EP4695498A1 - Systems and methods for determining real-time performance of coiled tubing cleanout operations - Google Patents

Abstract

Systems and methods presented herein facilitate improvement of coiled tubing cleanout operations (CTCOs), and generally relate to systems and methods for providing real-time diagnostics of the CTCOs. For example, an example method includes acquiring, via one or more sensors of a coiled tubing system, data relating to a CTCO performed at least partially within a wellbore of the coiled tubing system; analyzing, via a processing and control system, the acquired data to provide real-time diagnostics of downhole conditions within the wellbore during performance of the CTCO; providing, via the processing and control system, one or more outputs relating to the real-time diagnostics of the downhole conditions within the wellbore during performance of the CTCO; and adjusting, via the processing and control system, one or more operational parameters of the CTCO based at least in part on the one or more outputs.

Description

IS23.0420-WO-PCT SYSTEMS AND METHODS FOR DETERMINING REAL-TIME PERFORMANCE OF COILED TUBING CLEANOUT OPERATIONS CROSS-REFERENCE TO RELATED APPLICATION [0001] This application claims priority to and the benefit of U.S. Provisional Patent Application Serial No.63/499,784, entitled “Systems and Methods for Determining Real-Time Performance of Coiled-Tubing Cleanout Operations,” filed May 3, 2023, which is hereby incorporated by reference in its entirety for all purposes. BACKGROUND [0002] The present disclosure generally relates to systems and methods for improving performance of coiled tubing cleanout operations (CTCOs) by providing real-time diagnostics of the CTCOs. [0003] This section is intended to introduce the reader to various aspects of art that may be related to various aspects of the present techniques, which are described and/or claimed below. This discussion is believed to be helpful in providing the reader with background information to facilitate a better understanding of the various aspects of the present disclosure. Accordingly, it should be understood that these statements are to be read in this light, and not as an admission of any kind. [0004] In many well applications, coiled tubing is employed to facilitate performance of many types of downhole operations. Coiled tubing offers versatile technology due in part to its ability to pass through completion tubulars while conveying a wide array of tools downhole. A coiled tubing system may include many systems and components, including a coiled tubing reel, an injector head, a gooseneck, lifting equipment (e.g., a mast or a crane), and other supporting IS23.0420-WO-PCT equipment, such as pumps, treating irons, or other components. Coiled tubing has been utilized for performing well treatment and/or well intervention operations in existing wellbores such as hydraulic fracturing operations, matrix acidizing operations, milling operations, perforating operations, coiled tubing drilling operations, and various other types of operations. SUMMARY [0005] A summary of certain embodiments described herein is set forth below. It should be understood that these aspects are presented merely to provide the reader with a brief summary of these certain embodiments and that these aspects are not intended to limit the scope of this disclosure. [0006] Various embodiments described herein provide systems and methods for providing real-time diagnostics of downhole conditions for coiled tubing cleanout operations (CTCOs). Such techniques use data from downhole and/or surface sensors and/or other components of a coiled tubing system to automatically determine various outputs that provide real-time assessments of the CTCOs. For example, such outputs may include solids transport efficiency, bottoms up, pump-to-bottom hole assembly (BHA) fluid travel time, and reservoir inflow and leakoff. It should be understood that the aforementioned outputs are merely illustrative, and that other outputs may be generated based on the data. [0007] Certain embodiments of the present disclosure include a method that includes acquiring, via one or more sensors of a coiled tubing system, data relating to a CTCO performed at least partially within a wellbore of the coiled tubing system. The method also includes analyzing, via a processing and control system, the acquired data to provide real-time diagnostics of downhole conditions within the wellbore during performance of the CTCO. The method IS23.0420-WO-PCT further includes providing, via the processing and control system, one or more outputs relating to the real-time diagnostics of the downhole conditions within the wellbore during performance of the CTCO. In addition, the method includes adjusting, via the processing and control system, one or more operational parameters of the CTCO based at least in part on the one or more outputs. [0008] Various refinements of the features noted above may be undertaken in relation to various aspects of the present disclosure. Further features may also be incorporated in these various aspects as well. These refinements and additional features may exist individually or in any combination. For instance, various features discussed below in relation to one or more of the illustrated embodiments may be incorporated into any of the above-described aspects of the present disclosure alone or in any combination. The brief summary presented above is intended to familiarize the reader with certain aspects and contexts of embodiments of the present disclosure without limitation to the claimed subject matter. BRIEF DESCRIPTION OF THE DRAWINGS [0009] Various aspects of this disclosure may be better understood upon reading the following detailed description and upon reference to the drawings, in which: [0010] FIG.1 illustrates a schematic diagram of an example coiled tubing system, in accordance with embodiments of the present disclosure; [0011] FIG.2 illustrates a well control system including a surface processing system to control the coiled tubing system of FIG.1, in accordance with embodiments of the present disclosure; IS23.0420-WO-PCT [0012] FIG.3 illustrates various example graphs, metrics, or other indicators that may be generated during a coiled tubing cleanout operation (CTCO), which may be generated by the surface processing system of FIG.1, in accordance with embodiments of the present disclosure; [0013] FIG.4 illustrates another example coiled tubing system for performing a CTCO, in accordance with embodiments of the present disclosure; [0014] FIG.5 illustrates an example workflow of various types of input data that may be used by the surface processing system of FIG.1 to generate various types of output data associated with a CTCO to provide a real-time diagnostic or assessment of the CTCO, in accordance with embodiments of the present disclosure; [0015] FIGS.6A through 6E illustrate closer views of the various sections of the workflow illustrated in FIG.5, in accordance with embodiments of the present disclosure; [0016] FIG.7 illustrates a real-time graph showing estimations of fluid inflow, which may be generated by the surface processing system of FIG.1, in accordance with embodiments of the present disclosure; [0017] FIG.8 illustrates a real-time graph showing estimations of reservoir fluid inflow, which may be generated by the surface processing system of FIG.1, in accordance with embodiments of the present disclosure; [0018] FIG.9 illustrates an example graphical display for showing all times and all depths, which may be generated by the surface processing system of FIG.1, in accordance with embodiments of the present disclosure; and [0019] FIG.10 illustrates a workflow of a method for providing real-time diagnostics using the surface processing system of FIG.1, in accordance with embodiments of the present disclosure. IS23.0420-WO-PCT DETAILED DESCRIPTION [0020] One or more specific embodiments of the present disclosure will be described below. These described embodiments are only examples of the presently disclosed techniques. Additionally, in an effort to provide a concise description of these embodiments, all features of an actual implementation may not be described in the specification. It should be appreciated that in the development of any such actual implementation, as in any engineering or design project, numerous implementation-specific decisions must be made to achieve the developers’ specific goals, such as compliance with system-related and business-related constraints, which may vary from one implementation to another. Moreover, it should be appreciated that such a development effort might be complex and time consuming, but would nevertheless be a routine undertaking of design, fabrication, and manufacture for those of ordinary skill having the benefit of this disclosure. [0021] When introducing elements