Fracture imaging from sonic reflections and mode conversion

Yamamoto, Hiroaki; Mikada, Hitoshi; Watanabe, Shinichi; Haldorsen, J.

doi:10.1190/1.1820802

Cited by 18 publications

(7 citation statements)

References 3 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Hornby 1989 and others (Yamamoto 1999, 2000, Haldorsen 2006 have shown that the direct waves can be filtered out and the reflected waves enhanced to provide a near wellbore reflection image that can detect bed boundaries and fractures in the immediate vicinity of the borehole. The amplitude of the reflected signal not only depends on the attenuation of energy along its travel path and at the reflector but also on the transfer of energy at the various interfaces.…”

Section: Signal Attenuation During Bars Surveymentioning

confidence: 97%

See 1 more Smart Citation

Dipole Shear Imaging behind casing: Extending the borehole Acoustic Imaging envelope to Brown-fields

et al. 2014

Self Cite

View full text Add to dashboard Cite

The potential for imaging bed boundaries and fractures using the borehole acoustic reflection survey (BARS) technique is well documented. Traditionally, this type of imaging has been conducted with a monopole source and imaging the reflected P and the mode-converted transmission waves (Pto S and S to P). Recently the BARS methodology has been applied to shear data from a dipole source. Much of the published work is in an open-hole environment. In our case study a BARS image was acquired in a layered carbonate reservoir in a horizontal well behind casing. The objective was to acquire a base image prior to a planned hydraulic fracturing job for comparison with the post-fracturing image. Both, monopole and dipole data were used to do the imaging. Data acquired shows that the BARS technique overcame uncertainties associated with; arrival of the casing modes, cement conditions, attenuation of the reflected signal at the casing/cement/formation interfaces and provided reliable results behind casing up to a distance of 100 ft away from the well. IntroductionBARS (Borehole Acoustic Reflection Survey) or SWI (Single Well Imaging) for detecting near borehole events at sub seismic scale was first demonstrated by Hornby in 1989. The methodology adopted involves imaging P waves from a monopole source. Later Yamamoto (1999) and other demonstrated that borehole crossing features could be imaged using S to P conversion downdip and P to S conversions updip of the event. More recently Tang and others (2009) demonstrated this methodology using dipole acoustic data. Published data does not show much experience of acoustic imaging in a cased well through a porous reservoir. A porous reservoir presents a highly attenuating environment making imaging "near borehole features", especially in a cased well very challenging. Acoustic imaging can be significantly beneficial if it can be successfully done in these environments.

show abstract

Section: Signal Attenuation During Bars Surveymentioning

confidence: 97%

“…The methodology adopted involves imaging P waves from a monopole source. Later Yamamoto (1999) and other demonstrated that borehole crossing features could be imaged using S to P conversion downdip and P to S conversions updip of the event. More recently Tang and others (2009) demonstrated this methodology using dipole acoustic data.…”

mentioning

confidence: 98%

Dipole Shear Imaging behind casing: Extending the borehole Acoustic Imaging envelope to Brown-fields

et al. 2014

Self Cite

View full text Add to dashboard Cite

show abstract

“…; Yamamoto et al . ; Coates et al . ) shows that the reflected waves can be detected from heterogeneities more than 10 m away from the borehole and that these reflections can be used to image structures.…”

Section: Introductionmentioning

confidence: 98%

“…1). Previous research (Hornby 1989;Esmersoy et al 1998;Yamamoto et al 1999;Coates et al 2000) shows that the reflected waves can be detected from heterogeneities more than 10 m away from the borehole and that these reflections can be used to image structures. This imaging capability presents possibilities for this method in heterogeneous reservoir evaluation.…”

Section: Introductionmentioning

confidence: 99%

High‐resolution Radon transforms for improved dipole acoustic imaging

Yue

2016

Geophysical Prospecting

View full text Add to dashboard Cite

Imaging using dipole acoustic logging reflections has become a research topic of increasing interest in recent years. Extracting reflections from the whole waveform is both important and extremely difficult because the reflections are obscured by large‐amplitude direct waves. A method of wavefield separation based on high‐resolution Radon transforms has been applied to separate the reflected waves. First, an analysis of the common offset gathers shows that the linear Radon transform can be used to separate the direct and reflected wave fields. However, traditional linear Radon transforms cannot focus the wave event using the least squares method. An improved high‐resolution linear Radon transform is achieved using the principles of maximum entropy and Bayesian methods based on previous studies. The separation method is tested using synthetic data for hard and soft formations, a void model, and a fault model. The high‐resolution Radon transform method is used to process a field dataset and exhibits improved results compared with those of the standard method.

show abstract

“…The acoustic waves reflected by the near-borehole interfaces with non-continuous acoustic impedance are obtained through acoustic reflection logging (Hornby 1989;Ellis et al 1996;Esmersoy et al 1997Esmersoy et al , 1998Chang et al 1998;Yamamoto et al 1998;1999). Migration imaging techniques that are similar to those used in seismic exploration are then employed to visualize small-scale geologic structures from a few meters to dozens of meters away from boreholes (Yamamoto et al 2000;Tang 2004;Pistre et al 2005;Li et al 2008;Chai et al 2009;Tang et al 2007).…”

Section: Introductionmentioning

confidence: 99%

Experimental study of the azimuthal performance of 3D acoustic transmitter stations

Che

Qiao

et al. 2016

Pet. Sci.

View full text Add to dashboard Cite

Better well logging techniques for geologic investigations are urgently needed to identify and evaluate complex reservoirs. We describe a new type of 3D transmitter station with corresponding circuits and bodies. They can be used in a promising new technique of acoustic reflection well logging, that features better azimuthal detection capabilities, as well as better investigation depth. The transmitter stations consist of three-level subarrays that can radiate acoustic energy in any required azimuth of 3D space by circularly exciting various combinations at different levels. We tested the 3D acoustic transmitter stations and obtained laboratory directivity measurements with the 3D acoustic transmitter stations for the first time. The results show that the 3-dB beam width in the horizontal plane ranges from 59°to 67°as a result of phase-delayed excitation. The main beam is steered in the vertical plane at a deflection angle that ranges from 0°to 16°when the delay time of the excitation pulse between each pair of adjacent arc arrays is gradually adjusted. The 3-dB beam width is equal to 11°, whereas the deflection angle in the vertical plane is equal to 14°. Each of the four third-level subarrays in the same circumferential direction display consistent horizontal and vertical directivities, thus satisfying the requirements of azimuthal acoustic reflection logging.

show abstract

Fracture imaging from sonic reflections and mode conversion

Cited by 18 publications

References 3 publications

Dipole Shear Imaging behind casing: Extending the borehole Acoustic Imaging envelope to Brown-fields

Dipole Shear Imaging behind casing: Extending the borehole Acoustic Imaging envelope to Brown-fields

High‐resolution Radon transforms for improved dipole acoustic imaging

Experimental study of the azimuthal performance of 3D acoustic transmitter stations

Contact Info

Product

Resources

About