Halliburton Energy Services, Inc.

Baidurja Ray

Avi Lin

Jianfu Ma

Tirumani N Swaminathan

Larry Steven Eoff

Daniel Joshua Stark

Dinesh Ananda Shetty

Aaron Gene Russell

Christopher Austin Lewis

Sergei Parsegov

Seyed Omid Razavi

Tirumani Swaminathan

Philip D Nguyen

Mikko K Jaaskelainen

Stanley Vernon Stephenson

Joshua Lane Camp

Janette Cortez Montalvo

Jie Bai

Vishwajit Manajirao Ghatge

Trent L Kennedy

Sean Michael Simpson

Hao Sun

Austen Murray

Joshua Camp

Disclosed herein is an automated process of identifying shut-in parameters of a hydraulic fracturing operation from hydraulic fracturing treatment (HF) data. Also disclosed is a system and computer program product for automatically determining shut-in parameters from HF data. The HF data can be collected in real time during a HF from various sensors, equipment, or systems typically used in HFs or present at a well site. In one example, a method for automatically determining hydraulic fracturing parameters includes: (1) obtaining HF data, (2) determining a Rate Shut-In (RSI) time from the HF data, (3) determining a Well Shut-In (WSI) time using the RSI, and (4) calculating an Instantaneous Shut-In Pressure (ISIP) value based upon both the RSI and the WSI times, wherein determining the RSI time, the WSI time and calculating the ISIP value are automatically performed by one or more processors.

Automated identification and application of hydraulic fracturing shut-in parameters

Aspects of the subject technology relate to systems and methods for optimizing multi-unit pumping operations at a well site. Systems and methods are provided for receiving sensor data from a hydraulic fracturing fleet equipment at an equipment system, designating an event as being flagged based on the sensor data from the hydraulic fracturing fleet equipment, determining a physical action based on the flagged event and a priority list of actions, and providing instructions to a first pump of the hydraulic fracturing fleet equipment to perform the physical action based on the flagged event and the priority list of actions.

Distributed diagnostics and control of a multi-unit pumping operation

A workflow for fracturing a subterranean formation includes providing fracturing databases or models for the hydrocarbon wellbore, selecting one or more fracturing fluid systems for fracturing the subterranean formation based on the fracturing databases or models and recommending at least one of the one or more selected fracturing fluid systems for fracturing the subterranean formation. Additionally, a workflow controller for fracturing a subterranean formation includes a workflow processing unit having fracturing models or databases to determine functional aspects of one or more fracturing fluid systems to provide a fracturing fluid system recommendation for the subterranean formation, and a fracturing fluid delivery unit that applies the fracturing fluid system recommendation to the subterranean formation. A hydrocarbon wellbore fracturing system for a subterranean formation is also provided.

System and method for selecting fluid systems for hydraulic fracturing

A system is provided including at least one pump for pumping a fluid into a wellbore, a pressure sensor provided at a wellhead of the wellbore for measuring a backpressure of the fluid being pumped into the wellbore, and a diagnostic manager. The diagnostic manager obtains pressure data associated with a pressure signal from the pressure sensor, wherein the pressure data includes pressure measurements of the fluid over a selected time period. The diagnostic manager converts, based on the pressure data, at least a portion of the pressure signal into frequency domain. The diagnostic manager detects a change in frequency of the pressure signal in the Fourier spectrum and determines that a fault associated with the wellbore has occurred based on the changed frequency of the pressure signal.

Detection of wellbore faults based on surface pressure of fluids pumped into the wellbore

The disclosure presents a technique for determining how downhole material will be distributed among two or more active perforation clusters in a hydraulic fracturing well system. The determination can be conducted during the execution of a treatment stage allowing modifications prior to completion of the treatment stage. The technique utilizes a three-step process where a first step can determine a predictive model of the wellbore, such as subterranean formation properties, wellbore properties, and target goal of the treatment stage. A second step can calibrate for unknown parameters, such as downhole HF fluid pressure at the active perforation clusters and downhole HF fluid flow rate at the perforation clusters. A third step can predict how downhole material will be distributed to the active perforation clusters and fracture clusters. The prediction result can be utilized to modify a pumping plan of the treatment stage to better achieve the targeted goal.