of various embodiments of the present disclosure, the articles “a,” “an,” and “the” are intended to mean that there are one or more of the elements. The terms “comprising,” “including,” and “having” are intended to be inclusive and mean that there may be additional elements other than the listed elements. Additionally, it should be understood that references to “one embodiment” or “an embodiment” of the present disclosure are not intended to be interpreted as excluding the existence of additional embodiments that also incorporate the recited features. [0022] As used herein, the terms “connect,” “connection,” “connected,” “in connection with,” and “connecting” are used to mean “in direct connection with” or “in connection with via one or more elements”; and the term “set” is used to mean “one element” or “more than one element.” Further, the terms “couple,” “coupling,” “coupled,” “coupled together,” and “coupled IS23.0420-WO-PCT with” are used to mean “directly coupled together” or “coupled together via one or more elements.” As used herein, the terms “up” and “down,” “uphole” and “downhole”, “upper” and “lower,” “top” and “bottom,” and other like terms indicating relative positions to a given point or element are utilized to more clearly describe some elements. Commonly, these terms relate to a reference point as the surface from which drilling operations are initiated as being the top (e.g., uphole or upper) point and the total depth along the drilling axis being the lowest (e.g., downhole or lower) point, whether the well (e.g., wellbore, borehole) is vertical, horizontal or slanted relative to the surface. [0023] In addition, as used herein, the terms “real time”, ”real-time”, or “substantially real time” may be used interchangeably and are intended to describe operations (e.g., computing operations) that are performed without any human-perceivable interruption between operations. For example, as used herein, data relating to the systems described herein may be collected, transmitted, and/or used in control computations in “substantially real time” such that data readings, data transfers, and/or data processing steps occur once every second, once every 0.1 second, once every 0.01 second, or even more frequent, during operations of the systems (e.g., while the systems are operating). In addition, as used herein, the terms “automatic” and “automated” are intended to describe operations that are performed or are caused to be performed, for example, by a processing and control system (i.e., solely by the processing and control system, without human intervention). In addition, as used herein, the term “approximately equal to” may be used to mean values that are relatively close to each other (e.g., within 5%, within 2%, within 1%, within 0.5 %, or even closer, of each other). [0024] As mentioned above, coiled tubing cleanout operations (CTCO) generally include injecting fluids (e.g., including injection water, oil, and gas) to transport solids present in a IS23.0420-WO-PCT wellbore from downhole locations where they have deposited, during the production life of a well, to surface. During CTCOs, coiled tubing operators must ensure in substantially real-time that certain job performance criteria and operational constraints are met. The problem solved by the embodiments described herein is the difficulty operators face when trying to assess certain relatively important CTCO check points in substantially real-time, including, but not limited to the following Check Points 1-4, which are described in greater detail herein: 1. That the amount of fluid leak-off into the reservoir is minimized to prevent formation damage; 2. That the amount of fluid inflow from the reservoir is under control to prevent surface fluid handling limitations; 3. That the solids to be removed from, and present in, the wellbore are being transported efficiently toward the surface with the injected fluids; and 4. That operating conditions such as pump rates, choke settings, CT depth may be adjusted to optimize the CTCO efficiency when required. [0025] The embodiments described herein provide systems and methods for providing real- time diagnostics of downhole conditions for CTCOs. Such techniques use data from downhole and/or surface sensors and/or other components of a coiled tubing system to automatically determine various outputs that provide real-time assessments of the CTCOs. For example, such outputs may include solids transport efficiency, bottoms up, pump-to-bottom hole assembly (BHA) fluid travel time, and reservoir inflow and leakoff. It should be understood that the aforementioned outputs are merely illustrative, and that other outputs may be generated based on the data. IS23.0420-WO-PCT [0026] With the foregoing in mind, FIG.1 illustrates a schematic diagram of an example coiled tubing system 10. As illustrated, in certain embodiments, a coiled tubing string 12 may be run into a wellbore 14 that traverses a hydrocarbon-bearing formation 16 (i.e., reservoir). While certain elements of the coiled tubing system 10 are illustrated in FIG.1, other elements of the coiled tubing system 10 (e.g., blow-out preventers, wellhead “tree”, etc.) may be omitted for clarity of illustration. In certain embodiments, the coiled tubing system 10 includes an interconnection of pipes, including vertical and/or horizontal casings 18, coiled tubing 20, and so forth, that connect to a surface facility 22 at the surface 24 of the coiled tubing system 10. In certain embodiments, the coiled tubing 20 extends inside the casing 18 and terminates at a tubing head (not shown) at or near the surface 24. In addition, in certain embodiments, the casing 18 contacts the wellbore 14 and terminates at a casing head (not shown) at or near the surface 24. [0027] In certain embodiments, a BHA 26 may be run inside the casing 18 by the coiled tubing 20. As illustrated in FIG.1, in certain embodiments, the BHA 26 may include a downhole motor 28 that operates to rotate a drill bit 30 (e.g., during drilling operations) or other downhole tools. In certain embodiments, the downhole motor 28 may be driven by hydraulic forces carried in fluid supplied from the surface 24 of the coiled tubing system 10. In certain embodiments, the BHA 26 may be connected to the coiled tubing 20, which is used to run the BHA 26 to a desired location within the wellbore 14. It is also contemplated that, in certain embodiments, the rotary motion of the drill bit 30 may be driven by rotation of the coiled tubing 20 effectuated by a rotary table or other surface-located rotary actuator. In such embodiments, the downhole motor 28 may be omitted. [0028] In certain embodiments, the coiled tubing 20 may also be used to deliver fluid 32 to the drill bit 30 through an interior of the coiled tubing 20 to aid in the drilling process and carry IS23.0420-WO-PCT cuttings and possibly other fluid or solid components in return fluid 34 that flows up the annulus between the coiled tubing 20 and the casing 18 (or via a return flow path provided by the coiled tubing 20, in certain embodiments) for return to the surface facility 22. It is also contemplated that the return fluid 34 may include remnant proppant (e.g., sand) or possibly rock fragments that result from a hydraulic fracturing application, and flow within the coiled tubing system 10. Under certain conditions, fracturing fluid and possibly hydrocarbons (oil and/or gas), proppants and possibly rock fragments may flow from the fractured formation 16 through perforations in a newly opened interval and back to the surface 24 of the coiled tubing system 10 as part of the return fluid 34. In certain embodiments, the BHA 26 may be supplemented behind a rotary drill by an isolation device such as, for example, an inflatable packer that may be activated to isolate the zone below or above it and enable local pressure tests. [0029] As such, in certain embodiments, the coiled tubing system 10 may include a downhole well tool 36 that is moved along the wellbore 14 via the coiled tubing 20. In certain embodiments, the downhole well tool 36 may include a variety of drilling/cutting tools coupled with the coiled tubing 20 to provide a coiled tubing string 12. In the illustrated embodiment, the downhole well tool 36 includes the drill bit 30, which may be powered by the downhole motor 28 (e.g., a positive displacement motor (PDM), or other hydraulic motor) of the BHA 26. In certain embodiments, the wellbore 14 may be an open wellbore or a cased wellbore defined by the casing 18. In addition, in certain embodiments, the wellbore 14 may be vertical or horizontal or inclined. It should be noted that the downhole well tool 36 may be part of various types of BHAs 26 coupled to the coiled tubing 20. [0030] As also illustrated in FIG.1, in certain embodiments, the coiled tubing system 10 may include a downhole sensor package 38 having multiple