Patent Publication Number: US-11047220-B2

Title: Real-time optimization of stimulation treatments for multistage fracture stimulation

Description:
CROSS-REFERENCE TO RELATED APPLICATIONS 
     This application is a national stage entry of PCT/US2017/015759 filed Jan. 31, 2017, said application is expressly incorporated herein in its entirety. 
     FIELD OF THE DISCLOSURE 
     The present disclosure generally relates to systems and methods for real-time optimization of stimulation treatments for multistage fracture stimulation. More particularly, the present disclosure relates to real-time optimization of stimulation treatments in a hydrocarbon reservoir by controlling a simulated stimulation treatment schedule for a main fracture stimulation treatment stage using a predicted net pressure in a cluster of fractures representing a dominant fracture for the main fracture stimulation treatment stage. 
     BACKGROUND 
     In the oil and gas industry, a well that is not producing as expected may need stimulation to increase the production of subsurface hydrocarbon deposits, such as oil and natural gas. Hydraulic fracturing is a type of stimulation treatment that has long been used for well stimulation in unconventional reservoirs. A multistage stimulation treatment operation may involve drilling a lateral wellbore and injecting treatment fluid into a surrounding formation in multiple stages via a series of perforations or formation entry points along a path of a wellbore through the formation. During each of the stimulation treatment, different types of fracturing fluids, proppant materials (e.g., sand), additives and/or other materials may be pumped into the formation via the entry points or perforations at high pressures to initiate and propagate fractures within the formation to a desired extent. With advancements in lateral well drilling and multistage hydraulic fracturing of unconventional reservoirs, there is a greater need for ways to accurately monitor the downhole flow and distribution of injected fluids across different clusters of fractures and efficiently deliver treatment fluid into the subsurface formation. 
     Diversion is a technique used in injection treatments to facilitate uniform distribution of treatment fluid over each stage of the treatment. Diversion may involve the delivery of a diverting agent into the wellbore to divert injected treatment fluids toward formation entry points along the wellbore path that are receiving inadequate treatment. Examples of different diverting agents include, but are not limited to, viscous foams, particulates, gels, benzoic acid and other chemical diverters. Traditionally, operational decisions related to the use of diversion technology for a given treatment stage, including when and how much diverter is used, are made a priori according to a predefined treatment schedule. Such conventional diversion techniques therefore, fail to consider the parameters of a successfully diverted main fracture stimulation treatment stage before determining the next main fracture stimulation treatment schedule. 
    
    
     
       BRIEF DESCRIPTION OF THE DRAWINGS 
       The present disclosure is described below with references to the accompanying drawings in which like elements are referenced with like reference numerals, and in which: 
         FIG. 1  is a schematic diagram illustrating a well system for multistage fracture stimulation treatment in a hydrocarbon reservoir. 
         FIGS. 2A-2B  are a flow diagram illustrating one embodiment of a method for implementing the present disclosure. 
         FIG. 3  is a block diagram illustrating one embodiment of a computer system for implementing the present disclosure 
     
    
    
     DESCRIPTION OF THE ILLUSTRATIVE EMBODIMENTS 
     The subject matter of the present disclosure is described with specificity, however, the description itself is not intended to limit the scope of the disclosure. The subject matter thus, might also be embodied in other ways, to include different structures, steps and/or combinations similar to and/or fewer than those described herein, in conjunction with other present or future technologies. Although the term “step” may be used herein to describe different elements of methods employed, the term should not be interpreted as implying any particular order among or between various steps herein disclosed unless otherwise expressly limited by the description to a particular order. Other features and advantages of the disclosed embodiments will be or will become apparent to one of ordinary skill in the art upon examination of the following figures and detailed description. It is intended that all such additional features and advantages be included within the scope of the disclosed embodiments. Further, the illustrated figures are only exemplary and are not intended to assert or imply any limitation with regard to the environment, architecture, design, or process in which different embodiments may be implemented. 
     The present disclosure overcomes one or more deficiencies in the prior art by real-time optimization of stimulation treatments in a hydrocarbon reservoir by controlling a simulated stimulation treatment schedule for a main fracture stimulation treatment stage using a predicted net pressure in a cluster of fractures representing a dominant fracture for the main fracture stimulation treatment stage. 
