Abstract: A downhole measurement tool includes at least one regular receiver and at least one reference receiver externally deployed on a tool body. The reference receiver is configured to be acoustically isolated from the borehole, for example, via an isolation structure including a high-impedance cap and a low-impedance gap. The reference receiver may be deployed in a linear array with the regular receiver(s) and may be substantially identical to the regular receiver(s) such that it has substantially the same sensitivity to tool mode signals and internal drilling noise as do the regular receivers. Received waveforms may be processed so as to remove tool mode arrivals and/or drilling noise.

Abstract: A method for removing cyclic noise from a borehole image includes transforming the image into the frequency domain using a two-dimensional (2-D) transform (e.g., using a discrete cosine transform). The cyclic noise components (peaks) are removed from the transformed image which is then inverse transformed back into the spatial domain using an inverse 2-D transform to obtain a corrected image. An automated method enables the cyclic peaks to be identified and removed from the borehole image via downhole processing.

Abstract: A method for removing cyclic noise from a borehole image includes transforming the image into the frequency domain using a two-dimensional (2-D) transform (e.g., using a discrete cosine transform). The cyclic noise components (peaks) are removed from the transformed image which is then inverse transformed back into the spatial domain using an inverse 2-D transform to obtain a corrected image. An automated method enables the cyclic peaks to be identified and removed from the borehole image via downhole processing.

Abstract: A method for removing cyclic noise from a borehole image includes transforming the image into the frequency domain using a two-dimensional (2-D) Fourier Transform, removing cyclic noise components from the transformed image, and inverse transforming the image back into the spatial domain using an inverse 2-D Fourier Transform. The cyclic noise component may also be isolated by subtracting the corrected image from the original image or by removing all non-cyclic noise components from the transformed image prior to inverse transforming. Removal of the cyclic noise from a borehole image tends to enable the identification of borehole features and provide for improved accuracy in formation parameter evaluation. Evaluation of the cyclic noise component may also enable the source of the noise to be identified and mitigated.

Abstract: A method for making acoustic logging measurements includes grouping received acoustic waveforms into one of a plurality of groups, each group being representative of a measured borehole condition (e.g., a range of measured standoff values and/or a range of measured azimuth angles). The waveforms stored in at least one of the groups are stacked so as to obtain an averaged waveform. The averaged waveform may be further processed, for example, via a semblance algorithm to obtain at least one acoustic wave slowness.

Abstract: A method for determining an acoustic anisotropy of a subterranean formation includes measuring acoustic wave slownesses at three or more toolface angles while rotating a logging while drilling tool in a borehole. Compressional, shear, and/or guided wave slownesses may be measured. The measured slownesses are fit to a mathematical model to obtain maximum and minimum slownesses. The maximum and minimum slownesses are processed to determine the acoustic anisotropy of the formation.

Abstract: A method for making acoustic logging measurements includes grouping received acoustic waveforms into one of a plurality of groups, each group being representative of a measured borehole condition (e.g., a range of measured standoff values and/or a range of measured azimuth angles). The waveforms stored in at least one of the groups are stacked so as to obtain an averaged waveform. The averaged waveform may be further processed, for example, via a semblance algorithm to obtain at least one acoustic wave slowness.

Abstract: A method for determining an acoustic anisotropy of a subterranean formation includes measuring acoustic wave slownesses at three or more toolface angles while rotating a logging while drilling tool in a borehole. Compressional, shear, and/or guided wave slownesses may be measured. The measured slownesses are fit to a mathematical model to obtain maximum and minimum slownesses. The maximum and minimum slownesses are processed to determine the acoustic anisotropy of the formation.

Abstract: A downhole measurement tool includes at least one regular receiver and at least one reference receiver externally deployed on a tool body. The reference receiver is configured to be acoustically isolated from the borehole, for example, via an isolation structure including a high-impedance cap and a low-impedance gap. The reference receiver may be deployed in a linear array with the regular receiver(s) and may be substantially identical to the regular receiver(s) such that it has substantially the same sensitivity to tool mode signals and internal drilling noise as do the regular receivers. Received waveforms may be processed so as to remove tool mode arrivals and/or drilling noise.

Abstract: A method for removing cyclic noise from a borehole image includes transforming the image into the frequency domain using a two-dimensional (2-D) transform (e.g., using a discrete cosine transform). The cyclic noise components (peaks) are removed from the transformed image which is then inverse transformed back into the spatial domain using an inverse 2-D transform to obtain a corrected image. An automated method enables the cyclic peaks to be identified and removed from the borehole image via downhole processing.

Abstract: A method for removing cyclic noise from a borehole image includes transforming the image into the frequency domain using a two-dimensional (2-D) Fourier Transform, removing cyclic noise components from the transformed image, and inverse transforming the image back into the spatial domain using an inverse 2-D Fourier Transform. The cyclic noise component may also be isolated by subtracting the corrected image from the original image or by removing all non-cyclic noise components from the transformed image prior to inverse transforming. Removal of the cyclic noise from a borehole image tends to enable the identification of borehole features and provide for improved accuracy in formation parameter evaluation. Evaluation of the cyclic noise component may also enable the source of the noise to be identified and mitigated.