Halliburton Energy Services, Inc.

Andrew David Vos

Dale E Jamison

Kenneth Heidt Matthews, Iii

Ketan Chimanlal Bhaidasna

Daniel Joshua Stark

Brice Aaron Jackson

Daniel Reynold Robichaud

Sandeep D Kulkarni

Brian Alan Evans

Mateusz Michal Dyngosz

Richard Gary Morgan

Xiangnan Ye

Denise Nicole Benoit

Jeffrey James Miller

Bhargav Gajji

Adam Dotson

Lawrence Joseph Herskowitz

Christopher Ray Bell

Subrahmanyam Surya Venkata Sista

Marek Kozikowski

Ben John Iverson

James Robert Jones

Kenneth Heidt Matthews

Abhhilash Mamilla

Sandeep Mavinkal Kizhakke Veedu

Pyotr Rabochiy

Harmeet Singh Jammu

A variety of methods and apparatus are disclosed, including, in one embodiment, detecting a drilling event, involving flowing a drilling fluid from a wellbore being drilled through a separator, removing rock cuttings from the drilling fluid by the separator, discharging the drilling fluid from the separator without the rock cuttings removed to a mud pit, measuring a first viscosity of the drilling fluid upstream of the mud pit with a single point viscometer, measuring a second viscosity of the drilling fluid in the mud pit or downstream of the mud pit with a second viscometer that is not a single point viscometer, and detecting a drilling event associated with drilling of the wellbore by comparing the first viscosity with the second viscosity.

Drilling event detection

Analyzing solid components in the return line of a borehole can be accomplished by implementing a bar or disc in the return line. As solid components pass by, they will generate an acoustic wave on impact. In another aspect, solid components can be directed to a shaker system where the solid components will impact a soundboard. The acoustic waves can be captured, such as by a microphone or transducer. The acoustic waves can be processed and transformed into acoustic data. A machine learning system can use previously trained models to determine the solid component parameters using the acoustic data. The parameters can include the size, shape, composition, density, softness, wettability, and other parameters of the solid components. These parameters can then be used as inputs to users or other borehole systems, such as a well site controller to improve drilling operations or to identify the need to implement corrective actions.

Analyzing drill cuttings using acoustic analysis

A sensor assembly comprising one or more sensors configured to be radially positioned about a flowline, each of the respective sensors configured to obtain a respective measurement of a fluid flowing through the flowline at a respective position, wherein one or more phase properties of the fluid in the flowline are determined based on the measurements.

Sensor assembly for interpreting multiphase flow in a flowline

A sag detection apparatus comprises an oven containing a sample cell supported by a cell support structure, a thermal conductivity sensor including a sensor housing, and a roller with a first end supported by a first bearing and fixedly coupled to a first end of the cell support structure and a second end supported by a second bearing and fixedly coupled to a second end of the cell support structure. Temperature sensor wires electrically connect a temperature sensor and first fixed contact via stationary contacts configured to remain fixed during rotation of the roller and rotating contacts configured to rotate with rotation of the roller. Heat source wires electrically connect a heat source and a second fixed contact via stationary contacts configured to remain fixed during rotation of the roller and rotating contacts configured to rotate with rotation of the roller.

Sag detection using thermal conductivity

A self-cleaning temperature sensor comprises: a bellows coupled to a support structure; a pneumatic or hydraulic cylinder; a sensor configured to measure a temperature of a fluid and extending from the pneumatic or hydraulic cylinder, wherein the sensor comprises an exposure end configured to contact the fluid during sensing by the sensor; sensor wires connected with the sensor and extending to a control system; and a self-cleaning system comprising: a hood having walls extending radially outward a distance along a central axis wherein the hood defines a first volume; and a cleaning brush integrated with or adjacent the bottom of the support structure. In a retracted configuration, the exposure end of the sensor is positioned at a retracted position a distance from cleaning brush, and, in an extended configuration, the exposure end of the sensor extends a distance along the central axis away from the retracted position.

Self-cleaning thermometer for use in a mud pit

A self-cleaning thermal conductivity sensor comprises: a bellows coupled to a support structure; a pneumatic or hydraulic cylinder; a sensor configured to measure a thermal conductivity of a fluid and extending from the pneumatic or hydraulic cylinder, wherein the sensor comprises an exposure end configured to contact the fluid during sensing by the thermal conductivity sensor, a temperature sensor, and a heat source; sensor wires connected with the thermal conductivity sensor and extending to a control system; a self-cleaning system comprising: a hood having walls extending radially outward and defining a volume; and a cleaning brush integrated with or adjacent the bottom of the support structure. In a retracted configuration, the exposure end of the sensor is positioned at a retracted position a distance from cleaning brush, and, in an extended configuration, the exposure end of the sensor extends a distance along the central axis away from the retracted position.