     In one embodiment, the present disclosure includes a method for optimization of stimulation treatments for a main fracture stimulation treatment stage, which comprises: measuring values for i) a fluid flow allocation for each cluster of fractures associated with the main fracture stimulation treatment stage using fiber optic sensors and a surface pressure profile; and ii) tortuosity and friction pressure losses across each cluster of fractures; calibrating a fracture model by iteratively simulating values for i) the fluid flow allocation for each cluster of fractures associated with the main fracture stimulation treatment stage and the surface pressure profile; and ii) the tortuosity and friction pressure losses across each cluster of fractures until a difference in the simulated values and the respective measured values is within a predetermined margin of error; simulating an initial treatment schedule for the main fracture stimulation treatment stage using the calibrated fracture model and one or more initial treatment schedule parameters; calculating a predicted net pressure value for each cluster of fractures using one of the simulated initial treatment schedule and an updated treatment schedule; updating the simulated initial treatment schedule until a difference between the predicted net pressure value for a cluster of fractures representing a dominant fracture and a predetermined net pressure value for a cluster of fractures representing another dominant fracture is within another predetermined margin of error, which represents a last updated treatment schedule; and performing the main fracture stimulation treatment stage based on the last updated treatment schedule. 
     In another embodiment, the present disclosure includes a non-transitory program carrier device tangibly carrying computer executable instructions for optimization of stimulation treatments for a main fracture stimulation treatment stage, the instructions being executable to implement: measuring values for i) a fluid flow allocation for each cluster of fractures associated with the main fracture stimulation treatment stage using fiber optic sensors and a surface pressure profile; and ii) tortuosity and friction pressure losses across each cluster of fractures; calibrating a fracture model by iteratively simulating values for i) the fluid flow allocation for each cluster of fractures associated with the main fracture stimulation treatment stage and the surface pressure profile; and ii) the tortuosity and friction pressure losses across each cluster of fractures until a difference in the simulated values and the respective measured values is within a predetermined margin of error; simulating an initial treatment schedule for the main fracture stimulation treatment stage using the calibrated fracture model and one or more initial treatment schedule parameters; calculating a predicted net pressure value for each cluster of fractures using one of the simulated initial treatment schedule and an updated treatment schedule; updating the simulated initial treatment schedule until a difference between the predicted net pressure value for a cluster of fractures representing a dominant fracture and a predetermined net pressure value for a cluster of fractures representing another dominant fracture is within another predetermined margin of error, which represents a last updated treatment schedule; and performing the main fracture stimulation treatment stage based on the last updated treatment schedule. 
     In yet another embodiment, the present disclosure includes a non-transitory program carrier device tangibly carrying computer executable instructions for optimization of stimulation treatments for a main fracture stimulation treatment stage, the instructions being executable to implement: measuring values for i) a fluid flow allocation for each cluster of fractures associated with the main fracture stimulation treatment stage and a surface pressure profile during a step down test; and ii) tortuosity and friction pressure losses across each cluster of fractures after the step down test; calibrating a fracture model by iteratively simulating values for i) the fluid flow allocation for each cluster of fractures associated with the main fracture stimulation treatment stage and the surface pressure profile; and ii) the tortuosity and friction pressure losses across each cluster of fractures until a difference in the simulated values and the respective measured values is within a predetermined margin of error; simulating an initial treatment schedule for the main fracture stimulation treatment stage using the calibrated fracture model and one or more initial treatment schedule parameters; calculating a predicted net pressure value for each cluster of fractures using one of the simulated initial treatment schedule and an updated treatment schedule; updating the simulated initial treatment schedule until a difference between the predicted net pressure value for a cluster of fractures representing a dominant fracture and a predetermined net pressure value for a cluster of fractures representing another dominant fracture is within another predetermined margin of error, which represents a last updated treatment schedule; and performing the main fracture stimulation treatment stage based on the last updated treatment schedule. 
     While the present disclosure may be described with respect to stimulation treatments in a hydrocarbon reservoir, it is not limited thereto and may also be applied to other types of stimulation treatments (e.g., matrix acidizing treatments) to achieve similar results. 