downhole sensors 40. In certain IS23.0420-WO-PCT embodiments, the sensor package 38 may be mounted along the coiled tubing string 12, although certain downhole sensors 40 may be positioned at other downhole locations in other embodiments. In addition, in certain embodiments, downhole sensors 40 disposed on the coiled tubing 20 may be configured to detect downhole flow rates, downhole temperatures, and downhole pressures, and so forth, in the wellbore 14. In addition, in certain embodiments, downhole sensors 40 disposed on the casing 18 may be configured to detect downhole temperatures, and downhole pressures, and so forth, in the wellbore 14. [0031] In certain embodiments, data from the downhole sensors 40 may be relayed uphole to a surface processing system 42 (e.g., a computer-based processing and control system) disposed at the surface 24 and/or other suitable location of the coiled tubing system 10. In certain embodiments, the data may be relayed uphole in substantially real time (e.g., relayed while it is detected by the downhole sensors 40 during operation of the downhole well tool 36) via a wired or wireless telemetric control line 44, and this real-time data may be referred to as edge data. In certain embodiments, the telemetric control line 44 may be in the form of an electrical line, fiber- optic line, or other suitable control line for transmitting data signals. In certain embodiments, the telemetric control line 44 may be routed along an interior of the coiled tubing 20, within a wall of the coiled tubing 20, or along an exterior of the coiled tubing 20. In addition, as described in greater detail herein, additional data (e.g., surface data) may be supplied by surface sensors 46 and/or stored in a memory location 48. By way of example, historical data and other useful data may be stored in the memory location 48 such as a cloud storage 50. [0032] As illustrated, in certain embodiments, the coiled tubing 20 may be deployed by a coiled tubing unit 52 and delivered downhole via an injector head 54. In certain embodiments, the injector head 54 may be controlled to slack off or pick up the coiled tubing 20 so as to control IS23.0420-WO-PCT the tubing string weight and, thus, the weight on bit (WOB) or torque acting on the drill bit 30 (or the downhole well tool 36). In certain embodiments, the downhole well tool 36 may be moved along the wellbore 14 via the coiled tubing 20 under control of the injector head 54 so as to apply a desired tubing weight and, thus, to achieve a desired rate of penetration (ROP) as the drill bit 30 is operated. Depending on the specifics of a given application, various types of data may be collected downhole, and transmitted to the surface processing system 42 in substantially real time to facilitate improved operation of the downhole well tool 36. For example, the data may be used to fully or partially automate downhole operations, to optimize the downhole operations, and/or to provide more accurate predictions regarding components or aspects of the downhole operations. [0033] In certain embodiments, fluid 32 may be delivered downhole under pressure from a pump unit 56. In certain embodiments, the fluid 32 may be delivered by the pump unit 56 through the downhole hydraulic motor 28 to power the downhole hydraulic motor 28 and, thus, the drill bit 30. In certain embodiments, the return fluid 34 is returned uphole, and this flow back of the return fluid 34 is controlled by suitable flowback equipment 58. In certain embodiments, the flowback equipment 58 may include chokes and other components/equipment used to control flow back of the return fluid 34 in a variety of applications, including well treatment applications. [0034] As described in greater detail herein, the coiled tubing unit 52, the injector head 54, the pump unit 56, and the flowback equipment 58 may include advanced surface sensors 46, actuators, and local controllers, such as PLCs, which may cooperate together to provide sensor data to, receive control signals from, and generate local control signals based on communications with, respectively, the surface processing system 42. In certain embodiments, as described in IS23.0420-WO-PCT greater detail herein, the surface sensors 46 may include flow rate, pressure, and fluid rheology sensors 46, among other types of sensors. In addition, as described in greater detail herein, the actuators may include actuators for pump and choke control of the pump unit 56 and the flowback equipment 58, respectively, among other types of actuators. [0035] In certain embodiments, surface sensors 46 of the coiled tubing unit 52 may be configured to detect positions of the coiled tubing 20, weights of the coiled tubing 20, and so forth. In addition, in certain embodiments, surface sensors 46 of the injector head 54 may be configured to detect wellhead pressure, and so forth. In addition, in certain embodiments, surface sensors 46 of the pump unit 56 may be configured to detect pump pressures, pump flow rates, and so forth. In addition, in certain embodiments, surface sensors 46 of the flowback equipment 58 may be configured to detect fluids production rates, solids production rates, and so forth. [0036] FIG.2 illustrates a well control system 60 that may include the surface processing system 42 to control the coiled tubing system 10 described herein. In certain embodiments, the surface processing system 42 may include one or more analysis modules 62 (e.g., a program of computer-executable instructions and associated data) that may be configured to perform various functions of the embodiments described herein. In certain embodiments, to perform these various functions, the one or more analysis modules 62 may execute on one or more processors 64 of the surface processing system 42, which may be connected to one or more storage media 66 of the surface processing system 42. Indeed, in certain embodiments, the one or more analysis modules 62 may be stored in the one or more storage media 66. [0037] In certain embodiments, the computer-executable instructions of the one or more analysis modules 62, when executed by the one or more processors 64, may cause the one or IS23.0420-WO-PCT more processors 64 to generate one or more models. Such models may be used by the surface processing system 42 to predict values of operational parameters that may or may not be measured (e.g., using gauges, sensors) during well operations. [0038] In certain embodiments, the one or more processors 64 may include a microprocessor, a microcontroller, a processor module or subsystem, a programmable integrated circuit, a programmable gate array, a digital signal processor (DSP), or another control or computing device. In certain embodiments, the one or more processors 64 may include machine learning and/or artificial intelligence (AI) based processors. In certain embodiments, the one or more storage media 66 may be implemented as one or more non-transitory computer-readable or machine-readable storage media. In certain embodiments, the one or more storage media 66 may include one or more different forms of memory including semiconductor memory devices such as dynamic or static random access memories (DRAMs or SRAMs), erasable and programmable read-only memories (EPROMs), electrically erasable and programmable read-only memories (EEPROMs) and flash memories; magnetic disks such as fixed, floppy and removable disks; other magnetic media including tape; optical media such as compact disks (CDs) or digital video disks (DVDs); or other types of storage devices. Note that the computer-executable instructions and associated data of the analysis module(s) 62 may be provided on one computer-readable or machine-readable storage medium of the storage media 66, or alternatively, may be provided on multiple computer-readable or machine-readable storage media distributed in a large system having possibly plural nodes. Such computer-readable or machine-readable storage medium or media are considered to be part of an article (or article of manufacture), which may refer to any manufactured single component or multiple components. In certain embodiments, the one or more storage media 66 may be located either in the machine running the machine-readable IS23.0420-WO-PCT instructions, or may be located at a remote site from which machine-readable instructions may be downloaded over a network for execution. [0039] In certain embodiments, the processor(s) 64 may be connected to a network interface 68 of the surface processing system 42 to allow the surface processing system 42 to communicate with the multiple downhole sensors 40 and surface sensors 46 described herein, as well as communicate with the actuators 70 and/or PLCs 72 of the surface equipment 74 (e.g., the coiled tubing unit 52, the pump unit 56, the flowback equipment 58, and so forth) and of the downhole equipment 76 (e.g., the BHA 26, the