Self-cleaning thermal conductivity sensor for use in a mud pit

Distributed artificial intelligence (AI) can be used to monitor a wellbore operation in some examples described herein. In one such example, physical equipment can be positioned at a surface of a wellsite to support a drilling operation at the wellsite. Each piece of physical equipment may include a sensor module, a processor communicatively coupled to the sensor module, and a memory. The memory can include an AI module configured to determine a condition associated with the equipment by analyzing sensor data from the sensor module using one or more machine-learning models. The memory additionally can include a warning module for causing the processor to output a warning notification based on the condition. The memory further can include a communications module for causing the processor to transmit a communication indicating the condition to a destination via a network. The communication may be different from the warning notification.

Monitoring a wellbore operation using distributed artificial intelligence

An apparatus may include: a shaker body; a shaker screen disposed within the shaker body; and one or more air nozzles disposed within the shaker body, wherein the one or more air nozzles is positioned below the shaker screen, and wherein the one or more air nozzles is operable to deliver a pressurized stream of air to at least a portion of a bottom of the shaker screen.

Systems and methods for cleaning shale shakers

A system can be used to determine properties of a wellbore treatment fluid. The system can include a rotational system defining an axis of rotation and an aging cell. The aging cell can be positioned in the rotational system to rotate about the axis of rotation. The aging cell can include a housing, a sensor shaft, and a sensor. The housing can define an interior region of the aging cell to receive a wellbore treatment fluid. The sensor shaft can be at an angle from the axis of rotation and can be coupled to the interior region to transmit electronic signals about the wellbore treatment fluid. The sensor can be positioned on the sensor shaft to detect the electronic signals while the aging cell rotates about the axis of rotation, and the electronic signals can be used to determine the properties of the wellbore treatment fluid.

Aging cell for determining properties of wellbore treatment fluid

A test apparatus can measuring particle plugging of a simulated fracture. The test apparatus can include a first test component having a first surface and a second test component having a second surface. The second test component can be positionable relative to the first test component to create a simulated fracture between the first surface and the second surface. The test apparatus can include a visualization area of at least one of the first test component or the second test component can be positioned between a fluid inlet and a fluid outlet along at least a portion of the simulated fracture.

Test apparatus for measuring particle plugging of a simulated fracture

Disclosed are methods in which measurements are obtained from a plurality of sensors secured in spaced relation to one another across at least a portion of the depth of reservoir of some form in order to identify one or more characteristics of the fluids within the reservoir. The sensors are used to monitor ambient forces exerted by fluids within the tank proximate each sensor. An example mechanism for obtaining the measurements includes a plurality of sensors, such as strain gauges, supported on a structure that supports the sensors in fixed relation to one another, and can, in some examples, support the sensors in a known relation relative to boundaries of the reservoir.

Method and apparatus for measuring characteristics of fluid in a reservoir

A mobile robot is disclosed herein. The mobile robot may include a frame, a propulsion module, a navigation module designed to navigate the mobile robot along a target pathway, and a computational module. The mobile robot may obtain a composition reading of the drilling fluid and a pressure reading of the drilling fluid. The robot may determine, using the computational module, an additive to add to a drilling fluid reservoir based on the composition reading and the pressure reading. The mobile robot may then retrieve the additive from an inventory and deposit the additive into the drilling fluid reservoir.

Mobile robots for managing drilling operations

A lubricity tester unit may comprise a housing, a shaft, wherein a first end of the shaft is disposed at a first end of the housing, wherein the shaft extends through housing along a central axis of the housing, and an encoder, wherein the encoder is disposed on an internal wall of the housing, wherein the shaft is disposed through a hole in the encoder, wherein the encoder is an optical encoder configured to measure angular position of the shaft. The lubricity tester unit may further comprise rotating rings, wherein the rotating rings are coupled to a second end of the shaft, a friction inducing surface, wherein the friction inducing surface is disposed around the rotating rings, a first sensor, wherein the first sensor is disposed through the housing, and a second sensor, wherein the second sensor is disposed through the housing.

Non-contact torque sensing

Apparatus and methods for determining a laminar-turbulent transition of a fluid are provided. For example, a measurement tool can receive a set of wellbore conditions received from a wellbore. Measurement tool parameters can be determined based on the set of wellbore conditions. The measurement tool can be set according to the measurement tool parameters such that a fluid received from the wellbore can move through the measurement tool in a laminar state. The measurement tool may be adjusted according to the measurement tool parameters such that the fluid moves in a turbulent state. The measurement tool may determine a laminar-turbulent transition region for the fluid. The measurement tool may output the laminar-turbulent transition region for use in a drilling operation in the wellbore.

Growing community of inventors

Spring, TX, United States of America

Andrew David Vos