     Referring now to  FIG. 1 , a schematic diagram illustrates an example of a well system  100  for performing a multistage stimulation treatment within a hydrocarbon reservoir formation. As shown in the example of  FIG. 1 , well system  100  includes a wellbore  102  in a subsurface formation  104  beneath a surface  106  of the wellsite. Wellbore  102  as shown in the example of  FIG. 1  includes a lateral portion. However, it should be appreciated that embodiments are not limited thereto and that well system  100  may include any combination of lateral, vertical, slant, curved, and/or other wellbore orientations. The subsurface formation  104  in this example may include a reservoir that contains hydrocarbon resources, such as oil, natural gas, and/or others. For example, the subsurface formation  104  may be a rock formation (e.g., shale, coal, sandstone, granite, and/or others) that includes hydrocarbon deposits, such as oil and natural gas. In some cases, the subsurface formation  104  may be a tight gas formation that includes low permeability rock (e.g., shale, coal, and/or others). The subsurface formation  104  may be composed of naturally fractured rock and/or natural rock formations that are not fractured to any significant degree. 
     Well system  100  also includes a fluid injection system  108  for injecting treatment fluid, e.g., hydraulic fracturing fluid, into the subsurface formation  104  over multiple sections  118   a ,  118   b ,  118   c ,  118   d , and  118   e  (collectively referred to herein as “sections  118 ”) of the wellbore  102 , as will be described in further detail below. Each of the sections  118  may correspond to, for example, a different stage or interval of the multistage stimulation treatment. The boundaries of the respective sections  118  and corresponding treatment stages/intervals along the length of the wellbore  102  may be delineated by, for example, the locations of bridge plugs, packers and/or other types of equipment in the wellbore  102 . Additionally, or alternatively, the sections  118  and corresponding treatment stages may be delineated by particular features of the subsurface formation  104 . Although five sections are shown in  FIG. 1 , it should be appreciated that any number of sections and/or treatment stages may be used as desired for a particular implementation. Furthermore, each of the sections  118  may have different widths or may be uniformly distributed along the wellbore  102 . 
     As shown in  FIG. 1 , injection system  108  includes an injection control subsystem  111 , a signaling subsystem  114  installed in the wellbore  102 , and one or more injection tools  116  installed in the wellbore  102 . The injection control subsystem  111  can communicate with the injection tools  116  from a surface  110  of the wellbore  102  via the signaling subsystem  114 . Although not shown in  FIG. 1 , injection system  108  may include additional and/or different features for implementing the optimization techniques disclosed herein. For example, the injection system  108  may include any number of computing subsystems, communication subsystems, pumping subsystems, monitoring subsystems, and/or other features as desired for a particular implementation. In some implementations, the injection control subsystem  111  may be communicatively coupled to a remote computing system (not shown) for exchanging information via a network for purposes of monitoring and controlling wellsite operations, including operations related to the stimulation treatment. Such a network may be, for example and without limitation, a local area network, medium area network, and/or a wide area network, e.g., the Internet. 
     During each stage of the stimulation treatment, the injection system  108  may alter stresses and create a multitude of fractures in the subsurface formation  104  by injecting the treatment fluid into the surrounding subsurface formation  104  via a plurality of formation entry points along a portion of the wellbore  102  (e.g., along one or more of sections  118 ). The fluid may be injected through any combination of one or more valves of the injection tools  116 . The injection tools  116  may include numerous components including, but not limited to, valves, sliding sleeves, actuators, ports, and/or other features that communicate treatment fluid from a working string disposed within the wellbore  102  into the subsurface formation  104  via the formation entry points. The formation entry points may include, for example, open-hole sections along an uncased portion of the wellbore path, a cluster of perforations along a cased portion of the wellbore path, ports of a sliding sleeve completion device along the wellbore path, slots of a perforated liner along the wellbore path, or any combination of the foregoing. 
