Halliburton Energy Services, Inc.

Ahmed Elsayed Fouda

Burkay Donderici

Luis Emilio San Martin

Junwen Dai

Baris Guner

Glenn Andrew Wilson

Ilker R Capoglu

Etienne M Samson

Christopher Michael Jones

Tasneem Mandviwala

Freeman Lee Hill, Iii

Li Pan

Reza Khalaj Amineh

Wei-Bin Ewe

Sadeed Sayed

Bin Dai

Wei Zhang

Sushovon Singha Roy

Xusong Wang

Freeman Hill

Kai Ren

Michael S Bittar

Mikko K Jaaskelainen

Krishna M Ravi

Li Gao

Mark Windsor Roberson

Xiang Wu

George David Goodman

Scott Goodwin

Brian Vandellyn Park

Junsheng Hou

Priyesh Ranjan

Daniel Viassolo

David Orlando Torres

Michael John Christie

Radompon Sungkorn

Paul Chin Ling Chang

Charles Bartee

Sriram Srinivasan

Chao-Fu Wang

Mahmoud Eid Hussein Selim

Reza K Amineh

Kenneth Liang

Wolfgang Harmut Nitsche

Alexander Stewart

Tasneem A Mandviwala

Luis Emillio San Martin

Systems and methods to generate radial resistivity profiles of formations using combined measurements from omni-directional and pad-type tools are described. Measurements from a pad-type resistivity tool are obtained along a wellbore drilled through a subsurface formation. Measurements from an omni-directional resistivity tool (e.g., a dual laterolog) are also obtained. The measurements from the pad-type and omni-directional tools are then combined and used to generate a radial resistivity profile of the formation.

Subsurface formation radial profiling using combined processing of omni-directional and pad-type tools

Methods and devices used to calibrate EM corrosion detection tools may estimate the effects of the presence of a core on measurements to enable more accurate corrosion detection in the well line. The methods may involve sending voltages to a core of a well tool disposed in the well line to obtain signals while the core is in a saturated and unsaturated state. Subsequent measurements using the core may be calibrated using a constant resulting from the division of the signals achieved at the core in the saturated and unsaturated states.

Calibrating electromagnetic corrosion detection tools via core saturation

A method and system for downhole sampling. The system may include a downhole fluid sampling tool that may include one or more probes configured to extend into a formation, and a pump configured to collect a fluid from the formation through the one or more probes. The method may further comprise a flowline configured to transport the fluid from the formation through the one or more probes and through the downhole fluid sampling tool and a fluid analysis module comprising a resonator antenna disposed on the flowline and configured to measure at least one property of the fluid. Additionally, the method may comprise measuring at least one property of the fluid with at least one resonator antennas that are disposed on or within an outer surface of the flowline.

Sensors for measuring properties of materials flowing through a flowline

A method may comprise disposing a downhole pressure sampling tool into a wellbore; calculating a prior distribution based at least in part on one or more proxy logs, moving the downhole pressure sampling tool to a first location in the wellbore, taking at least one measurement with the downhole pressure sampling tool at the first location in the wellbore, calculating a posterior distribution based at least in part on the at least one measurement and the prior distribution, identifying a second location based at least in part on the posterior distribution, and moving the downhole pressure sampling tool to the second location.

Sequential selection of locations for formation pressure test for pressure gradient analysis

Systems and methods for obtaining a calibrated permittivity dispersion measurements of a subsurface formation by measuring an impedance of the subsurface formation using a borehole imager at a first one or more frequencies; measuring a permittivity of the subsurface formation using a reference tool at a second one or more frequencies; calculating a first dispersion curve of the permittivity of the subsurface formation based at least in part on the measured impedance of the subsurface formation at the first one or more frequencies; extrapolating the permittivity of the subsurface formation to the second one or more frequencies using the calculated first dispersion curve of the permittivity of the subsurface formation; calibrating the permittivity of the subsurface formation based at least in part on the extrapolated permittivity of the subsurface formation and the measured permittivity of the subsurface formation; and generating a second dispersion curve of the permittivity of the subsurface formation based at least in part on one or more of the calibrated permittivity of the subsurface formation at the first one or more frequencies and the measured permittivity of the subsurface formation at the second one or more frequencies.

Combined processing of borehole imagers and dielectric tools

A method for correcting borehole images may include acquiring a raw data image of a formation using a downhole tool that takes one or more measurements and processing the raw data image through a machine learning model to form a corrected image. The method may further include displaying the corrected image and identifying one or more formation properties based at least in part on the corrected image.

Artifact removal from borehole images using machine learning

A method and system for correlating two or more logs. The method may include reviewing an openhole log to identify one or more depths within a wellbore for testing, disposing a fluid sampling tool into the wellbore, creating a correlation log with the fluid sampling tool, depth-matching the correlation log to the openhole log to create a relative shift table, and moving the fluid sampling tool to the one or more depths within the wellbore based at least in part on the relative shift table. The system may include a fluid sampling tool disposed in a wellbore to create a correlation log and an information handling system connected to the fluid sampling tool.

