Halliburton Energy Services, Inc.

Landmark Graphics Corporation

Jianfu Ma

Avi Lin

Harold Grayson Walters

Baidurja Ray

Vladimir Nikolayevich Martysevich

Dinesh Ananda Shetty

Tirumani N Swaminathan

Dwight David Fulton

Kenneth E Williams

Jianlei Sun

Ronald Glen Dusterhoft

Jie Bai

Youli Mao

Ajish Sreeni Radhakrishnan Potty

Ken Huang

Peng Zhang

A method may comprise identifying one or more pressure dissipation mechanisms that drop pressure within a fluid handling system, identifying one or more open flowpath elements, performing a matching algorithm with an information handling system, and initializing the matching algorithm with an estimate of a coefficient. A system may comprise a fluid handling system and an information handling system. The fluid handling system may comprise a fluid supply vessel, wherein the fluid supply vessel is disposed on a surface, pumping equipment, wherein the pumping equipment is attached to the fluid supply vessel and disposed on the surface; a wellbore supply conduit, wherein the wellbore supply conduit is attached to the pumping equipment and disposed in a formation, and a flowpath element, wherein the flowpath element fluidly couples the wellbore supply conduit to the formation.

Method for perforation clusters stimulation efficiency determination

A method may comprise plotting treatment data to form a plot of the treatment data, fitting a function to the plot of the treatment data, determining an intercept of the function, calculating one or more coefficients, plotting the one or more coefficients on a histogram, and identifying one or more active flowpath elements on the histogram. A system may comprise a fluid handling system and an information handling system. The fluid handling system may comprise a fluid supply vessel, wherein the fluid supply vessel is disposed on a surface; pumping equipment, wherein the pumping equipment it attached to the fluid supply vessel and disposed on the surface; wellbore supply conduit, wherein the wellbore supply conduit is attached to the pumping equipment and disposed in a formation; and a plurality of flowpath elements, wherein the flowpath elements fluidly couple the wellbore supply conduit to the formation.

Interpretation of pumping pressure behavior and diagnostic for well perforation efficiency during pumping operations

Disclosed are systems and methods for obtaining input data comprising properties associated with at least one parent well and a child well associated with the at least one parent well, dividing the input data into a training data subset, a validation data subset, and a test data subset, selecting at least one machine learning model using the training data subset, the validation data subset, and the test data subset based on k-fold cross validation, tuning hyper parameters for each of the at least one machine learning model, and generating a learning output using the at least one machine learning model and the hyper parameters for each of the at least one machine learning model, the learning output indicating a test root-mean-square error (RMSE) and a training RMSE.

Systems and methods for forecasting well interference

Disclosed are systems and methods for obtaining an input sequence of input data features associated with a well for at least one time stamp during a period of time including well production rates for the well and well operation constraints for the well, dividing the input data features into a training data subset, a validation data subset, and a test data subset, building a well production model for the well using machine learning based on the training data subset, the validation data subset, and the test data subset, and generating a forecast for the well for a future period of time using the well production model, the forecast comprising a future well production rate for the well including at least one of an oil rate, a gas rate, and a water rate.

Systems and methods for forecasting well productivity

The disclosure is directed to a method and system that estimates the number of active fractures for a given hydraulic fracturing fluid pressure. The hydraulic fracturing pressure can be correlated to a corresponding hydraulic fracturing fluid absorption rate of downhole fractures. Using the pressure and rate correlation, an active fracture ratio can be determined and then utilized to estimate the number of active fractures at a given hydraulic fracturing fluid pressure. In other aspects, a target fluid pressure is represented by a curve or other shape corresponding to a fluid friction model so that the fluid pressure correlation to the fluid absorption rate can be utilized to compute the active fracture ratio. The disclosed system is operable to control a well site pump system to adjust the fluid pressure and fluid composition, to monitor the downhole fluid, to collect the fluid values, and to compute an estimated active fracture ratio.

Estimating active fractures during hydraulic fracturing operations

The disclosure improves the analysis of the hydraulic fracturing (HF) break down process of a well system. The analysis can use as inputs collected HF data such as the HF fluid pressure, HF fluid flow rate, and HF fluid composition over one or more time intervals. In some aspects, the perforation parameters and stratigraphic well placement can also be used as inputs. The analysis can also use as inputs the HF model inputs that were used in collecting the HF data. The analysis can determine an effectiveness parameter of the received inputs. HF model inputs can be selected that would best fit a HF job plan goal for the current well system. In some aspects, the HF model inputs can be communicated to a well system controller of the current well system to further direct HF job plan operations.

Evaluating hydraulic fracturing breakdown effectiveness

An illustrative hydraulic fracture mapping method includes: collecting microseismic signals during a multistage hydraulic fracturing operation; deriving microseismic event locations from the microseismic signals to create a microseismic event map for each stage of the operation; fitting a set of fracture planes to the microseismic event maps; determining a stimulated reservoir volume ('SRV') region for each said stage; identifying where SRV regions overlap to form an overlap region; partitioning the overlap region to eliminate any overlap between the SRV regions; truncating the set of fracture planes for the SRV regions to discard any portion outside the revised SRV regions; and storing or displaying the truncated set of fracture planes for the first revised SRV region.

Stimulated fracture network partitioning from microseismicity analysis

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

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, reservoir characterizations of subterranean regions can be enhanced by using realtime fracture matching techniques for capturing the time dependent evolution of fracture parameters based on the occurrence of the time microseismic events generated by stimulation treatments. These microseismic events may further be used to determine hydraulic fracture planes, identify areas of concentration of high density microseismic events, identify and analyze complex fracture networks, and use these and other techniques to enhance the reservoir characterization.

Enhancing reservoir characterization using real-time SRV and fracture evolution parameters

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.

Identifying correlations between stimulated reservoir volume parameters and fracture network parameters

In some aspects, data for a new microseismic event associated with a stimulation treatment of a subterranean region is received. A boundary that was previously computed to enclose locations of prior microseismic events associated with the stimulation treatment is identified. The boundary is modified based on the data for the new microseismic event.

Real-time stimulated reservoir volume calculation

In some aspects, first and second boundaries are computed based on locations of microseismic events associated with a stimulation treatment of a subterranean region. Based on the first and second boundaries, an uncertainty associated with a stimulated reservoir volume (SRV) for the stimulation treatment is identified. The first and second boundaries are defined in a common spatial domain and at least a portion of the second boundary resides outside the first boundary.

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Sugar Land, TX, United States of America

Jianfu Ma