     The injection tools  116  may also be used to perform diversion in order to adjust the downhole flow distribution of the treatment fluid across the plurality of formation entry points. Thus, the flow of fluid and delivery of diverter material into the subsurface formation  104  during the stimulation treatment may be controlled by the configuration of the injection tools  116 . The diverter material injected into the subsurface formation  104  may be, for example, a degradable polymer. Examples of different degradable polymer materials that may be used include, but are not limited to, polysaccharides; lignosulfonates; chitins; chitosans; proteins; proteinous materials; fatty alcohols; fatty esters; fatty acid salts; aliphatic polyesters; poly(lactides); poly(glycolides); poly(ϵ-caprolactones); polyoxymethylene; polyurethanes, poly(hydroxybutyrates); poly(anhydrides); aliphatic polycarbonates; polyvinyl polymers; acrylic-based polymers poly(amino acids); poly(aspartic acid); poly(alkylene oxdies); poly(ethylene oxides); polyphosphazenes; poly(orthoesters); poly(hydroxy ester ethers); polyether esters, polyester amides; polyamides; polyhydroxyalkanoates; polyethyleneterephthalates; polybutyleneterephthalates; polyethylenenapthalenates; and copolymers, blends, derivatives, or combinations thereof. However, it should be appreciated that embodiments of the present disclosure are not intended to be limited thereto and that other types of diverter materials may also be used. 
     In one or more embodiments, the valves, ports, and/or other features of the injection tools  116  can be configured to control the location, rate, orientation, and/or other properties of fluid flow between the wellbore  102  and the subsurface formation  104 . The injection tools  116  may include multiple tools coupled by sections of tubing, pipe, or another type of conduit. The injection tools may be isolated in the wellbore  102  by packers or other devices installed in the wellbore  102 . 
     In some implementations, the injection system  108  may be used to create or modify a complex fracture network in the subsurface formation  104  by injecting fluid into portions of the subsurface formation  104  where stress has been altered. For example, the complex fracture network may be created or modified after an initial injection treatment has altered stress by fracturing the subsurface formation  104  at multiple locations along the wellbore  102 . After the initial injection treatment alters stresses in the subterranean formation, one or more valves of the injection tools  116  may be selectively opened or otherwise reconfigured to stimulate, or re-stimulate, specific areas of the subsurface formation  104  along one or more sections  118  of the wellbore  102 , taking advantage of the altered stress states to create complex fracture networks. In some cases, the injection system  108  may inject fluid simultaneously for multiple intervals and sections  118  of wellbore  102 . 
     The operation of the injection tools  116  may be controlled by the injection control subsystem  111 . The injection control subsystem  111  may include, for example, data processing equipment, communication equipment, and/or other systems that control injection treatments applied to the subsurface formation  104  through the wellbore  102 . It should be appreciated that such control systems may be automated to enable the techniques disclosed herein to be performed without any user intervention. Additionally, or alternatively, the operation of one or more of these systems may be controlled at least partly based on input from a user via a user interface provided by the injection control subsystem  111 , as will be described in further detail below with respect to  FIG. 3 . 
     In one or more embodiments, the injection control subsystem  111  may receive, generate, or modify a baseline treatment plan for implementing the various stages of the stimulation treatment along the path of the wellbore  102 . The baseline treatment plan may specify a baseline pumping schedule for the treatment fluid injections and diverter deployments over each stage of the stimulation treatment. The baseline treatment plan may also specify initial or predetermined values for relevant parameters of the treatment fluid and diverter to be injected into the subsurface formation  104  during each treatment cycle and diversion phase, respectively, of each stage of the stimulation treatment. The parameters specified by such a baseline plan may include, for example, a pre-determined amount of diverter to be injected into the subsurface formation  104  during one or more diversion phases of the stimulation treatment. The predetermined diverter amount in this example may be based on historical data relating to the diverter usage during prior stimulation treatments performed along other wellbores drilled within the same hydrocarbon producing field. Additionally, or alternatively, the predetermined diverter amount may be based on the results of a computer simulation performed during a design phase of the treatment. In one or more embodiments, the predetermined diverter amount to be injected into the subsurface formation  104  may be adjusted based on the techniques described in further detail below. 