Predicting material distribution in a hydraulic fracturing treatment stage

The disclosure presents a process for calibrating a diversion model for a treatment stage of a hydraulic fracturing well site. The process can pump a portion of the proppant into the wellbore, flush the wellbore with clean HF fluid, and then perform a diagnostic test to determine a near-wellbore (NWB) flow resistance parameter. Next, diverter material can be distributed into the wellbore and the amount of diverter material delivered to each active perforation cluster can be estimated. A second diagnostic test can be performed followed by computing diversion model parameters such as a near-wellbore zone length parameter for perforation clusters capable of receiving HF fluid. In another aspect, a system is disclosed that can direct operations of a well site pump and collect data from surface and downhole diagnostic sensors, and then use the collected data for the diversion model calibration process.

Calibrating a diversion model for a hydraulic fracturing well system

A wellbore fracturing system that includes wellbore fracturing resources coupled through a wellbore conveyance to a subterranean formation of the wellbore; The wellbore fracturing system further includes a bottom hole pressure gauge that provides a bottom hole gauge pressure, and a processor coupled to the wellbore fracturing resources and the wellbore conveyance that calculates a wellbore friction pressure using a time-series sampling of bottom-hole gauge pressures for a fracturing fluid system after a uniform fracturing fluid condition is achieved in the wellbore. Also included are methods of calculating and managing a wellbore friction pressure.

Selection of fluid systems based on well friction characteristics

An illustrative monitoring system for a hydraulic fracturing operation includes: a data acquisition module collecting microseismic signals from a subterranean formation undergoing a hydraulic fracturing operation; a processing module implementing a monitoring method; and a visualization module that displays an estimate or prediction of fracture extent. The monitoring method implemented by the processing module includes: deriving microseismic event locations and times from the microseismic signals; fitting at least one fracture plane to the microseismic event locations; projecting each microseismic event location onto at least one fracture plane; determining a time-dependent distribution of the projected microseismic event locations; calculating one or more envelope parameters from the time-dependent distribution; and generating an estimate or prediction of fracture extent using the or more envelope parameters. The envelope parameters may include an exponent of a time-power law, and said generating may include re-fitting the fracture plane if the exponent isn't approximately one-half.

Systems and methods deriving hydraulic fracture growth from microseismicity analysis

The present disclosure relates to oil and gas well proppant compositions and methods for enhancing the conductivity of a propped fracture formed during a hydraulic fracturing operation. The method introduces a micro-proppant slurry prepared with slickwater containing both a low-density and a conventional micro-proppant during injection of the pad fluid stages to prop the natural and induced microfractures open and then injecting a proppant slurry prepared with slickwater containing low-density proppant and conventional frac sand during proppant slurry stage to prop the dominant fractures or large branches, provide open flow paths to keep them connective with the wellbore.

Methods for enhancing effective propped fracture conductivity

A method for improved data-driven estimation of a stimulated reservoir volume may generate an optimized surface that encloses a set of data points including microseismic event data corresponding to a treatment of a subterranean formation. A Delaunay triangulation may be performed on the set of data points to generate a set of polytopes. A Voronoi polygon may be generated about each data point and used to obtain a local density measure that is locally and adaptively determined for each data point. Based on the local density measure, polytopes in the set of polytopes may be discriminated for inclusion in the optimized surface.

Data-driven estimation of stimulated reservoir volume

In accordance with some embodiments of the present disclosure, a method of modeling a downhole drilling tool is disclosed. The method may include obtaining microseismic data corresponding to a treatment of a subterranean region, the microseismic data including a microseismic event time for each of a plurality of microseismic events, and a microseismic event location for each of the plurality of microseismic events. The method may additionally include calculating a plurality of fracture planes based upon the microseismic event times, and calculating a closed boundary enclosing a first subset of the plurality of fracture planes. The method may further include identifying a microseismic supported stimulated reservoir volume (&#x3bc;SRN) for the treatment based on the closed boundary.

Analysis of microseismic supported stimulated reservoir volumes

In some aspects, a closed boundary is computed based on locations and location-uncertainty domains of microseismic events associated with a stimulation treatment of a subterranean region. The closed boundary encloses the locations and respective location-uncertainty domains of multiple microseismic event data points. An error bound of a stimulated reservoir volume (SRV) for the stimulation treatment is identified based on the closed boundary.

Identifying an error bound of a stimulated reservoir volume of a subterranean region

In some aspects, a stimulated reservoir volume (SRV) parameter for a stimulation treatment applied to a subterranean region is identified. A parameter of a fracture-plane network generated by application of the stimulation treatment is identified. A correlation between the SRV parameter and the fracture-plane network parameter is identified. In some implementations, the SRV and the fracture-plane network are computed based on microseismic event data associated with the stimulation treatment.

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Houston, TX, United States of America

Baidurja Ray