines, First Edition, October 2009 ( library/documents/general/APi%20Hydraulic%20Fracturing%20Guidance%20Document.pdf) Fischer, T., Hainzl, S., Eisner, L., Shapiro, S.A. and Le Calvez, J., 2008a, Microseismic signatures of hydraulic fracture growth in sediment formations: observations and modeling. Jour. Geoph. Res., 113, B02307, doi: /2007JB Grechka, V., 2009, Applications of seismic anisotropy in the oil and gas industry, EAGE Publications bv. Jupe, A.J., Jones, R.H., Wilson, S.A., and Cowles, J.F., 2003, Microseismic monitoring of geomechanical reservoir processes and fracture-dominated fluid flow, Fracture and In-Situ Stress Characterization of Hydrocarbon Reservoirs, Geological Society, London, Special Publications.2003, Ameed, M.S. (Ed); 209: Maver, K.G., Boivineau, A.S., Rinck, U., Barzaghi, L., and Ferulano, F., Real time and continuous reservoir monitoring using microseismicity recorded in a live well, First Break, 27, Thomsen, L., 1986, Weak elastic anisotropy, Geophysics, 51, 1954–1966. Warpinski, N., 2009, Microseismic Monitoring: inside and out, JPT, November 2009,

We are grateful to Microseismic Inc. for supporting and providing us with the dataset. We thank Vladimir Grechka for providing us with the P-wave traveltime inversion code. Acknowledgments