     In one or more embodiments, the injection control subsystem  111  initiates control signals to configure or reconfigure the injection tools  116  and/or other equipment (e.g., pump trucks, etc.) in real time based on the treatment plan or modified version thereof. During operation, the signaling subsystem  114  as shown in  FIG. 1  transmits the signals from the injection control subsystem  111  at the wellbore surface  110  to one or more of the injection tools  116  disposed in the wellbore  102 . For example, the signaling subsystem  114  may transmit hydraulic control signals, electrical control signals, and/or other types of control signals. The control signals may be reformatted, reconfigured, stored, converted, retransmitted, and/or otherwise modified as needed or desired en-route between the injection control subsystem  111  (and/or another source) and the injection tools  116  (and/or another destination). The transmitted signals thereby enable the injection control subsystem  111  to control the operation of the injection tools  116  while the treatment is in progress. Examples of different ways to control the operation of each of the injection tools  116  include, but are not limited to, opening, closing, restricting, dilating, repositioning, reorienting, and/or otherwise manipulating one or more valves of the tool to modify the manner in which treatment fluid, proppant, or diverter is communicated into the subsurface formation  104 . 
     It should be appreciated that the combination of injection valves of the injection tools  116  may be configured or reconfigured at any given time during the stimulation treatment. It should also be appreciated that the injection valves may be used to inject any of various treatment fluids, proppants, and/or diverter materials into the subsurface formation  104 . Examples of such proppants include, but are not limited to, sand, bauxite, ceramic materials, glass materials, polymer materials, polytetrafluoroethylene materials, nut shell pieces, cured resinous particulates comprising nut shell pieces, seed shell pieces, cured resinous particulars comprising seed shell pieces, fruit pit pieces, cured resinous particulates comprising fruit pit pieces, wood, composite particulates, lightweight particulates, microsphere plastic beads, ceramic microspheres, glass microspheres, manmade fibers, cement, fly ash, carbon black powder, and combinations thereof. 
     In some implementations, the signaling subsystem  114  transmits a control signal to multiple injection tools, and the control signal is formatted to change the state of only one or a subset of the multiple injection tools. For example, a shared electrical or hydraulic control line may transmit a control signal to multiple injection valves, and the control signal may be formatted to selectively change the state of only one (or a subset) of the injection valves. In some cases, the pressure, amplitude, frequency, duration, and/or other properties of the control signal determine which injection tool is modified by the control signal. In some cases, the pressure, amplitude, frequency, duration, and/or other properties of the control signal determine the state of the injection tool affected by the modification. 
     In one or more embodiments, the injection tools  116  may include one or more sensors for collecting data relating to downhole operating conditions and formation characteristics along the wellbore  102 . Such sensors may serve as real-time data sources for various types of downhole measurements and diagnostic information pertaining to each stage of the stimulation treatment. Examples of such sensors include, but are not limited to, micro-seismic sensors, tiltmeters, pressure sensors, and other types of downhole sensing equipment. The data collected downhole by such sensors may include, for example, real-time measurements and diagnostic data for monitoring the extent of fracture growth and complexity within the surrounding formation along the wellbore  102  during each stage of the stimulation treatment, e.g., corresponding to one or more sections  118 . 
     In one or more embodiments, the injection tools  116  may include fiber-optic sensors for collecting real-time measurements of acoustic intensity or thermal energy downhole during the stimulation treatment. For example, the fiber-optic sensors may be components of a distributed acoustic sensing (DAS), distributed strain sensing, and/or distributed temperature sensing (DTS) subsystems of the injection system  108 . However, it should be appreciated that embodiments are not intended to be limited thereto and that the injection tools  116  may include any of various measurement and diagnostic tools. In some implementations, the injection tools  116  may be used to inject particle tracers, e.g., tracer slugs, into the wellbore  102  for monitoring the flow distribution based on the distribution of the injected particle tracers during the treatment. For example, such tracers may have a unique temperature profile that the DTS subsystem of the injection system  108  can be used to monitor over the course of a treatment stage. 
     In one or more embodiments, the signaling subsystem  114  may be used to transmit real-time measurements and diagnostic data collected downhole by one or more of the aforementioned data sources to the injection control subsystem  111  for processing at the wellbore surface  110 . Thus, in the fiber-optics example above, the downhole data collected by the fiber-optic sensors may be transmitted to the injection control subsystem  111  via, for example, fiber optic cables included within the signaling subsystem  114 . The injection control subsystem  111  (or data processing components thereof) may use the downhole data that it receives via the signaling subsystem  114  to perform real-time fracture mapping and/or real-time fracturing pressure interpretation using any of various data analysis techniques for monitoring stress fields around hydraulic fractures. 
