RockLab Details. Rock Physics Testing

Transcription

1 Rock Physics Testing Seismic velocity and electrical resistivity of rock samples are varying, as the stress/strain (and its orientation), temperature and fluid of the formation of interest are changing and moving. In addition to the pressure wave velocity (Vp), the shear wave velocity (Vs) is also an important parameter to know, since it is related directly to the rock effective stress e.g. for caprock integrity in the context of overburden management. Furthermore, full waveform analysis of lab data can tell us more about wave interactions with matrix and fractures in a rock sample (including attenuation and amplitude). To utilize all these possibilities, accurate and efficient recording of seismic and electrical signal, followed by high-confidence interpretation, is very crucial and can provide us with quantitative rock physics models, which can be used for reservoir monitoring purpose. All NGI triaxial cells are equipped with active seismic and electrical signals acquisition system, which can be programmed such that signals are logged automatically and periodically during test (loading/unloading, drainage/imbibition, See Figure 1a). Typically, triaxial tests are executed for days and the amount of the acquired seismic and electrical data are huge. Therefore, NGI has developed a streamlined acquisition and interpretation workflow, which can handle the huge amount of data very efficiently, at the end producing velocity and resistivity values in digital files. The measurement can be made not only along the axial direction of the rock sample but also along the radial direction, which make it possible to estimate the anisotropy of the rock sample only with a single test (i.e. no need for one test for vertical-to-bedding and the other for parallelto-bedding). Furthermore, a special cell is developed, where we have three radial measurements available at three different locations along the axis (Figure 1b). This can 1) produce azimuthal anisotropy of rock sample and 2) monitor fluid movement in a rock sample for measurement of both seismic velocity and electrical resistivity. Figure 1. (a) Test data example for multiple cycles of loading/unloading and Brine-CO2 drainage/imbibition; (b) multi-direction and point measurement system cell (Soldal et al, 2015). [See Figure 6 for the interpretation in terms of P-velocity, Amplitude w.r.t. stress change] Capabilities

2 All NGI Triaxial cell are equipped with rock physics setup (axial and radial; Vp, Vs and resistivity) NGI set-up are specially designed for the combination of geomechanical and geophysical measurements. E.g. large-amount geophysical datasets can be acquired in a cost effective way during geomechanical testing. High flexibility towards choice of stress and temperature path or flooding conditions (i.e. representative for a dynamically changing reservoir or compacting sediments). Streamlined measurements, processing, analysis and reporting of large number of P- and S -wave velocities and resistivity data High focus for high quality S- wave measurements Applications Stress sensitivity of velocity and resistivity including anisotropy. Dense sampling during any type of loading to investigate stress dependency Velocity and resistivity during fluid substitution, including fracture flow Correlation between rock physical and geomechanical parameters Rock physics relations Shear wave geomechanics (including static-dynamic relationship) New developments Software updated for quantitative analysis: full waveform analysis of lab data 1) to quantify attenuation, 2) reduce uncertainty in S-wave estimate via signal processing and/or finite element modelling. Workflow and algorithm for fluid saturation estimation: velocity-resistivitybased saturation estimation. References Alemu, B.L., Aker, E., Soldal, M., Johnsen, Ø., Aagaard, P., Effect of sub-core scale heterogeneities on acoustic and electrical properties of a reservoir rock: a CO2 flooding experiment of brine saturated sandstone in a computed tomography scanner, Geophysical Prospecting, 61(1), Moghadam, J.N., Mondol, N.H., Hellevang, H., Øiestein, J., Aagaard, P., Seismic response of CO2 saturated Red Wildmoor Sandstone under varying temperature and pressures, 76 th EAGE Conference & Exhibition, June 16-19, Amsterdam, The Netherlands. Nooraiepour, M., Bahman, B., Park, J., Sauvin, G., Skurtveit, E., Mondol, N.H., Experimental study of brine/co2 transport through a naturally fractured tight sandstones: an integrated fluid flow and geophysical investigation, Geophysics, 83(1), JANUARY-FEBRUARY, 1-12.

3 Park, J., Tveit, S., Mannseth, T., Agersborg, R., Sauvin, G., 2018, Geophysical monitoring, FME SUCCESS Synthesis report Vol 4. Soldal, M, Park, J., Omolo, L.O., Tran, T., Sauvin, G., Johnsen, Ø., Mondol, N.H., 2015b. Geophysical monitoring of CO2 flow during sandstone flooding experiments, 3rd EAGE Workshop on Rock Physics, November 15-18, Istanbul, Turkey. Zadeh, M. K., Mondol, N.H., and Jahren, J., Velocity anisotropy of Upper Jurassic organic-rich shales, Norwegian Continental Shelf, Geophysics, 82(2). C61-C75. Examples Figure 2. Sensor orientation relative to rock sample bedding (top). P-wave velocity(left, bottom) and electrical resistivity (right, bottom) versus injected CO2 in pore volume (PV), measured simultaneously at different levels/points and directions during CO2 flooding test with Gres Des Vosges (GDV). (Soldal et al. 2015b)

4 Figure 3. a) Illustration of naturally-fractured De Geerdalen sandstone, b) fracture plane extracted from CT scanning, and changes in c) acoustic velocity and d) electrical resistivity during drainage of brine by CO2 in the fracturec (Nooraiepour et al. 2018). Figure 4. a) Schematic representation of hydrostatic cell, b) applied confining stresses, CO2 pore pressure, effective stresses, and temperatures and observed velocities at different temperature (T) and pressure (P) conditions for c) Knorringfjellet and d) Red Wildmoor sandstone core plugs (Moghadam et al. 2016).

5 Figure 5. a) Schematic diagram of the tested samples in the triaxial cell and the transducer arrangement around the samples, b) the loading paths and test progression with elapsed time for a core plug cut vertical to the bedding and c) Thomsen anisotropy parameters versus mean effective stress (Zadeh et al. 2017). Figure 6. Evolution of effective vertical stress (blue line), axial P-wave velocity (orange dot), and P-wave first arrival maximum amplitude (black dot) with time. The first cycle is CO2-saturated, the second one brine-saturated and the last phases is CO2-injection into brine-saturated sample.