downhole motor 28, the drill bit 30, the downhole well tool 36, and so forth) for the purpose of controlling operation of the coiled tubing system 10, as described in greater detail herein. In certain embodiments, the network interface 68 may also facilitate the surface processing system 42 to communicate data to the cloud storage 50 (or other wired and/or wireless communication network) to, for example, archive the data or to enable external computing systems 78 to access the data and/or to remotely interact with the surface processing system 42. [0040] It should be appreciated that the well control system 60 illustrated in FIG.2 is only one example of a well control system, and that the well control system 60 may have more or fewer components than shown, may combine additional components not depicted in the embodiment of FIG.2, and/or the well control system 60 may have a different configuration or arrangement of the components depicted in FIG.2. In addition, the various components illustrated in FIG.2 may be implemented in hardware, software, or a combination of both hardware and software, including one or more signal processing and/or application specific integrated circuits. Furthermore, the operations of the well control system 60 as described herein may be implemented by running one or more functional modules in an information processing IS23.0420-WO-PCT apparatus such as application specific chips, such as application-specific integrated circuits (ASICs), field-programmable gate arrays (FPGAs), programmable logic devices (PLDs), systems on a chip (SOCs), or other appropriate devices. These modules, combinations of these modules, and/or their combination with hardware are all included within the scope of the embodiments described herein. [0041] As described in greater detail herein, the embodiments described herein facilitate the operation of well-related tools. For example, a variety of data (e.g., downhole data and surface data) may be collected to enable optimization of operations of well-related tools such as the downhole well tool 36 illustrated in FIG.1 by the surface processing system 42 illustrated in FIG.2 (or other suitable processing systems). In certain embodiments, the data may be provided as advisory data by the surface processing system 42 (or other suitable processing systems). However, in other embodiments, the data may be used to facilitate automation of downhole processes and/or surface processes (i.e., the processes may be automated without human intervention), as described in greater detail herein, by the surface processing system 42 (or other suitable processing system). The embodiments described herein may enhance downhole operations by improving the efficiency and utilization of data to enable performance optimization and improved resource controls. [0042] As described in greater detail herein, in certain embodiments, downhole parameters may be obtained via, for example, downhole sensors 40 while the downhole well tool 36 is disposed within the wellbore 14. In certain embodiments, the downhole parameters may be obtained in substantially real time and sent to the surface processing system 42 via wired or wireless telemetry. In certain embodiments, downhole parameters may be combined with surface parameters by the surface processing system 42. In certain embodiments, the downhole IS23.0420-WO-PCT and surface parameters may be processed by the surface processing system 42 during use of the downhole well tool 36 to enable automatic (e.g., without human intervention) optimization with respect to use of the downhole well tool 36 during subsequent stages of operation of the downhole well tool 36. [0043] Non-limiting examples of downhole parameters that may be sensed in substantially real time include, but are not limited to, weight on bit (WOB), torque acting on the downhole well tool 36, downhole pressures, downhole differential pressures, downhole temperatures, downhole fluid velocities and fluid direction, and other desired downhole parameters. In certain embodiments, downhole parameters may be used by the surface processing system 42 in combination with surface parameters, and such surface parameters may include, but are not limited to, pump-related parameters (e.g., pump rate and circulating pressures of the pump unit 56). In certain embodiments, the surface parameters also may include parameters related to fluid returns (e.g., wellhead pressure, return fluid flow rate, choke settings, amount of proppant returned, and other desired surface parameters). In certain embodiments, the surface parameters also may include data from the coiled tubing unit 52 (e.g., surface weight of the coiled tubing string 12, speed of the coiled tubing 20, rate of penetration, and other desired parameters). In certain embodiments, the surface data that may be processed by the surface processing system 42 to optimize performance also may include previously recorded data such as fracturing data (e.g., close-in pressures from each fracturing stage, proppant data, friction data, fluid volume data, and other desired data). [0044] In certain embodiments, use of the downhole data and surface data enables the surface processing system 42 to self-learn (e.g., modeling or simulation using the machine learning or artificial intelligence (AI) based processors, machine learning or AI based algorithms IS23.0420-WO-PCT stored in the one or more storage media 66, or combinations thereof). This real-time modeling by the surface processing system 42, based on the downhole and surface parameters, enables improved downhole operations. Such modeling by the surface processing system 42 also enables the downhole process to be automated and automatically optimized by the surface processing system 42. For instance, the modeling based on the downhole parameters may be used by the surface processing system 42 to predict wear on the downhole motor 28 and/or the drill bit 30, and to advise as to timing of the next trip to the surface 24 for replacement of the downhole motor 28 and/or the drill bit 30. [0045] In certain embodiments, the modeling based on the downhole parameters also enable use of pressures to be used by the surface processing system 42 in characterizing the formation 16. Such real-time downhole parameters also enable use of pressures by the surface processing system 42 for in situ evaluation and advisory of post-fracturing flow back parameters, and for creating an optimum flow back schedule for maximized production of, for example, hydrocarbon fluids from the surrounding formation 16. Data available from a given well may be utilized in designing the next fracturing schedule for the same pad/neighbor wells as well as predictions regarding subsequent wells. [0046] For example, downhole data such as WOB, torque data from a load module associated with the downhole well tool 36, and bottom hole pressures (internal and external to the bottom hole assembly 26/downhole well tool 36) may be processed via the surface processing system 42. The processed data may then be utilized by the surface processing system 42 to control the injector head 54 to generate, for example, a faster and more controlled rate of penetration (ROP). Additionally, the processed data may be updated by the surface processing system 42 as the downhole well tool 36 is moved to different positions along the wellbore 14 to IS23.0420-WO-PCT help optimize operations. The processed data also enables automation of the downhole process through automated controls over the injector head 54 via control instructions provided by the surface processing system 42. [0047] In certain embodiments, data from downhole may be combined by the surface processing system 42 with surface data received from injector head 54 and/or other measured or stored surface data. By way of example, surface data may include hanging weight of the coiled tubing string 12, speed of the coiled tubing 20, wellhead pressure, choke and flow back pressures, return pump rates, circulating pressures (e.g., circulating pressures from the manifold of a coiled tubing reel in the coiled tubing unit 52), and pump rates. The surface data may be combined with the downhole data by the surface processing system 42 in real time to provide an automated system that self-controls the injector head 54. For example, the injector head 54 may be automatically controlled (e.g., without human intervention) to optimize ROP under direction from the surface processing system 42. [0048] In certain embodiments, data from drilling parameters (e.g., surveys and pressures) as well as fracturing parameters (e.g., volumes and pressures) may be combined with real-time data obtained from sensors 40, 46. The combined data may be used by the surface processing system 42 in a manner that aids in machine learning and/or artificial intelligence to automate subsequent jobs in the same well and/or for