Establishing a Geomechanical Workflow for Time-lapse Modelling of an HPHT Field

Dybvik, Ole Petter; Gemmer, Lykke; Theune, Ulrich; Østmo, S.

doi:10.3997/2214-4609.201400229

Cited by 4 publications

(2 citation statements)

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“…However, the interpretation of the shifts between vintages of time-lapse seismic data in terms of fluid, mechanical and geometric changes is challenging (Røste et al, 2006) especially with respect to the time-lapse effect in the overburden. Indeed, overburden time shifts have been observed in a wide range of time-lapse studies: chalk fields, e.g., Valhall (Barkved and Kristiansen, 2005;; highpressure, high-temperature fields, e.g., Elgin, Franklin and Kristin (De Gennaro et al, 2008;Dybvik et al, 2009); sandstone reservoirs at normal pressure and temperature, e.g., Snorre field (Røste et al, 2015); and turbidite sands fields, e.g., the Genesis and Dalia fields (Rickett et al, 2007;Rodriguez-Herrera et al, 2015). Except in rare cases in which subsidence is significant (e.g., Ekofisk field -Guilbot and Smith, 2002), shifts in the time-lapse vintages are predominantly due to the accumulation of small velocity changes.…”

Section: Introductionmentioning

confidence: 99%

Determination of a stress-dependent rock-physics model using anisotropic time-lapse tomographic inversion

et al. 2020

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In the petroleum industry, time-lapse (4D) studies are commonly used for reservoir monitoring, but they are also useful to perform risk assessment for potential overburden deformations (e.g., well shearing, cap-rock integrity). Although complex anisotropic velocity changes are predicted in the overburden by geomechanical studies, conventional time-lapse inversion workflows only deal with vertical velocity changes. To retrieve the geomechanically induced anisotropy, we have adopted a reflection traveltime tomography method coupled with a time-shift estimation algorithm of prestack data of the baseline and monitor simultaneously. For the 2D approach, we parameterize the anisotropy using five coefficients, enough to cover any type of anisotropy. Before applying the workflow to a real data set, we first study a synthetic data set based on the real data set and include velocity variations between baseline and monitor found in the literature (vertical P-wave velocity decrease in the cap rock and isotropic P-wave velocity change in the reservoir). On the synthetics, we measure the angular ray coverage necessary to retrieve the target anisotropy and observe that the retrieved anisotropies depend on the offset range. Based on a synthetic experiment, we believe that the acquisition of the real case study is suitable for performing tomographic inversion. The anisotropic velocity changes obtained on three inlines separated by 375 m are consistent and show a strong positive anomaly in the cap rock along the 45° direction (the [Formula: see text] parameter in Thomsen notation), whereas the vertical velocity change is surprisingly almost negligible. We adopt a rock-physics explanation compatible with these observations and geologic considerations: a reactivation of water-filled subvertical cracks.

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Section: Introductionmentioning

confidence: 99%

Determination of a stress-dependent rock-physics model using anisotropic time-lapse tomographic inversion

et al. 2020

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“…Guilbot and Smith (2002), Landrø and Stammeijer (2004) and Hatchell and Bourne (2005) discussed various methods to estimate velocity and thickness changes for compacting reservoirs. Hansen, Aronsen and Østmo (2009) and Dybvik et al (2009) are other examples of time‐shift analysis used for detecting geomechanical changes in overburden due to reservoir pressure depletion. In this work we study if variations in sea‐bed diffraction hyperbolas can be used to estimate water velocity and thickness changes.…”

Section: Introductionmentioning

confidence: 99%

Estimation of changes in water column velocities and thicknesses from time lapse seismic data

Osdal

Landrø²

2010

Geophysical Prospecting

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A B S T R A C TSea-bed diffractions are frequently observed for several of the fields in the Norwegian Sea and the Barents Sea. This is a challenge in time lapse seismic analysis, since diffracted multiples are difficult to remove by processing and therefore is a major source of poor time lapse data quality. In this work we test if the diffractions can be used for enhanced 4D interpretation. By analysing the time-shift of the sea-bed diffraction hyperbola between the base and monitor it is tested if changes in water velocity and tides can be estimated.Two models using time lapse diffraction analysis are tested: the first one simply adds time-shifts for the two branches of the diffraction hyperbola and this average time-shift is then used to estimate the water velocity change. The other method uses an inversion method based on the diffraction equation for a point diffractor to estimate the velocity change. In-line common-midpoint shifts are estimated by subtracting the time-shifts of both hyperbola branches followed by direct inversion. The diffraction based time-shifts are compared to time-shifts estimated by standard cross-correlation of the sea-bed reflection. The averaging method gives slightly higher uncertainties, while the inversion using an exact traveltime equation gives similar uncertainties compared to the sea-bed reflection method.

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Overburden 4D time shifts induced by reservoir compaction at Snorre field

2015

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Interpreting and understanding overburden seismic changes are important to avoid health, safety, and environmental (HSE) accidents and well-drilling problems. Furthermore, overburden time shifts might indicate areas with reservoir compaction and depletion. In the Snorre sandstone field, 4D seismic time shifts of as much as 3 ms are observed in the overburden. The cumulative overburden time shifts captured at top reservoir correlate well with pressure-depletion areas in the reservoir, indicating that the time shifts might be related to changes in stress and strain because of reservoir compaction. For further investigation, a 2D geomechanical model is built in the area with the most prominent overburden time shifts. Based on the stiffness of the reservoir and surrounding rocks and simulated reservoir pore-pressure changes, the geomechanical model predicts a maximum downward displacement at the top reservoir of 0.4 m and maximum seabed subsidence of 0.25 m. By defining an appropriate strain-sensitivity parameter, the results from the geomechanical model are forward-modeled into velocity changes. For comparison, velocity changes are estimated from the time shifts. A good qualitative match is obtained between the geomechanical model and the observed time shifts, indicating that the time shifts are caused by geomechanical effects related to production. Other explanations of the observed overburden time shifts, such as fluid leakage, out-of-zone-injection, or seismic acquisition or processing problems, are found to be less realistic causes of the observed time shifts.

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Establishing a Geomechanical Workflow for Time-lapse Modelling of an HPHT Field

Cited by 4 publications

References 0 publications

Determination of a stress-dependent rock-physics model using anisotropic time-lapse tomographic inversion

Determination of a stress-dependent rock-physics model using anisotropic time-lapse tomographic inversion

Estimation of changes in water column velocities and thicknesses from time lapse seismic data

Overburden 4D time shifts induced by reservoir compaction at Snorre field

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