Halliburton Energy Services, Inc.

Tian He

Christopher Michael Jones

Darren George Gascooke

Bin Dai

Michael Thomas Pelletier

Dingding Chen

Mehdi Alipour Kallehbasti

Ming Gu

Di Du

Luis Emilio San Martin

Robert Paul Freese

Hua Xia

Robert S Atkinson

Satyan Gopal Bhongale

Jing Shen

Mehdi Alipour Kallenhbasti

A method includes obtaining a plurality of master sensor responses with a master sensor in a set of training fluids and obtaining node sensor responses in the set of training fluids. A linear correlation between a compensated master data set and a node data set is then found for a set of training fluids and generating node sensor responses in a tool parameter space from the compensated master data set on a set of application fluids. A reverse transformation is obtained based on the node sensor responses in a complete set of calibration fluids. The reverse transformation converts each node sensor response from a tool parameter space to the synthetic parameter space and uses transformed data as inputs of various fluid predictive models to obtain fluid characteristics. The method includes modifying operation parameters of a drilling or a well testing and sampling system according to the fluid characteristics.

System and methods for mapping sensor data across parameter spaces

The present disclosure relates generally to a system and method for increasing the reliability and data-rate transmission of information from a downhole device to the surface and from the surface to the downhole device. A fluid sampling system may comprise a downhole tool positionable in a wellbore and comprising a fluid testing chamber. The downhole tool may also comprise a light spectrum analysis unit disposed at a surface of the wellbore, wherein the light spectrum analysis unit comprises a detector. The downhole tool may further comprise a fiber optic cable for carrying light from the downhole tool to the light spectrum analysis unit, wherein the fiber optic cable is connected to the downhole tool and the light spectrum analysis unit.

Two frequency comb fourier spectroscopy for chemical sensing

Disclosed are methods and systems for determination of fluid contamination of a fluid sample from a downhole fluid sampling tool. A method may comprise obtaining a fluid sample, wherein the fluid sample comprises a reservoir fluid contaminated with a well fluid; obtaining input parameters, wherein the input parameters comprise fluid properties obtained from measurement of the fluid sample and mud filtrate composition; obtaining initial values of iterative parameters, wherein the iterative parameters comprise fluid contamination of the fluid sample; determining calculated fluid properties of the reservoir fluid using equation of state flash calculating; and repeating steps of determining component mole fractions and determining calculated fluid properties for use in the mole fraction distribution function until a comparison of one or more of the calculated fluid properties with one or more of the input parameters is within a tolerance error.

Drilling fluid contamination determination for downhole fluid sampling tool

A downhole formation fluid identification sensing module for measuring averaged gas molecular weight of wellbore formation fluid acquires simultaneous temperature, pressure, and density measurements. The sensing module includes two venturi-type gas sensors that both contain vibrating tubes. During operation, formation fluid flows through the vibrating tubes whereby resonant frequency measurements are acquired simultaneously with temperature and pressure measurements. Each measurement is then utilized to determine the gas molecular weight of the dry, wet or saturated formation fluid.

Thermal modulated vibrating sensing module for gas molecular weight detection

Disclosed is the detection of emulsions and microdispersions with an optical computing device. One disclosed method includes emitting electromagnetic radiation from an electromagnetic radiation source, optically interacting the electromagnetic radiation with a fluid and thereby generating fluid interacted radiation, detecting a portion of the fluid interacted radiation with a reference detector arranged within an optical channel of an optical computing device, generating a reference signal with the reference detector, and determining an emulsive state of the fluid based on the reference signal.

Emulsion detection using optical computing devices

A method includes obtaining a plurality of master sensor responses with a master sensor in a set of training fluids and obtaining node sensor responses in the set of training fluids. A linear correlation between a compensated master data set and a node data set is then found for a set of training fluids and generating node sensor responses in a tool parameter space from the compensated master data set on a set of application fluids. A reverse transformation is obtained based on the node sensor responses in a complete set of calibration fluids. The reverse transformation converts each node sensor response from a tool parameter space to the synthetic parameter space, and uses transformed data as inputs of various fluid predictive models to obtain fluid characteristics. The method includes modifying operation parameters of a drilling or a well testing and sampling system according to the fluid characteristics.

System and methods for cross-sensor linearization

Disclosed are methods and systems for determination of fluid contamination of a fluid sample from a downhole fluid sampling tool. A method may comprise obtaining a fluid sample, obtaining input parameters, wherein the input parameters comprise fluid properties obtained from measurement of the fluid sample and mud filtrate composition, obtaining initial values of iterative parameters, determining component mole fractions of the reservoir fluid using the initial values of the iterative parameters in a mole fraction distribution function, determining calculated fluid properties of the reservoir fluid using equation of state flash calculating, and repeating steps of determining component mole fractions and determining calculated fluid properties and further obtaining updated values of the iterative parameters for use in the mole fraction distribution function until a comparison of one or more of the calculated fluid properties with one or more of the input parameters is within a tolerance error.

Disclosed herein are methods and systems for fluid characterization of fluid samples from a downhole fluid sampling tool. A fluid characterization method may include obtaining a fluid sample of a reservoir fluid; analyzing the fluid sample to derive input parameters, wherein the input parameters comprise fluid properties obtained from measurement of the fluid sample; determining component mole fractions of the fluid sample using a mole fraction distribution function; and determining calculated fluid properties using equation of state flash calculating.

Fluid characterization and phase envelope prediction from downhole fluid sampling tool

A method of cross-tool optical fluid model validation includes selecting verified field data measured with a first sensor of an existing tool as validation fluids and selecting a second sensor for a new tool or on a different existing tool. The method may also include applying cross-tool optical data transformation to the validation fluids in a tool parameter space from the first sensor to the second sensor, and calculating the synthetic optical responses of the second sensor on the validation fluids through cross-space data transformation. The method may further include determining a new or adjusting an existing operational fluid model of the second sensor in a synthetic parameter space according to the candidate model performance evaluated on the validation fluids, and optimizing well testing and sampling operation based on real-time estimated formation fluid characteristics using the validated fluid models of the second sensor in an operating tool.

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Houston, TX, United States of America

Tian He