     In one or more embodiments, the data analysis techniques performed by the injection control subsystem  111  may include a step-down test for identifying friction due to near-wellbore tortuosity (or “tortuosity friction”) and other friction components of a total fracture entry friction along the wellbore  102 . Such friction components may affect near-wellbore pressure loss during the stimulation treatment and thus, impact the effectiveness of the treatment along the wellbore  102 . In one or more embodiments, the near-wellbore pressure loss may represent a difference between a bottom hole pressure and a bottom hole instantaneous shut-in pressure. Tortuosity friction in particular may be attributed to the path of fractures within the subsurface formation  104  relative to the wellbore&#39;s geometry. As will be described in further detail below, the friction components identified from the step-down test along with the fluid flow allocation for each cluster of fractures and a surface pressure profile obtained from surface pressure sensors may be used to calibrate a fracture model and simulate an initial treatment schedule for a main fracture stimulation treatment stage. 
     Referring now to  FIGS. 2A-2B , a flow diagram illustrates one embodiment of a method  200  for implementing the present disclosure. The method  200  enables real-time optimization of stimulation treatments in a hydrocarbon reservoir by controlling a simulated stimulation treatment schedule for a main fracture stimulation treatment stage using a predicted net pressure in a cluster of fractures representing a dominant fracture for the main fracture stimulation treatment stage. The method  200  may be performed by the injection control subsystem  111  of the well system  100  in  FIG. 1 , as described above. Accordingly, the stimulation treatment in this example may be a multistage stimulation treatment, e.g., a multistage, hydraulic fracturing treatment. Each stage of the treatment may be conducted along a portion of a wellbore path within a subsurface formation, e.g., one or more sections  118  of the wellbore  102  within subsurface formation  104  of  FIG. 1 , as described above. The subsurface formation or portion thereof may be targeted as part of a treatment plan for stimulating the production of such resources from the rock formation. Accordingly, the method  200  may be used, for example, to optimize a pre-diverter stimulation treatment schedule for a main fracture stimulation treatment stage to achieve successful bridging and diversion. 
     In step  202 , a standard step-down test is performed before the next main fracture stimulation treatment stage to measure perforation and tortuosity friction pressure losses across each cluster of fractures in a formation near a lateral wellbore caused by the step-down test. 
     In step  204 , a fluid flow allocation for each cluster of fractures and a surface pressure profile is measured during the step-down test performed in step  202  using fiber optic sensors (thermal or acoustic) in the formation near the lateral wellbore and at the surface of the main wellbore. 
     In step  206 , a fracture model is calibrated by iteratively simulating values for i) the fluid flow allocation for each cluster of fractures and the surface pressure profile; and ii) the perforation and tortuosity friction pressure losses across each cluster of fractures until a difference in their simulated values and their measured values from steps  204  and  202 , respectively, is within a predetermined margin of error. Each simulation may be performed using the formation properties, well completion information, the step-down test schedule (rates and volumes) for performing the step-down test in step  202  and techniques well known in the art. In each iteration of the simulation, the perforation efficiency for each cluster of fractures may be modified until the difference in the simulated values and measured values for i) the fluid flow allocation for each cluster of fractures and the surface pressure profile; and ii) the perforation and tortuosity friction pressure losses across each cluster of fractures is within a predetermined margin of error. A predetermined margin of error is preferably less than or equal to 10% however, may be some other predefined percentage. 
     In step  208 , an initial treatment schedule is simulated for the next main fracture stimulation treatment stage using the fracture model calibrated in step  206 , one or more parameters (e.g. injection rates; treatment fluid/proppant properties; pad stage/slurry stage volumes; proppant concentrations) and techniques well-known in the art. The initial treatment schedule may include simulated fluid flow rates and fracture widths for each respective cluster of fractures. The cluster of fractures with the greatest flow rate and/or fracture width represents a dominant fracture. 
     In step  210 , a predicted net pressure value is calculated for each cluster of fractures using one of the initial treatment schedule from step  208  and the updated treatment schedule from step  214 , and techniques well-known in the art. 