neighboring wells. The accurate combination of data and the updating of that data in real time helps the surface processing system 42 improve the automatic performance of subsequent tasks. [0049] As mentioned above, various embodiments described herein provide systems and methods for providing real-time diagnostics of downhole conditions for CTCOs. Such techniques use data from downhole and/or surface sensors and/or other components of a coiled IS23.0420-WO-PCT tubing system to automatically determine various outputs that provide real-time assessments of the CTCOs. For example, such outputs may include solids transport efficiency, bottoms up, pump-to-BHA fluid travel time, and reservoir inflow and leakoff. It should be understood that the aforementioned outputs are merely illustrative, and that other outputs may be generated based on the data. [0050] FIG.3 illustrates various example graphs, metrics, or other indicators that may be generated during a CTCO, which may be generated by the surface processing system 42, as described in greater detail herein. For example, in certain embodiments, the system and methods described herein may generate a graph 80 that illustrates one or more pump rates (e.g., from the pump unit 56 illustrated in FIG.1) associated with a CTCO, a graph 82 that illustrates losses or reservoir leakoff, or a graph 84 that illustrates gains or reservoir inflow, or a combination thereof. In addition, in certain embodiments, the systems and methods described herein may generate a graph 86 that illustrates annular rates associated with a CTCO. For example, a first curve 88 may illustrate a minimum rate for the cleanout operation, and a second curve 90 may illustrate an actual rate of the cleanout operation. In addition, in certain embodiments, the systems and methods and methods described herein may generate a graph 92 that illustrates cleanout efficiency of a CTCO. In addition, in certain embodiments, the systems and methods and methods described herein may generate metrics that indicate a bottoms up rate 94 associated with a flowmeter, a bottoms up rate 96 associated with a pump (e.g., the pump unit 56 illustrated in FIG.1), a bottoms up rate 98 associated with a BHA 26 (e.g., as illustrated in FIG.1), or the like, or a combination thereof. [0051] In general, full real-time resolution of coiled tubing operations is relatively costly. However, certain modeling principles may be used to aid such analysis. For example, real-time IS23.0420-WO-PCT mass balances relating to volume rates of fluids injected at the surface 24 and the pumps may be assumed. In addition, real-time volume rates of fluids along the coiled tubing annulus may be estimated using pressure, volume, and temperature (PVT) values and the volume rates of fluids injected at the surface 24. In addition, it may be assumed that injection rates are relatively stable over relatively long periods of time. In addition, it may further be assumed that, after a few bottom ups, averaged real-time results should converge and be indicative of current conditions. [0052] FIG.4 illustrates another example coiled tubing system 10 for performing a CTCO. As illustrated in FIG.4, the coiled tubing system 10 may include various components, such as one or more downhole pressure sensors (DHPs) 40A, one or more downhole temperature sensors (DHTs) 40B, a flowmeter (Vx) 46A, one or more pump sensors 46B, and one or more drill sensors (WHTs) 46C. The sensors may provide a pump rate associated with the CTCO, a pressure associated with the CTCO, a depth of the coiled tubing associated with the CTCO, or the like, or a combination thereof. [0053] Various sources of data may be used, for example, by the surface processing system 42 illustrated in FIG.2, to determine the various outputs that provide real-time assessments of the CTCOs, as described in greater detail herein. For example, in certain embodiments, hole survey data, completion diagram data, coiled tubing string data, nitrogen PVT data (if nitrogen is used), data relating to baseoil (i.e., the oil that is used for cleaning out the well), seawater (i.e., the water that is used for cleaning out the well), or any other water-based or oil-based liquid, may be used by the surface processing system 42. In addition, in certain embodiments, data that is relatively more difficult to obtain, such as solids density and particle size, hydrocarbon PVT or molar composition, and so forth, may be used by the surface processing system 42. In certain embodiments, PVT data from lookup tables generated using hydrocarbon molar compositions, as IS23.0420-WO-PCT well as mappings of flow data from lookup tables generated using hole survey data, completions data, expected ranges of viscosities and densities, and so forth, may be used by the surface processing system 42. [0054] FIG.5 illustrates an example workflow 100 of various types of input data that may be used by the surface processing system 42 as described herein to generate various types of output data associated with a CTCO to provide a real-time diagnostic or assessment of the CTCO. In addition, FIGS.6A through 6E illustrate closer views of the various sections of the workflow 100 illustrated in FIG.5. In particular, FIGS.6A through 6C illustrate methods to determine production rates of all injected fluids and reservoir fluids at standard conditions as well as the leak-off rate of injected fluid at reference conditions, and FIGS.6D and 6E illustrate how the rates determined in FIGS.6A through 6C may be used to determine annular volume rates at all times and at all measure depths, and compare them with the minimum flowrate required to transport solids, as determined by a solids transport model 102. [0055] As illustrated in FIG.6A, using pump flow sensors S_IX_inject_rate, the volume rate ^^^^ _^ ^{^} ^^{^} ^^{^} ^^{^} ^_^^^ of all injected fluids at pump conditions is known. Using pump pressure ^^^^ _^ ^{^} ^^{^} ^^{^} ^^{^} ^_^^^ from sensors S_IX_inject_pressure and temperature ^^^^ _^ ^{^} ^^{^} ^^{^} ^^{^} ^_^^^ from sensors S_IX_inject_temperature, the mass rate of all injected fluid may be determined using PVT data 104. Finally, from the mass rates ^^^^ _^ ^{^} ^^{^^} ^^{^} ^ _^^^^ and using PVT data 104, the volume rate ^^^^ _^ ^{^} ^^{^} ^^{^} ^^{^} ^_^^^� ^^^^ _^ ^{^^} ^^{^^} ^_^ , ^^^^ _^ ^{^} ^^{^^} ^^{^} ^� may be converted to surface production conditions ^^^^ ^{^^^^}� ^^^^ ^{^^^^}, ^^^^ ^{^^^^}� us ^{^^^^} ^_{^^^ ^^^^ ^^^^ ^^^^} ing the surface production pressure ^^^^ _^^^^ from the surface production pressure sensors S_IX_prod_pressure and the surface production temperature ^^^^ ^{^^^^} ^_^^^ from the surface production sensors S_IX_prod_temperature. In parallel, using production flow sensors S_IX_prod_rate, the volume rate ^^^^ ^{^^^^} ^_{^^^ ^^^^} of all produced fluid phases (gas, oil and water) at pump IS23.0420-WO-PCT conditions is known. As used herein, X is intended to denote either G for gas, O for oil, or W for water. [0056] As illustrated in FIG.6B, by comparing ^^^^ ^{^^^^ ^^^^} ^_{^^^ ^^^^} with ^^^^ _{^^^^ ^^^^} at surface production conditions � ^^^^ ^{^^^^ ^^^^ ^^^^} ^_^^^, ^^^^ _^^^^�, the surface production volume rate ^^^^ _{^^^^ ^^^^} of all reservoir fluids at surface production � ^^^^ ^{^^^^}, ^^^^ ^{^^^^}� may be determined. Then, by comparing ^^^^ ^{^^^^ ^^^^} _{^^^^ ^^^^ ^^^^ ^^^^} with ^^^^ _{^^^^ ^^^^} at surface production the surface production volume rate ^^^^ ^{^^^^} ^_{^^^ ^^^^} of all injected fluids at surface production conditions� ^^^^ ^{^^^^ ^^^^ ^^^^ ^^^^} ^_^^^, ^^^^ _^^^^� may be determined. Finally, by comparing ^^^^ _{^^^^ ^^^^} with ^^^^ _{^^^^ ^^^^} at surface production conditions� ^^^^ ^{^^^^ ^^^^ ^^^^} ^_^^^, ^^^^ _^^^^�, the leak-off volume rate ^^^^ _{^^^^ ^^^^} of all injected fluids at surface production conditions� ^^^^ ^{^^^^ ^^^^} ^_^^^, ^^^^ _^^^^� may be determined. [0057] As illustrated in FIG.6C, using PVT data 104, all rates determined in FIG.6B may be converted to any reference pressure and reference temperature conditions. [0058] As illustrated in FIG.6D, using PVT data 104, volume rates ^^^^ ^{^^^^ ^^^^} ^_{^^^ ^^^^} and ^^^^ _{^^^^ ^^^^} know at reference conditions� ^^^^ , ^^^^ � may b ^{^^^^ ^^^^} ^_{^^^ ^^^^ ^^^^ ^^^^ ^^^^ ^^^^} e converted to mass rates ^^^^ _{^^^^ ^^^^} and ^^^^ _{^^^^ ^^^^} , respectively. For a given set of and temperature condition ( ^^^^, ^^^^) at a time ^^^^ and a measured depth ^^^^ ^^^^, using PVT data 104, the volume rates ^^^^ ^{^^^^} ^_{^^^ ^^^^} and ^^^^ ^{^^^^} ^_{^^^ ^^^^} may be determined at these ( ^^^^, ^^^^) conditions. The total volume rate ^^^^ , the sum of all ^^^ ^{^^^^ ^^^^} ^_{^^^ ^^^^ ^^^^ ^^^^ ^^^^} ^ _{^^^^ ^^^^} and ^^^^ _{^^^^ ^^^^} may therefore be determined at time ^^^^ and a measured depth ^^^^ ^^^^. [0059] As illustrated in FIG.6E, at a given measured depth ^^^^ ^^^^, a solids transport model 102 may be