Halliburton Energy Services, Inc.

Landmark Graphics Corporation

Harold Grayson Walters

Ronald Glen Dusterhoft

Billy F Slabaugh

Jason E Bryant

Avi Lin

Phillip C Harris

Jianfu Ma

Roger Lynn Schultz

Neal Gregory Skinner

Mohamed Yousef Soliman

Stanley J Heath

Loyd Eddie East

Billy Wilson McDaniel

Vladimir Nikolayevich Martysevich

Priyesh Ranjan

Stanley Vernon Stephenson

Ronnie Glen Morgan

Jeffrey Marc Yarus

Leonard R Case

Dwight David Fulton

Johnny W Johnson

Glenn Robert McColpin

Manisha Bhardwaj

Shahab Jamali Ghare Tape

Tommy Slabaugh, Legal Representative

Michael Segura

David M Barrick

Jonn Thompson

Von Parkey

Glenn Robert Mccolpin

Billy Wilson Mcdaniel

Jimmie Dean Weaver, Jr

Mikko K Jaaskelainen

Rickey Lynn Morgan

Ken A Smith

Joseph A Beisel

Mark A Parker

Herbert John Horinek

Jie Bai

Samuel Bryant Johnson

Peyman Heidari

Shaun Burns

Philip D Nguyen

Rajesh Kumar Saini

Thomas Donovan Welton

David Eugene McMechan

Andrey V Filippov

Michael Wayne Sanders

Richard W Pauls

Jim D Weaver

Dinesh Ananda Shetty

Michael A McCabe

Trinidad Munoz, Jr

Ronald J Powell

Amit Kumar

Terry Wayne Wong

David B Allison

Bobby K Bowles

Neil Alan Stegent

Norman Raymond Warpinski

Dominic Camilleri

R Clay Cole

Shang Zhang

Crispin Doyle

Sean R Beach

Pandurang Manohar Kulkarni

Bobby J Burns

Ajish Sreeni Radhakrishnan Potty

Shohreh Amini

Rama Subba Reddy Thavva

Gaetan Bardy

Gaetan Pierre Louis Bardy

Gregory L Tanaka

Robert Douglas Hillard

Vikesh Singh Baghel

Ronald E Hyden

Steve F Wilson

Luis Alexander Matzar

Greg Daniel Brumbaugh

Steven James Drinovsky

Kevin B Hall

Meftun Erdogan

Billy Ray Slabaugh

Ron J Powell

Shane L Milson

Hailun Ni

Richa Chauhan

Billy Francis Slabaugh, Jr

Erik Lee

Jeffery L Mundy

Christina A Parkinson

Shaun Bums

Herbert Hornick

Norman R Warpinski

Richard James Langenwalter

Jesse C Hampton

Luis A Matzar

Michelle Renee Sansil

Richard T Gonzalez

Kenneth R Coffman

The disclosure is directed to methods to design and revise hydraulic fracturing (HF) job plans. The methods can utilize one or more data sources from public, proprietary, confidential, and historical sources. The methods can build mathematical, statistical, machine learning, neural network, and deep learning models to predict production outcomes based on the data source inputs. In some aspects, the data sources are processed, quality checked, and combined into composite data sources. In some aspects, ensemble modeling techniques can be applied to combine multiple data sources and multiple models. In some aspects, response features can be utilized as data inputs into the modeling process. In some aspects, time-series extracted features can be utilized as data inputs into the modeling process. In some aspects, the methods can be used to build a HF job plan prior to the start of work at a well site. In other aspects, the methods can be used to revise an existing HF job plan in real-time, such as after a treatment cycle, a pumping stage, or a time interval.

Hydraulic fracturing job plan real-time revisions utilizing collected time-series data

The life of internal components of a frack pump is affected by the frack fluid being pumped. The disclosure evaluates pump components and identifies parameters of frack pumps that may affect the remaining life of pump components based on pump models generated using flow type histories of the frack pumps. Pump related factors can also be used to identify the pump parameters. In one example, a method of evaluating pump components of a frack pump includes: (1) comparing a flow type history of the frack pump to at least one pump model, wherein the flow type history is automatically determined and is based on a proppant concentration of frack fluid pumped by the frack pump, (2) evaluating a condition of at least one component of the pump based on the comparing, and (3) changing a parameter of the pump based on the evaluating.

