A tale of two surveys: experiences processing two similar but different land 3D‐3C MEMS surveys

Calvert, Alexander; Novak, John M.; Maher, John E.; Burch, D.; Bird, D. J.; Larson, Ron

doi:10.1190/1.2148324

Cited by 6 publications

(4 citation statements)

References 3 publications

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“…In addition, the Batholiths passive seismic experiment (Calkins et al, 2010) provides estimates of the crossterms of the Green tensor G c that are more robust than G zz in the presence of seismic signal not in-line with the stations. Figure 2 is a map of sources and receivers for a subset of the 80 km 2 Coronation field data set, where sources are 1 kg of dynamite buried at 18 m and the receivers are three components (Calvert et al, 2005). The horizontal receivers are oriented such that there is an East-West (radial) and a North-South (transverse) component.…”

Section: Introductionmentioning

confidence: 99%

Exploiting the crossterms of the virtual Rayleigh‐wave Green tensor for surface‐wave inversion

Wijk

Douma²,

Mikesell

et al. 2011

SEG Technical Program Expanded Abstracts 2011

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Surface-wave tomography from the correlations of ambient noise records has provided a powerful tool to investigate the Earth's subsurface with new surface-wave information. Exploration surveys can benefit from inversion of these virtual surface waves, as well. Most commonly, correlations are performed on the vertical components of the wavefields, but here we use the crossterms of multicomponent data and show virtual surface wave recordings are less sensitive to artifacts from signal not in-line with the two stations. We illustrate this with a subsection of the Coronation data set and the Batholiths temporary seismic deployment, showing estimates of the Rayleigh wave and the consequent phase-velocity dispersion curve.

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Section: Introductionmentioning

confidence: 99%

Exploiting the crossterms of the virtual Rayleigh‐wave Green tensor for surface‐wave inversion

Wijk

Douma²,

Mikesell

et al. 2011

SEG Technical Program Expanded Abstracts 2011

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“…This is particularly true for land multicomponent seismic. Recently, the use of digital MEMS (micro-electro-mechanical system) sensors has substantially improved the quality of land converted-wave data (Calvert et al, 2005). As a result, here we present an example of using MEMS-based converted-wave technology for evaluating fractured tight-sandstone gas reservoirs from the Sichuan gasfield in Southwest China.…”

Section: Introductionmentioning

confidence: 99%

PP and PS seismic response from fractured tight gas reservoirs: a case study

Jianming¹,

Zhang²,

Li³

2008

J. Geophys. Eng.

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In this paper, we present an example of using PP and PS converted-wave data recorded by digital MEMS (micro-eletro-mechanical-system) to evaluate a fractured tight gas reservoir from the Xinchang gas field in Sichuan China. For this, we analyze the variations in converted shear-wave splitting, Vp/Vs ratio and PP and PS impedance, as well as other attributes based on absorption and velocity dispersion. The reservoir formation is tight sandstone, buried at a depth of about 5000m, and the converted-wave data reveal significant shear-wave splitting over the reservoir formation. We utilize a rotation technique to extract the shear-wave polarization and time delay from the data, and a small-window correlation method to build time-delay spectra that allow the generation of a time-delay section. At the reservoir formation, the shear-wave time-delay is measured at 20ms, about 15% shear-wave anisotropy, correlating with the known gas reservoirs. Furthermore, the splitting anomalies are consistent with the characteristics of other attributes such as Vp/Vs ratio and P-and S-wave acoustic and elastic impedance. The P-wave shows consistent low impedance over the reservoir formation, whilst the S-wave impedance shows relatively high impedance. The calculated gas indicator based on absorption and velocity dispersion yields a high correlation with the gas bearing formations.This confirms the benefit of multicomponent seismic data from digital MEMS sensors.

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“…However, in recent years, the advent of digital multicomponent MEMS (micro-electro-mechanical system) sensors has led to the acquisition of several land multicomponent surveys. Roche et al (2005) reported the use of convertedwave reflectivity recorded by MEMS sensors for mapping gas production in sand reservoirs, and Mattocks et al (2005) presented examples for characterizing fractures in carbonates, Furthermore, Calvert et al (2005) compared two converted-wave surveys from MEMS sensors for lithology predication.…”

Section: Introductionmentioning

confidence: 99%

Multicomponent PP and PS Seismic Response from Volcanic Gas Reservoirs

Li¹,

Chen²,

Xiao-feng³

et al. 2006

68th EAGE Conference and Exhibition Incorporating SPE EUROPEC 2006

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Here we present an example of using PP and PS converted-waves for characterizing volcanic gas reservoirs in Daqing Oilfield in Northeast China. The volcanic targets are buried at depth raging from 2800m to 3600m, which often give rise to incoherent P-wave response. To overcome this problem, a multicomponent seismic experiment was set up to evaluate the converted-waves recorded by digital MEMS (micro-electro-mechanical system) sensors. The experiment includes six 2D lines, passing through ten boreholes drilled for the volcanic reservoirs. Several multicomponent VSPs have also been acquired for correlation purposes. Analysis the P-and S-waves from the target formation at the ten borehole locations reveals very consistent P-and S-wave amplitude anomalies. From the gas producing wells, the Pwave reflection is consistently weak and scattered, whilst the PS-wave reflection are consistently strong and continuous. In contrast from the non-producing wells, both PP-and PS-waves show continuous and strong reflections. The gas reservoirs can then be delineated from joint PP-and PS-amplitude analysis and the results agree with the drilling results in the study area. This provides conclusive evidence demonstrating the benefit of multicomponent seismic data from digital MEMS sensors.

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A tale of two surveys: experiences processing two similar but different land 3D‐3C MEMS surveys

Cited by 6 publications

References 3 publications

Exploiting the crossterms of the virtual Rayleigh‐wave Green tensor for surface‐wave inversion

Exploiting the crossterms of the virtual Rayleigh‐wave Green tensor for surface‐wave inversion

PP and PS seismic response from fractured tight gas reservoirs: a case study

Multicomponent PP and PS Seismic Response from Volcanic Gas Reservoirs

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