used to determine what the minimum volume rate ^^^^ _{^^^^ ^^^^ ^^^^} should be to ensure efficient solids transport and compare it with ^^^^ _{^^^^ ^^^^ ^^^^ ^^^^ ^^^^}. IS23.0420-WO-PCT [0060] The methodology described herein combines the use of: • Dynamic data from downhole sensors 40 acquired in substantially real-time, including pressure and temperature; • Dynamic data from surface sensors 46 acquired in substantially real-time, including pressure, temperature, pump rates, and production rates; • Dynamic data from coiled tubing hardware, including sensors providing coiled tubing depth data; • Static data describing geometries of the wellbore 14 and the coiled tubing 20, properties of the fluids and solids, and so forth; and • Interpretation models described herein and running in substantially real-time using the dynamic and static data; [0061] to provide coiled tubing operators with real-time diagnostics on the various check points, such as the four Check Points described herein. The sensors 40, 46 used by the surface processing system 42 described herein include (e.g., where X denotes fluid type with X = W, O, or G for water, oil, or gas, respectively): • Surface Sensors 40 o S_CT_depth: A sensor that determines the Measured Depth (MD) at which the bottom (e.g., downhole) end of the coiled tubing string 12 is located in the wellbore 14; o S_IX_inject_rate: A sensor that determines the injection rate of fluid X at the surface 24; o S_IX_inject_pressure: A sensor that determines the pressure of fluid X at pump X at the surface 24; IS23.0420-WO-PCT o S_IX_inject_temperature: A sensor that determines the temperature of fluid X at pump X at the surface 24; o S_TX_prod_rate: A sensor that determines the production rate of fluid X at a surface production line; o S_TX_prod_pressure: A sensor that determines the pressure of fluid X at a surface production line; o S_TX_prod_temperature: A sensor that determines the temperature of fluid X at a surface production line; o S_WH_pressure: A sensor that determines the pressure of fluid X at the wellhead (e.g., the injector head 54 illustrated in FIG.1); and o S_WH_temperature: A sensor that determines the temperature of fluid X at the wellhead. • Downhole sensors 46 o S_DH_pressure: A sensor that determines downhole wellbore pressure near the bottom (e.g., downhole) end of the coiled tubing string 12; and o S_DH_temperature: A sensor that determines downhole wellbore temperature near the bottom (e.g., downhole) end of the coiled tubing string 12. Methods for Estimating Check Points 1 and 2 [0062] As used herein, RY denotes reservoir fluid type Y with Y = W, O, or G for reservoir water, oil, or gas, respectively; IY denotes Injected fluid type with Y = W, O, or G for injected water, oil, or gas, respectively; and TY denotes all fluids (injected and reservoir) type Y with Y = IS23.0420-WO-PCT W, O, or G for injected and reservoir water, oil, or gas, respectively. In addition, the following notations are used herein: • For fluid X = RG, RO, RW, IG, IO, IW, TG, TO, TW: o ^^^^ ^{^^^^} ^_^^^ : the mass rate of fluid X being produced at the surface 24 o ^^^^ ^{^^^^} ^_^^^ : the volume rate of fluid X being produced at the surface 24; for X=TG, TO or TG, this is given by S_X_prod_rate o ^^^^ ^{^^^^} ^_^^^ : the pressure at which fluid X l is being produced at a surface production line, given by S_X_prod_pressure o ^^^^ ^{^^^^} ^_^^^ : the temperature at which fluid X l is being produced at a surface production line, given by S_X_prod_temperature • For fluid X = IG, IO, IW: o ^^^^ _^ ^{^^} ^^{^^} ^_^ : the mass rate of fluid X being injected at the surface 24 o ^^^^ _^ ^{^} ^^{^^} ^^{^} ^ : the volume rate of fluid X being injected at the surface 24, given by S_X_inject_rate o ^^^^ _^ ^{^^} ^^{^^} ^_^ : the pressure at which fluid X l is being injected at surface, given by S_X_inject_pressure o ^^^^ _^ ^{^} ^^{^^} ^^{^} ^ : the temperature at which fluid X l is being injected at surface, given by S_X_inject_temperature [0063] All volume rates are first expressed at the same arbitrary reference pressure ^^^^ _{^^^^ ^^^^ ^^^^}, and temperature, ^^^^ _{^^^^ ^^^^ ^^^^}. Such reference condition can be standard conditions, typically 1 atmosphere and 15 degrees Celcius. Such reference conditions may also be production conditions provided by the sensor data S_X_prod_pressure ( ^^^^ ^{^^^^} ^_^^^) and S_X_prod_temperature ( ^^^^ ^{^^^^} ^_^^^) as illustrated in FIG.6. Conversion is done as follows: ^_{^^^ ^^^^ =} ^{^^^^( ^^^^, ^^^^) ^^^^ ^^^^)} IS23.0420-WO-PCT [0064] ^^^^ and ^^^^ are the pressure and temperature used by the particular sensor 40, 46 to report the volume rate ^^^^, and ^^^^ is the density function of the fluid in consideration. If the particular sensor 40, 46 uses ambient conditions to report ^^^^, then the sensor data S_X_inject_pressure ( ^^^^ _^ ^{^} ^^{^^} ^^{^} ^ ) and S_X_inject_temperature ( ^^^^ _^ ^{^} ^^{^^} ^^{^} ^ ) provide the required information for the injected fluids. The sensor data S_X_prod_pressure ( ^^^^ ^{^^^^ ^^^^} ^_^^^) and S_X_prod_temperature ( ^^^^ _^^^^) provides the required information for the produced fluids. If the sensors 40, 46 do not use ambient conditions, the reference conditions, ^^^^ _{^^^^ ^^^^ ^^^^} and ^^^^ _{^^^^ ^^^^ ^^^^} for the sensors 40, 46 must be known a priori. For example, if the sensors 40, 46 use standard conditions, it may be understood that the volume rates ^^^^ are provided at such conditions. The density function is a known fluid property that does not require sensing. As described herein, all rates are assumed to have been converted to the same reference pressure ^^^^ _{^^^^ ^^^^ ^^^^} and temperature ^^^^ _{^^^^ ^^^^ ^^^^}. [0065] The reference volume rate of reservoir fluid RX (X = G, O, W) being produced at the surface 24 at any time is taken as follows: ^^^^ ^{^^^^} ^_{^^^ ^^^^}� ^^^^ _{^^^^ ^^^^ ^^^^} , ^^^^ _{^^^^ ^^^^ ^^^^}� = max�0, ^^^^ ^{^^^^} ^_{^^^ ^^^^}� ^^^^ _{^^^^ ^^^^ ^^^^} , ^^^^ _{^^^^ ^^^^ ^^^^}� − ^^^^ _^^ ^{^^} ^^{^} ^^{^} ^_^^^� ^^^^ _{^^^^ ^^^^ ^^^^}, ^^^^ _{^^^^ ^^^^ ^^^^}�� [0066] S_TX_prod_rate (X = O, G, or W) provides ^^^^ ^{^^^^} ^_{^^^ ^^^^ ^^^^} and S_IX_inject_rate (X = O, G or W) provides ^^^^ _^ ^{^} ^^{^} ^^{^} ^^{^} ^_^^^ . In addition, ^^^^ ^{^^^^} ^_{^^^ ^^^^}� ^^^^ _{^^^^ ^^^^ ^^^^}, ^^^^ _{^^^^ ^^^^ ^^^^}� represents the reservoir fluid inflow rate at refence conditions (Check Point 2). FIG.7 illustrates a real-time graph 106 showing estimations of fluid inflow, which may be generated by the surface processing system 42, as described in greater detail herein. [0067] The reference volume rate of injected fluid IX (X = G, O, W) being produced at the surface 24 at any time is taken as: ^^^^ ^{^^^^}� ^^^^ , ^^^^ � = ^^^^ ^{^^^^}� ^^^^ , ^ ^{^^^^} ^_{^^^ ^^^^ ^^^^ ^^^^ ^^^^ ^^^^ ^^^^ ^^^^ ^^^^ ^^^^ ^^^^ ^^^^ ^^^^} ^^^ _{^^^^ ^^^^ ^^^^}� − ^^^^ _{^^^^ ^^^^}� ^^^^ _{^^^^ ^^^^ ^^^^} , ^^^^ _{^^^^ ^^^^ ^^^^}� IS23.0420-WO-PCT [0068] S_TX_prod_rate (X = O, G, or W) provides ^^^^ ^{^^^^} ^_{^^^ ^^^^} and using ^^^^ ^{^^^^} ^_{^^^ ^^^^} calculated above. [0069] The reference volume rate of injected fluid IX (X = G, O, W) leaking off into the reservoir 16 at any time is taken as: ^^^^ _^^ ^{^^} ^^{^} ^^{^} ^ ^{^} ^^{^^} ^^{^} ^� ^^^^ _^, _{^^^^ ^^^^ ^^^^ ^^} ^{^^} ^^{^} ^^{^ ^^^^} ^_{^^^ ^^^^ ^^^} ^^^^ � = ^^^^ _^^^^� ^^^^ _{^^^^ ^^^^ ^^^^}, ^^^^ _{^^^^ ^^^^ ^^^^}� − ^^^^ _{^^^^ ^^^^}� ^^^^ _{^^^^ ^^^^ ^^^^} , ^^^^ _{^^^^ ^^^^ ^^^^}� [0070] = or _{^^^^ ^^^^ ^^^^ ^^^^} calculated above. [0071] ^^^^ _^ ^{^} ^^{^} ^^{^} ^^{^} ^ ^{^} ^^{^^} ^^{^} ^� ^^^^ _{^^^^ ^^^^ ^^^^}, ^^^^ _{^^^^ ^^^^ ^^^^}� represents the injection fluid leak-off rate into the reservoir 16 at reference (Check Point 1). FIG.8 illustrates a real-time graph 108 showing estimations of reservoir fluid inflow, which may be generated by the surface processing system 42, as described in greater detail herein. Methods for Estimating Check Point 3 [0072] The mass rate of fluid X, with X = IG, IO, IW, or RW, being produced at the surface 24 is given as follows: ^^^^ ^{^^^^} = ^^^^� ^^^^ , ^^ ^{^^^^} ^_{^^^ ^^^^ ^^^^ ^^^^ ^^^^} ^^ _{^^^^ ^^^^ ^^^^}� ^^^^ _^^^^� ^^^^ _{^^^^ ^^^^ ^^^^} , ^^^^ _{^^^^ ^^^^ ^^^^}� [0073] The annular volume rate ^^^^ _^ ^{^} ^^{^} ^^{^} ^^{^} of fluid X, with X = IG, IO, IW, or RW, along the coiled _{tubing annulus is a function of the temperature ^^^^} ⁽ _{^^^^, ^^^^ ^^^^} ⁾ _{and pressure ^^^^} ⁽ _{^^^^, ^^^^ ^^^^} ⁾ _{where ^^^^ is time} and ^^^^ ^^^^ is the the Measured Depth along the annulus (i.e., between the coiled tubing string 12 and the wellbore 14). ^^{^^^ ^^^^ ^^^^ ^^^^ ^^^^ ^^^^ ^^^^} ) [0074] ^^^^ _^^^^ is the known density function for fluid X with X = IG, IO, IW, or RW. To determine ^^^^ _^ ^{^} ^^{^} ^^{^} ^^{^}( ^^^^, ^^^^ ^^^^), pressure ^^^^( ^^^^, ^^^^ ^^^^) and temperature ^^^^( ^^^^, ^^^^ ^^^^) must be estimated. ^^^^ ^^^^ ^^^^ may denote the true vertical depth measured at ^^^^ ^^^^. S_DH_pressure and S_DH_temperature IS23.0420-WO-PCT _{provide the downhole pressure ^^^^} ^{^^^^ℎ ^^^^(} _^^^^ ⁾ _{and temperature ^^^^} ^{^^^^ℎ ^^^^(} _^^^^ ⁾ _{at a measured depth, denoted} ^^^^ ^^^^ _{^^^^ ^^^^ ^^^^}. S_WH_pressure and S_WH_temperature provide the pressure ^^^^ ^{^^^^ℎ} ^ ⁽ _^^^^ ⁾ _{and temperature} ^^^^ ^{^^^^ℎ} ^ ⁽ _^^^^ ⁾ _{at the surface production line where ^^^^ ^^^^ ^^^^ = 0.