Automatically detecting a key parameter affecting pump components

Hydraulic fracturing operation planning using data-driven multi-variate statistical machine learning modeling

The life of internal components of a frack pump is affected by the frack fluid being pumped. Manually trying to keep track of the frack fluid type being pumped is a tedious task that is susceptible to incorrect data or missing data. As such, the disclosure provides automated tracking of the amount of time or fluid volume that frack pumps pump the different fluid types and managing usage of the frack pumps using a history of the pumping. An example method of managing usage of a frack pump includes: (1) obtaining, for a time period or fluid volume, a proppant presence for a frack fluid being pumped by a frack pump, (2) automatically determining a flow type history for the frack pump over the time period or fluid volume based at least on the proppant presence, and (3) controlling a usage of the frack pump using the flow type history.

Automatically determining flow type histories for frack pumps and managing usage thereof using the flow type histories

Disclosed is generating an acquisition request of a component, using a probabilistic model based on current and planned life consumption, to maintain a usable component inventory, by: determining planned consumption of the component; retrieving historical lifetime data associated with the component; determining the associated normalized current life consumed for historical specimens at failure based on a power law equivalency model; determining a probability of survival distribution associated with the component; determine a probability of future failure of each component in inventory given planned consumption of the component; determine a projected number of component failures prior to completion of the job associated with the component; generate the at least one acquisition request to acquire a quantity of new components at least equal to the projected number of specific component failures prior to completion of the job; wherein the usable inventory of the component includes at least the quantity of new components.

Systems and methods for automated probabilistic based forecasts of component demand and cost incorporating data up-sampling

The disclosure presents a technique to generate a fracture model using a differential stress map and model inputs. The technique simulates the fracture model using fracture fronts, initiated at perforations of a perforation stage of a hydraulic fracturing (HF) wellbore. Each fracture front is evaluated using a propagation step of a fracture model process. Using the relative differential stress states, a fracture pattern is composited to the fracture model. At each propagation step, the total energy available from the simulated HF fluid being pumped into the wellbore location is reduced by the amount necessary to generate the computed fractures. Once the remaining energy is reduced to a level where no further fractures can be created, or if a map boundary is encountered, the fracture model process terminates. The generated fracture model can be communicated to update HF job plans, wellbore placements, and other uses of the fracture model.

Simulating hydraulic fracturing geometry propagation using a differential stress and pattern-based model

An apparatus for measuring mechanical properties of a rock formation. The apparatus includes force application fixtures configured to apply opposing compressive forces to a disc-shaped sample of a core plug specimen from the rock formation. Each of the force application fixtures include an applicant portion having an end cap. The end cap has a shaped surface that is configured to conform with a portion of a non-planar side of the disc-shaped sample such that substantially an entire volume of the disc-shaped sample experiences a compressive stress when the opposing compressive forces are applied to the portions of the non-planar side. A system and method for measuring mechanical properties of a rock formation are also disclosed.

Method, apparatus and system for estimation of rock mechanical properties

Geomechanical parameters can be used to optimize a well configuration that includes one or more projected wells having locations and geometries. Formation data and regional stress information of a formation can be used to determine a local stress variation of the formation. A quality index can be generated by combining petrophysical properties with the local stress variation. Hydrocarbon recovery flow simulations can be generated by generating well configuration models based on the quality index, generating reservoir geomechanical model that includes hydraulic fracture propagation characteristics, determining new hydraulic fractures by simulating propagation through the reservoir geomechanical model and using geomechanical rules, and determining a projected hydrocarbon recovery rate by simulating flow with the new hydraulic fractures. A well placement plan can be selected using the projected hydrocarbon recovery rates. The well placement plan can be output to be used to plan one or more wellbores.

