Halliburton Energy Services, Inc.

John Philip Granville

Chung Lung Chang

Ruijia Wang

Batakrishna Mandal

Etienne M Samson

Mark Elliott Willis

Gary Wayne Kainer

Yinghui Lu

Yibing Zheng

Kristoffer Thomas Walker

Baichun Sun

Tatiana Gilstrap

Terry Bickley

Atchyuta Ramayya Venna

David Alan Welsh

Apparatus, methods, and systems for determining acoustic velocity behind casing or tubing in a subterranean wellbore. A method may include obtaining a plurality of waveform data sets corresponding to a plurality of propagation path regimes and obtaining a total wavefield across the receiver array. The method may also include determining a Green's function representing each of the plurality of propagation path regimes and determining a noise wavefield by convolving the Green's functions and a known transmitted pressure signal corresponding to the plurality of waveform data sets. The method may also include generating a reduced-noise wavefield by subtracting the noise wavefield from the total wavefield and estimating the acoustic velocity of a formation behind the casing or tubing from the reduce-noise wavefield.

Method and apparatus for geophysical formation evaluation measurements behind casing

Systems and methods are provided for determining a formation body wave slowness from an acoustic wave. Waveform data is determined by logging tool measuring the acoustic wave. Wave features are determined from the waveform data and a model is applied to the wave features to determine data-driven scale factors The data-driven scale factors can be used to determine a body wave slowness within a surrounding borehole environment and the body wave slowness can be used to determine formation characteristics of the borehole environment.

Methods and systems for processing borehole dispersive waves with a physics-based machine learning analysis

Fluid characteristics of a well fluid can be monitored. For example, a computing device can receive sensor signals from an acoustic sensor positioned on a well tool. The sensor signals can indicate characteristics of acoustic emissions generated by a well fluid impacting the well tool. The computing device can determine an acoustic signature for the well fluid using the characteristics of the acoustic emissions. The computing device can determine a difference between the acoustic signature a baseline acoustic-signature for the well fluid. The computing device can determine one or more fluid characteristics of the well fluid using the difference between the acoustic signature and the baseline acoustic-signature. The computing device can transmit a notification indicating the one or more fluid characteristics.

Monitoring fluid characteristics downhole

An apparatus includes a central body having a longitudinal axis and a first extended member attached to the central body, wherein the first extended member extends away from the longitudinal axis. The apparatus also includes a first mechanically sensitive sensor mechanically coupled to the first extended member.

Flow characterization tool

A method and system for determining a deployment profile of a fiber optic cable. The method may comprise disposing a fiber optic cable into a tubular structure, opening and closing a valve to form a pressure pulse, wherein the pressure pulse travels within the tubular structure, sensing the pressure pulse within the tubular structure with the fiber optic cable and at least one pressure transducer, recording data from the pressure pulse with the fiber optic cable and the at least one pressure transducer, and sending the data to an information handling system from the fiber optic cable. A well measurement system may comprise a tubular structure, a fiber optic cable, a valve, and an information handling system, wherein the information handling system is configured to open and close the valve to form a pressure pulse and record data from the pressure pulse.

Depth and distance profiling with fiber optic cables and fluid hammer

Disclosed are systems and methods for selecting modes and frequencies of interest in a slowness-frequency map of sonic logging information. These include measuring, by a sonic logging tool, sonic data within a borehole, determining a frequency range for a selected mode of the sonic data, determining a slowness range for the selected mode of the sonic data, applying the frequency range and the slowness range to the sonic data to select a subset of data from the sonic data, processing the selected subset of data.

Automatic slowness-frequency range determination for advanced borehole sonic data processing

A method and system for receiving calibration information including a first power spectral density (PSD) value and a first sand concentration value at a particular frequency. Data is collected in a liquid flow at the particular frequency at a first depth in a downhole environment. A second power spectral density (PSD) value is then determined for the data in the liquid flow at the particular frequency. The second PSD value being compared with the first PSD value. Sand can also be determined to be present in the liquid flow when the second PSD value is greater than the first PSD value by a predefined threshold. A second sand concentration value of the sand present in the liquid flow being quantified based on the first sand concentration value.

Systems and methods for sand flow detection and quantification

Techniques for estimating and visually presenting formation slowness are disclosed herein. The techniques include receiving acoustic signal responses from adjacent formations at a plurality of depths in a borehole environment, mapping a distribution of the acoustic signal responses at each depth according to slowness and a frequency values, determining at least one confidence interval to define a coherence threshold for the distribution of the acoustic signal responses at each depth, generating a variable density log for each depth based on the distribution of acoustic signals responses that satisfy the confidence interval for one or more frequency ranges, determining a formation slowness value for each depth based on the variable density log for the each depth, and presenting a semblance map that includes a slowness axis, a depth axis, the formation slowness value for each depth, and at least a portion of the distribution of acoustic signal responses at each depth.

Identifying and visually presenting formation slowness based on low-frequency dispersion asymptotes

In accordance with embodiments of the present disclosure, systems and methods for taking acoustic/ultrasonic wave measurements of a wellbore using a downhole tool equipped with microelectromechanical (MEM) transducers are provided. The MEM transducers may include a plurality of MEM transmitters (e.g., MEM speakers) and a plurality of separate MEM receivers (e.g., MEM microphones). These MEM transducers may be disposed in arrays proximate an outer surface of the downhole tool to collect acoustic/ultrasonic wave measurements of the full circumference of a wellbore. Due to their small size, large numbers of MEM transducers may be distributed radially around the downhole tool. Such an arrangement of sensors may enable the downhole tool to perform measurements of the entire wellbore without the downhole tool needing to be rotated, leading to an increased signal-to-noise ratio of the measurements.

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Humble, TX, United States of America

John Philip Granville