} The following approximations may be made: ^_{^^^( ^^^^, ^^^^ ^^^^) = ^^^^} ^{^^^^ℎ} ^ _{( ^^^^) +� ^^^^} ^{^^^^ℎ ^^^^} _{( ^^^^) − ^^^^} ^{^^^^ℎ} ^ _{( ^^^^)�} ^{^^^^ ^^^^ ^^^^( ^^^^ ^^^^)} ^_{^^^ ^^^^ ^^^^ ^^^^ ^^^^ ^^^} )_^ or ^_{^^^ ^^^^ ^^^^ ^^^^ ^^^^} [0076] Reservoir oil and gas may undergo phase transitions along the annulus. All of the reservoir hydrocarbon fluids RO and RG being produced may be combined into a single hydrocarbon fluid, denoted RHC: ^^^^ ^{^^^^ ^^^^ ^^^^} ^_{^^^ ^^^^ ^^^^} = ^^^^ _{^^^^ ^^^^} + ^^^^ _{^^^^ ^^^^} [0077] The annular volume rate ^^^^ _^ ^{^} ^^{^} ^_^ ^{^} ℎ^{^} ^_^^^ of the combined reservoir hydrocarbon fluids along the coiled tubing annulus is a function of the temperature ^^^^( ^^^^, ^^^^ ^^^^) and pressure ^^^^( ^^^^, ^^^^ ^^^^) where ^^^^ is time and ^^^^ ^^^^ is the the Measured Depth along the annulus. ^^{^^^ ^^^^ ^^^^ ^^^^ ^^^ ^^^^ ^^^^ ^^^^ ^^^^ ^^^^ ^^^^ ^ ^^^^ = )} ) [0078] ^^^^ _{^^^^ ^^^^} and ^^^^ _{^^^^ ^^^^} are the oil and gas volume fractions, respectively. In addition, ^^^^ _{^^^^ ^^^^}, ^^^^ _{^^^^ ^^^^}, ^^^^ _{^^^^ ^^^^} and ^^^^ _{^^^^ ^^^^} are known function of pressure and temperature. They can be provided by the IS23.0420-WO-PCT relevant Equation of State (EOS), or Pressure-Volume-Temperature (PVT) tables derived experimentally of using correlations, or by a Compositional Model (CM) when the hydrocarbon molar composition is known. Additionally, ^^^^ _{^^^^ ^^^^}, ^^^^ _{^^^^ ^^^^}, ^^^^ _{^^^^ ^^^^} and ^^^^ _{^^^^ ^^^^} may be pre-computed before the CTCO starts and stored in tables, for various values of pressure and temperature, and may be used as lookup tables during performance of the CTCO to improve computation time as the use ^{of the CM may be relatively computationally expensive. From this:} ^_{^^^ ^^^^ ^^^^ ^^^^ ( ^^^^, ^^^^ ^^^^) = ^^^^ ^^^^ ^^^^� ^^^^( ^^^^, ^^^^ ^^^^), ^^^^( ^^^^, ^^^^ ^^^^)� ^^^^ ^^^^ ^^^^ ^^^^ ^^^^ ( ^^^^, ^^^^ ^^^^)} [0079] The total rate ^^^^ _{^ ^^^ ^^^^ ^^^^ ^^^^} reservoir fluids ^{may be determined by:} ^_{^^^ ^^^^ ^^^^ ^^^^ ^^^^ ^^^^ ^^^^ ( ^^^^, ^^^^ ^^^^) = ^^^^ ^^^^ ^^^^ ^^^^ ( ^^^^, ^^^^ ^^^^) + ^^^^ ^^^^ ^^^^ ^^^^ ( ^^^^, ^^^^ ^^^^) + ^^^^ ^^^^ ^^^^ ^^^^ ( ^^^^, ^^^^ ^^^^) + ^^^^ ^^^^ ^^^^ ^^^^ ( ^^^^, ^^^^ ^^^^) + ^^^^ ^^^^ ^^^^ ^^^^ ( ^^^^, ^^^^ ^^^^) + ^^^^ ^^^^ ^^^^ ^^^^} [0080] To assess solids transport efficiency along the annulus, ^^^^ _^ ^{^} ^_^ ^{^} ^^{^} ^^{^} ^_{^^ ^^^^ ^^^^ ^^^^} ⁽ ^^^^, ^^^^ ^^^^⁾ may be compared to ^^^^ ^{^^^^} ^_{^^^ ^^^^ ^^^^( ^^^^, ^^^^ ^^^^)} , the minimum annular volume rate required to prevent solids from settling and prevent the existence of a solids bed at the bottom of the well. ^^^^ ^{^^^^} ^_{^^^ ^^^^ ^^^^} ( ^^^^, ^^^^ ^^^^) is a function of: • The known annular geometry at depth ^^^^ ^^^^ and time ^^^^ • The known wellbore deviation angle at depth ^^^^ ^^^^ • The known solids density and particle size • The known fluid densities and viscosity at depth ^^^^ ^^^^ and time ^^^^ • The above calculated annular volume rates ^^^^ _^^ ^{^} ^^{^} ^^{^^} (X=RO, RG, RW, IO, IG, IW) at depth ^^^^ ^^^^ and time ^^^^ IS23.0420-WO-PCT [0081] A model to calculate ^^^^ _^ ^{^^} ^^{^} ^^{^} ^ _{^^^^ ^^^^} may require relatively significant computational time. To solve ^^^^ ^{^^^^} ^_{^^^ ^^^^ ^^^^} faster in real-time, ^{^^^^} ^_^^ may be pre-computed for various combinations of the above _{^ ^^^^} parameters and stored in lookup tables to be used to solve ^^^^ _^ ^{^} ^^{^^} ^^{^} ^ _{^^^^ ^^^^} during performance of the CTCO. In addition, the range of the above parameters and, therefore, the size of the lookup tables, may be reduced by constraining the parameters to a range that could possibly occur during performance of the CTCO in consideration. FIG.9 illustrates an example graphical display 110 for showing all times and all depths how ^^^^ ^{^^^^} ^_{^^^ ^^^^ ^^^^} and ^^^^ _^ ^{^} ^_^ ^{^} ^^{^} ^^{^} ^_{^^ ^^^^ ^^^^ ^^^^} compare, which may be generated by the surface processing system 42, as described in greater detail herein. In particular, FIG.9 illustrates a real-time graph 110 comparing ^^^^ ^{^^^^} ^_{^^^ ^^^^ ^^^^} and ^^^^ _^ ^{^} ^_^ ^{^} ^^{^} ^^{^} ^_{^^ ^^^^ ^^^^ ^^^^} to determine regions of relatively good and relatively poor solids tubing annulus. Methods for Estimating Check Point 4 [0082] To provide advice on the adjustment to the operational parameters the following procedure can be followed: • Step 1. Running in hole and establish circulation. • Step 2. Evaluating inflow/losses following the methodology for Check Points 1 and 2. • Step 3. Evaluating lifting capabilities following the methodology for Check Point 3. • Step 4. Estimating characteristics describing the reservoir system in the well. • Step 5. Setting up a predictive numerical model. • Step 6. Running sensitivity of the predictive numerical model to a select range of reservoir characteristic values to identify required pumping rates to establish relatively good solids transport for a given reservoir description. • Step 7a. If Step 3 indicates relatively good solids transport along the coiled tubing annulus, assessing the possibility to reduce the pumping rates, and continue with the IS23.0420-WO-PCT operation until the method for estimating Check Point 3 indicates relatively poor solids transport, then proceeding with steps 5-7. • Step 7b. If Step 3 indicates relatively poor solids transport along the coiled tubing annulus, recommending a change in pumping rates. [0083] Step 1 is an essential part of the CTCO, it commonly follows these steps: 1. Reach circulation depth during run in hole ^^^^ ^^^^ _{^^^^ ^^^^ ^^^^}. 2. Start pumping with pumping rates ^^^^ _^ ^{^} ^^{^} ^^{^} ^^{^} ^_^^^ 3. Wait for time ^^^^ ^^^^ _^ ^{^} ^_{^^ ^^^^} : ^^^^ ^^^^^{^} _{= 2} ^{^^^^ ^^^^ ^^^^ ^^^ ^^^^^ ^^^^} ^_{^^^ ^^^^ � +} � ^^^^ ^^^^ ^^^^ ^^^^ where ^^^^ _{^^^^ ^^^^} is the internal and ^^^ _^^_{^^^ ^^^^} is the total volume of the annulus around the coiled tubing 20. 4. Observe the return rates ^^^^ ^{^^^^} ^_^^^ a. If the rates are stable, proceed to 5. b. If the rates are not stable, go to 3, and wait until the return rates stabilize. 5. Obtain the downhole pressure, surface pressure, and return rates. [0084] Steps 2 and 3 follow the methods described above and provide distribution of pressure ^^^^( ^^^^ ^^^^), phase volume fractions ^^^^( ^^^^ ^^^^) and volumetric flow rate ^^^^( ^^^^ ^^^^) along the annulus and estimated inflow/losses ^^^^ ^{^^^^ ^^^^ ^^^^} ^_{^^^ ^^^^} , ^^^^ _{^^^^ ^^^^} . [0085] Step 4: The average reservoir characteristics of the well may be estimated: average phase productivity index ^^^^ ^^^^ _^^^^ and average reservoir pressure ^^^^ ^{^^^^ ^^^^ ^^^^} ^may be attributed to characteristic depth ^^^^ ^^^^ _{^^^^ ^^^^ ^^^^}. Using pressure ^^^^ ^{^^^^ℎ ^^^^} and ^^^^ ^{^^^^ ^^^^ ^^^^} ^_{^^^ ^^^^} and ^^^^ _{^^^^ ^^^^} values, this system defines the relation between productivity index and reservoir pressure: IS23.0420-WO-PCT ^^^^ ^{^^^^} ^_{^^^ ^^^^ = ^^^^ ^^^^ ^^^^} ⁽ _^^^^ ^{^^^^ ^^^^ ^^^^} _{− ^^^^} ^{^^^^ ^^^^)} _{, ^^^^ ^^^^ ^^^^ ^^^^ > ^^^^ ^^^^ ^^^^} 0 0 [0086] From for e ^{^^^^ ^^^^ ^^^^} ach value ^^^^ there is ^^^^ ^^^^ _^^^^ that satisfies the equations. Additional information about the reservoir, such as well historical production, can be used to reduce the range of considered combination of values. [0087] Step 5: A predictive numerical model is setup using the initial distribution of phases, volumetric rates, and pressure from step 3. This model uses surface choke settings and pressure, pumping rates, and reservoir characteristics as inputs and outputs flow rates, phase volume fractions, and pressure distribution along the annulus. [0088] Step 6: Sensitivity of the model to the inputs is used to assess minimal pumping rates required to establish relatively good solids transport for each combination of operationally uncertain parameters. For each of the selected combination of reservoir characteristics values on step 4, these steps are performed: 1. Select new pumping rates. 2. Run numerical model with the selected pumping rates and reservoir characteristics. 