Planning a well configuration using geomechanical parameters

A method for real time crush testing of proppants including loading proppant into an apparatus comprising: a body with a chamber to accept a piston and proppant; a pressure piston; a pressure transducer located in the bottom of the chamber; and a displacement sensor; compressing the proppant with the pressure; calculating the amount of proppant material in the proppant pack; increasing pressure on the proppant pack until the sample is crushed; calculating proppant strength from at least the displacement sensor data. An apparatus includes a body with a chamber to accept a piston and proppant; a pressure piston; a pressure transducer located in the bottom of the chamber; and a displacement sensor.

Real time on location crush and conductivity testing

Disclosed are systems and methods for receiving historical production data associated with at least one hydraulic fracturing well, receiving time-series data associated with the at least one hydraulic fracturing well, the time-series data representing at least one type of data, receiving non-temporal data associated with the at least one hydraulic fracturing well, generating a machine learning model based on the historical production data, the time-series data associated with the at least one hydraulic fracturing well and based on an original job design during a first stage of the job at a particular hydraulic fracturing well, and the non-temporal data, determining an optimized job design for the particular hydraulic fracturing well having an objective function using a prediction based on the machine learning model, and implementing the optimized job design for the particular hydraulic fracturing well.

Systems and methods for real-time hydraulic fracture control

A fracturing treatment optimization system using multi-point pressure sensitive fiber optic cables to measure interwell fluid interaction data, microdeformation strain data, microseismic data, distributed temperature data, distributed acoustic data, and distributed strain data from multiple locations along a wellbore. The fracturing treatment optimization system may analyze the interwell fluid interaction data, microdeformation strain data, microseismic data, distributed temperature data, distributed acoustic data, and distributed strain data, modify a subsurface fracture network model, and calculate interwell fluid interaction effects. The fracturing treatment optimization system may use the fracture network model to measure current and predict future fracture growth, hydraulic pressure, poroelastic pressure, strain, stress, and related completion effects. The fracturing treatment optimization system may enable real-time monitoring and analysis of treatment and monitoring wells. The fracturing treatment optimization system may suggest and effect modifications to optimize treatment of the treatment and monitoring wells.

Well interference sensing and fracturing treatment optimization

A method of determining fracture complexity may comprise receiving one or more signal inputs from a fracturing operation, calculating an observed fracture growth rate based at least partially on the one or more signal inputs, calculating a predicted fracture growth rate, determining a fracture complexity value, and applying a control technique to make adjustments a hydraulic stimulation operation based at least in part on the fracture complexity value. Also provided is a system for determining a fracture complexity for a hydraulic fracturing operation may comprise a hydraulic fracturing system, a sensor unit to receive one or more signal inputs, a calculating unit, a fracture complexity unit, and a controller unit to apply a control technique to adjust one or more hydraulic stimulation parameters on the hydraulic fracturing system.

Estimation of fracture complexity

Some aspects of what is described here relate to seismic profiling techniques. A seismic excitation is generated in a first directional section of a first wellbore in a subterranean region. Seismic responses associated with the seismic excitation are detected in directional sections of a plurality of other wellbores in the subterranean region. A fracture treatment of the subterranean region is analyzed based on the seismic responses. In some instances, a multi-dimensional seismic velocity model of the subterranean region is generated based on the seismic responses.

Fracture treatment analysis based on multiple-wellbore seismic detection

Systems and methods using electrically controlled propellant to operate equipment in subterranean formations are provided. In some embodiments, the methods comprise: providing a tool assembly that comprises a tool body and an electrically controlled propellant; and placing the tool assembly in at least a portion of a subterranean formation. Electrical current may be applied to at least a portion of the electrically controlled propellant to ignite the portion of the propellant to operate a portion of the tool assembly.

Electrically controlled propellant in subterranean operations and equipment

A fracturing controller, a method for controlling fracture diversion, and a hydraulic fracturing system are provided herein. One example of a method for controlling fracture diversion of a fracture during hydraulic fracturing, includes: (1) providing a first fracturing treatment for the fracture at a first pump rate, (2) subsequently providing a low rate treatment for the fracture at a reduced pump rate less than the first pump rate, and (3) changing the reduced pump rate based on proppant bridging in the fracture during the low rate treatment.

Control of far field fracture diversion by low rate treatment stage

Growing community of inventors

Tomball, TX, United States of America

Harold Grayson Walters