Automatic landing of formation testing tools

A method for estimating a thickness for each of a plurality of nested tubulars may include disposing an electromagnetic (EM) logging tool in a wellbore, transmitting an electromagnetic field from the transmitter into one or more tubulars to energize the one or more tubulars with the electromagnetic field thereby producing an eddy current, and measuring the electromagnetic field generated by the eddy current. Additionally, the method may include defining a prior distribution of at least one pipe thickness log based on the plurality of measurements, processing a first set of measurement depth points to estimate one or more tubulars at one or more depths in the wellbore, computing a posterior distribution of the thickness log based at least in part on the prior distribution and the one or more thicknesses, and determining a second set of measurement depth points to process based on the posterior distribution.

Maximizing information gain from pipe inspection inversion

Provided are methods and system for hydrocarbon exploration. The method may include using a downhole reconfigurable pipe inspection tool for electromagnetic logging. The method may also include using the electromagnetic pipe inspection tool for inspecting wellbore pipes. The tool may include at least two modules, a signal generator for exciting the transmitter coil; and a receiver circuitry for measuring voltage across the receiver coil, wherein at least one tool parameter is reconfigurable. The first module houses a transmitter coil, a first end, and a second opposing end, wherein the first and second ends each have a connector thereon. The second module houses a receiver coil, a first end, and a second opposing end, wherein the first and second ends of the second module each have a connector thereon.

Reconfigurable downhole pipe inspection tool

Described herein are systems and techniques for monitoring substances that are injected into an Earth formation whether that be CO2 from a carbon capture and storage (CCS) process, or water or steam injected for an enhanced oil recovery (EOR) process. Components located on an outside of a wellbore casing may be electrically isolated from components located on the inside of the wellbore casing. Data and/or power may be transferred through the wellbore casing wirelessly in order to increase the reliability of a data collection system because the need for wires to be placed on the outside surface of a wellbore casing is eliminated. The components located on the outside of the casing may receive electromagnetic (EM) or transmit EM fields as part of a system that collects data about substances that are injected into Earth formations during a CCS or EOR process.

Electromagnetic systems for reservoir monitoring

Electromagnetic logging tools are optimized using synthetic logs for the purpose of pre-job planning and accuracy/resolution estimation. One, two and three-dimensional forward modeling are used to generate accurate inspection tool responses. A radial one-dimensional (R1D) electromagnetic forward model is also used to compute an approximate log. By constructing non-linear mapping functions between the R1D model-based log and the 2D model-based log, and mapping the R1D synthetic log using the non-linear mapping functions, a quasi 2D log is computed. The quasi 2D log is processed using model-based inversion, thereby providing estimates of pipe parameters. By analyzing the estimates of pipe parameters, tool performance metrics are obtained and analyze to determine the performance of the tool. The tool parameters are adjusted in order to optimize the performance metrics.

Downhole well pipe inspection using optimized inspection tools

Aspects of the subject technology relate to systems, methods, and computer-readable media for corrosion analysis using magnetic flux leakage measurements. The present technology can magnetic flux leakage data obtained by a magnetic flux leakage tool placed in a pipe within a wellbore and convert the magnetic flux leakage data into image data. Further, the present technology can provide the image data to a machine learning model. The machine learning model is configured to identify one or more physical parameters associated with corrosion present on the pipe.

Corrosion analysis using magnetic flux leakage measurements

Aspects of the subject technology relate to systems, methods, and computer-readable media for accounting for artifacts in pipe measurements made by an electromagnetic pipe inspection tool. Measurements gathered in a plurality of pipes across different depth points are accessed. Initial estimates of an attribute associated with the plurality of pipes are made for each pipe and a total estimate of the attribute for the plurality of pipes as a whole are made across the different depth points. Corresponding initial estimates of the attribute for each pipe are filtered to remove an artifact present in at least one of the corresponding initial estimates while the total estimate is preserved. Corresponding final estimates of the attribute for each pipe are determined based on both the measurements and corresponding filtered initial estimates of the attribute for each pipe. Integrity of each pipe can be determined based on the corresponding final estimates of the attribute.

Electromagnetic pipe inspection inversion with adaptive filter for artifact removal

Methods and systems for inspecting the integrity of multiple nested tubulars are included herein. A method for inspecting the integrity of multiple nested tubulars can comprise conveying an electromagnetic pipe inspection tool inside the innermost tubular of the multiple nested tubulars; taking measurements of the multiple nested tubulars with the electromagnetic pipe inspection tool; arranging the measurements into a response image representative of the tool response to the tubular integrity properties of the multiple nested tubulars; and feeding the response image to a pre-trained deep neural network (DNN) to produce a processed image, wherein the DNN comprises at least one convolutional layer, and wherein the processed image comprises a representation of the tubular integrity property of each individual tubular of the multiple nested tubulars.

Deep learning methods for wellbore pipe inspection

Described herein are systems and techniques for monitoring for monitoring and evaluating conditions associated with a wellbore and wellbore operations that use neural operators instead of computationally intensive iterative differential equations. Such systems and techniques allow for determinations to be made as operations associated with a wellbore are performed. Instead of having to wait for computationally intensive tasks to be performed or take risks of proceeding with a wellbore operation without real-time evaluations being performed, these wellbore operations may be continued while determinations are timely made, thus improving operation of computing systems that perform evaluations and that make decisions regarding safely and efficiently performing wellbore operations such as drilling a wellbore, cementing wellbore casings in place, or injecting fluids into formations of the Earth.

Three-dimensional inversion of multi-component electromagnetic measurements using a fast proxy model

Growing community of inventors

Houston, TX, United States of America

Ahmed Elsayed Fouda