     In step  212 , the method  200  determines if the difference between the predicted net pressure value calculated in step  210  for a cluster of fractures representing a dominant fracture and a predetermined net pressure value for a cluster of fractures representing another dominant fracture is within a predetermined margin of error. A predetermined margin of error is preferably less than or equal to 10% however, may be some other predefined percentage. If the difference between the predicted net pressure value calculated in step  210  and the predetermined net pressure value is not within a predetermined margin of error, then the method  200  proceeds to step  214 . Otherwise, the method  200  proceeds to step  216 . The predetermined net pressure value for the cluster of fractures representing another dominant fracture may be determined using historical data from a successfully diverted main fracture stimulation treatment stage during a respective prior stimulation treatment. Alternatively, the predetermined net pressure value for the cluster of fractures representing another dominant fracture may be determined using an average of the historical data from multiple successfully diverted main fracture stimulation treatment stages during a respective multiple prior stimulation treatments. In either embodiment, each main fracture stimulation treatment stage, for purposes of determining the predetermined net pressure value, may be performed in the same lateral wellbore used to perform the next main fracture stimulation treatment stage or in a different lateral wellbore for the same well or a different well used to perform the next main fracture stimulation treatment stage. More particularly, the predetermined net pressure value for the cluster of fractures representing another dominant fracture may be determined by measuring a fluid flow allocation for each cluster of fractures and a surface pressure profile during the prior stimulation treatment(s) using fiber optic sensors (thermal or acoustic) in the formation near the lateral wellbore and at the surface of the corresponding main wellbore. A fracture model is then calibrated by iteratively simulating i) the fluid flow allocation for each cluster of fractures and the surface pressure profile; and ii) the perforation and tortuosity friction pressure losses across each cluster of fractures until a difference in their simulated values and their respectively measured values is within a predetermined margin of error. In each iteration of the simulation, the perforation efficiency for each cluster of fractures may be modified until the difference in the simulated values and their respectively measured values is within a predetermined margin of error. A predetermined margin of error is preferably less than or equal to 10% however, may be some other predefined percentage. Once calibrated, the fracture model simulated results may be used to determine the predetermined net pressure value for the cluster of fractures representing another dominant fracture. 
     In step  214 , the initial treatment schedule simulated in step  208  is updated by interactively modifying one or more parameters (e.g. injection rates; treatment fluid/proppant properties; pad stage/slurry stage volumes; proppant concentrations) of the initial treatment schedule using the client interface and/or the video interface described further in reference to  FIG. 3  and running another simulation for the next main fracture stimulation treatment stage using the fracture model calibrated in step  206  and techniques well-known in the art. The method  200  returns the updated treatment schedule to step  210 . Some embodiments for modifying the one or more parameters of the initial treatment schedule may include, but are not limited to: (1) decreasing the injection rate and pad stage volume if the predicted net pressure from step  210  is more than the predetermined net pressure; and (2) increasing the injection rate and pad stage volume if the predicted net pressure from step  210  is less than the predetermined net pressure. 
     In step  216 , the next main fracture stimulation treatment stage is performed on the formation near the lateral wellbore caused by the step-down test based on the last updated treatment schedule from step  214 . 
     The method  200  therefore, optimizes the pre-diverter stimulation treatment schedule for a main fracture stimulation treatment stage to achieve a desired net pressure inside the dominant fracture. By controlling the net pressure inside the dominant fracture, the width of the dominant fracture can be optimized to achieve successful bridging and diversion. 
     The present disclosure may be implemented through a computer-executable program of instructions, such as program modules, generally referred to as software applications or application programs executed by a computer. The software may include, for example, routines, programs, objects, components and data structures that perform particular tasks or implement particular abstract data types. The software forms an interface to allow a computer to react according to a source of input. A fracture model simulator software application may be used as an interface application to implement the present disclosure. The software may also cooperate with other code segments to initiate a variety of tasks in response to data received in conjunction with the source of the received data. The software may be stored and/or carried on any variety of memory such as CD-ROM, magnetic disk, bubble memory and semiconductor memory (e.g. various types of RAM or ROM). Furthermore, the software and its results may be transmitted over a variety of carrier media such as optical fiber, metallic wire and/or through any of a variety of networks, such as the Internet. 
     Moreover, those skilled in the art will appreciate that the disclosure may be practiced with a variety of computer-system configurations, including hand-held devices, multiprocessor systems, microprocessor-based or programmable-consumer electronics, minicomputers, mainframe computers, and the like. Any number of computer-systems and computer networks are acceptable for use with the present disclosure. The disclosure may be practiced in distributed-computing environments where tasks are performed by remote-processing devices that are linked through a communications network. In a distributed-computing environment, program modules may be located in both local and remote computer-storage media including memory storage devices. The present disclosure may therefore, be implemented in connection with various hardware, software or a combination thereof, in a computer system or other processing system. 
     Referring now to  FIG. 3 , a block diagram illustrates one embodiment of a system for implementing the present disclosure on a computer. The system includes a computing unit, sometimes referred to as a computing system, which contains memory, application programs, a client interface, a video interface, and a processing unit. The computing unit is only one example of a suitable computing environment and is not intended to suggest any limitation as to the scope of use or functionality of the disclosure. 
     The memory primarily stores the application programs, which may also be described as program modules containing computer-executable instructions, executed by the computing unit for implementing the present disclosure described herein and illustrated in  FIGS. 1-2 . The memory therefore, includes a stimulation treatment optimization module, which enables steps  206 - 214  described in reference to  FIGS. 2A-2B . The stimulation treatment optimization module may integrate functionality from the remaining application programs illustrated in  FIG. 3 . In particular, the fracture model simulator may be used as an interface application to perform the simulation in steps  206 - 208  and  214 . Although the fracture model simulator may be used as interface application, other interface applications may be used, instead, or the stimulation treatment optimization module may be used as a stand-alone application. 
     Although the computing unit is shown as having a generalized memory, the computing unit typically includes a variety of computer readable media. By way of example, and not limitation, computer readable media may comprise computer storage media and communication media. The computing system memory may include computer storage media in the form of volatile and/or nonvolatile memory such as a read only memory (ROM) and random access memory (RAM). A basic input/output system (BIOS), containing the basic routines that help to transfer information between elements within the computing unit, such as during start-up, is typically stored in ROM. The RAM typically contains data and/or program modules that are immediately accessible to, and/or presently being operated on, the processing unit. By way of example, and not limitation, the computing unit includes an operating system, application programs, other program modules, and program data. 
     The components shown in the memory may also be included in other removable/nonremovable, volatile/nonvolatile computer storage media or they may be implemented in the computing unit through an application program interface (“API”) or cloud computing, which may reside on a separate computing unit connected through a computer system or network. For example only, a hard disk drive may read from or write to nonremovable, nonvolatile magnetic media, a magnetic disk drive may read from or write to a removable, nonvolatile magnetic disk, and an optical disk drive may read from or write to a removable, nonvolatile optical disk such as a CD ROM or other optical media. Other removable/nonremovable, volatile/nonvolatile computer storage media that can be used in the exemplary operating environment may include, but are not limited to, magnetic tape cassettes, flash memory cards, digital versatile disks, digital video tape, solid state RAM, solid state ROM, and the like. The drives and their associated computer storage media discussed above provide storage of computer readable instructions, data structures, program modules and other data for the computing unit. 
     A client may enter commands and information into the computing unit through the client interface, which may be input devices such as a keyboard and pointing device, commonly referred to as a mouse, trackball or touch pad. Input devices may include a microphone, joystick, satellite dish, scanner, or the like. These and other input devices are often connected to the processing unit through the client interface that is coupled to a system bus, but may be connected by other interface and bus structures, such as a parallel port or a universal serial bus (USB). 
     A monitor or other type of display device may be connected to the system bus via an interface, such as a video interface. A graphical user interface (“GUI”) may also be used with the video interface to receive instructions from the client interface and transmit instructions to the processing unit. In addition to the monitor, computers may also include other peripheral output devices such as speakers and printer, which may be connected through an output peripheral interface. 
     Although many other internal components of the computing unit are not shown, those of ordinary skill in the art will appreciate that such components and their interconnection are well-known. 
     While the present disclosure has been described in connection with presently preferred embodiments, it will be understood by those skilled in the art that it is not intended to limit the disclosure to those embodiments. It is therefore, contemplated that various alternative embodiments and modifications may be made to the disclosed embodiments without departing from the spirit and scope of the disclosure defined by the appended claims and equivalents thereof.