3. Estimate minimal volumetric rate required for solids transport ^^^^ _^ ^{^} ^^{^^} ^^{^} ^ _{^^^^ ^^^^} ( ^^^^, ^^^^ ^^^^) IS23.0420-WO-PCT 4^{. Compare the resulting distribution of volumetric rates in the annulus against} ^_{^^^ ^^^^ ^^^^ ^^^^ ^^^^ ( ^^^^, ^^^^ ^^^^):} indicates relatively poor solids transport, go to 1. b. If comparison indicates relatively good solids transport, save the combination of pumping rates and reservoir characteristics. [0089] The process of selecting new pumping rates is iterative and depends on the current evaluation of solids transport. If the status indicates relatively poor transport, then new pumping rates should be higher than the previous; and if the status indicates relatively good transport, then the new rates could be lower. The results of this sensitivity study are used to advise on the optimization of CTCO in Step 7. [0090] It will be appreciated that running the numerical model may use significant time and computational resources. To mitigate this, with available information on reservoir characteristics from production data of the well, a sensitivity study may be precalculated before the job begins. [0091] After action is taken based on the advice, Steps 2-4 may be reperformed. For example, new ^^^^ ^{^^} ^_{^^^ℎ ^^^^} , ^^^^ ^{^^} ^_{^^^ ^^^^} and ^^^^ _^ ^{^} ^^{^} ^^{^} ^^{^} ^ ^{^} ^^{^^} ^^{^} ^ values may be used to reduce the uncertainty in reservoir characteristics and narrow the set of applicable results of the sensitivity study. [0092] As such, the embodiments described herein facilitate the improvement of CTCOs by providing real-time diagnostics of downhole conditions during performance of the CTCOs. FIG. 10 illustrates a workflow of a method 112 for providing such real-time diagnostics, for example, using the surface processing system 42 (e.g., a computer-based processing and control system) described herein. As illustrated in FIG.10, in certain embodiments, the method 112 may include acquiring, via one or more sensors 40, 46 of a coiled tubing system 10, data relating to a CTCO performed at least partially within a wellbore 14 of the coiled tubing system 10 (block 114). In IS23.0420-WO-PCT addition, in certain embodiments, the method 112 may include analyzing, via a processing and control system (e.g., the surface processing system 42), the acquired data to provide real-time diagnostics of downhole conditions within the wellbore 14 during performance of the CTCO (block 116). In addition, in certain embodiments, the method 112 may include providing, via the processing and control system (e.g., the surface processing system 42), one or more outputs relating to the real-time diagnostics of the downhole conditions within the wellbore 14 during performance of the CTCO (block 118). In addition, in certain embodiments, the method 112 may include adjusting, via the processing and control system (e.g., the surface processing system 42), one or more operational parameters of the CTCO based at least in part on the one or more outputs (block 120). [0093] In certain embodiments, the one or more operational parameters of the CTCO may be automatically (e.g., without human intervention) adjusted by the processing and control system (e.g., the surface processing system 42) in substantially real-time during performance of the CTCO. In addition, in certain embodiments, all of the steps of the method 112 may be performed in substantially real-time during performance of the CTCO. Alternatively, in other embodiments, the one or more operational parameters of the CTCO may be adjusted by an operator using a computing system 78, a display of which is displaying the one or more outputs that are provided by the processing and control system (e.g., the surface processing system 42). [0094] In certain embodiments, the one or more outputs relating to the real-time diagnostics of the downhole conditions within the wellbore 14 may include an indication that an amount of fluid leak-off into a reservoir 16 through which the wellbore 14 extends is minimized to prevent formation damage (i.e., including the data that is described with reference to Check Point 1 described herein). In addition, in certain embodiments, the one or more outputs relating to the IS23.0420-WO-PCT real-time diagnostics of the downhole conditions within the wellbore 14 may include an indication that an amount of fluid inflow from a reservoir 16 through which the wellbore 14 extends is below a predetermined threshold to prevent fluid handling limitations at a surface location 24 of the coiled tubing system 10 (i.e., including the data that is described with reference to Check Point 2 described herein). In addition, in certain embodiments, the one or more outputs relating to the real-time diagnostics of the downhole conditions within the wellbore 14 may include an indication that solids in the wellbore 14 are being transported with injected fluids to a surface location 24 of the coiled tubing system 10 at or above a desired rate (i.e., including the data that is described with reference to Check Point 3 described herein). In addition, in certain embodiments, the one or more outputs relating to the real-time diagnostics of the downhole conditions within the wellbore 14 may include an indication that operating conditions of the CTCO are adjustable during performance of the CTCO (i.e., including the data that is described with reference to Check Point 4 described herein). [0095] In certain embodiments, the one or more sensors 40, 46 of the coiled tubing system 10 may include one or more downhole sensors 40 disposed within the wellbore 14 during performance of the CTCO. In addition, in certain embodiments, the one or more sensors 40, 46 of the coiled tubing system 10 may include one or more surface sensors 46 disposed at a surface location 24 of the coiled tubing system 10 during performance of the CTCO. [0096] The specific embodiments described above have been illustrated by way of example, and it should be understood that these embodiments may be susceptible to various modifications and alternative forms. It should be further understood that the claims are not intended to be limited to the particular forms disclosed, but rather to cover all modifications, equivalents, and alternatives falling within the spirit and scope of this disclosure. IS23.0420-WO-PCT [0097] The techniques presented and claimed herein are referenced and applied to material objects and concrete examples of a practical nature that demonstrably improve the present technical field and, as such, are not abstract, intangible or purely theoretical. Further, if any claims appended to the end of this specification contain one or more elements designated as “means for [perform]ing [a function]…” or “step for [perform]ing [a function]…”, it is intended that such elements are to be interpreted under 35 U.S.C. § 112(f). However, for any claims containing elements designated in any other manner, it is intended that such elements are not to be interpreted under 35 U.S.C. § 112(f).

Claims

IS23.0420-WO-PCT CLAIMS 1. A method, comprising: acquiring, via one or more sensors of a coiled tubing system, data relating to a coiled tubing cleanout operation performed at least partially within a wellbore of the coiled tubing system; analyzing, via a processing and control system, the acquired data to provide real-time diagnostics of downhole conditions within the wellbore during performance of the coiled tubing cleanout operation; providing, via the processing and control system, one or more outputs relating to the real- time diagnostics of the downhole conditions within the wellbore during performance of the coiled tubing cleanout operation; and adjusting, via the processing and control system, one or more operational parameters of the coiled tubing cleanout operation based at least in part on the one or more outputs. 2. The method of claim 1, wherein the one or more outputs relating to the real-time diagnostics of the downhole conditions within the wellbore comprise an indication that an amount of fluid leak-off into a reservoir through which the wellbore extends is minimized to prevent formation damage. 3. The method of claim 1, wherein the one or more outputs relating to the real-time diagnostics of the downhole conditions within the wellbore comprise an indication that an amount of fluid inflow from a reservoir through which the wellbore extends is below a IS23.0420-WO-PCT predetermined threshold to prevent fluid handling limitations at a surface location of the coiled tubing system. 4. The method of claim 1, wherein the one or more outputs relating to the real-time diagnostics of the downhole conditions within the wellbore comprise an indication that solids in the wellbore are being transported with injected fluids to a surface location of the coiled tubing system at or above a desired rate. 5. The method of claim 1, wherein the one or more outputs relating to the real-time diagnostics of the downhole conditions within the wellbore comprise an indication that operating conditions of the coiled tubing cleanout operation are adjustable during performance of the coiled tubing cleanout operation. 6. The method of claim 1, wherein the one or more sensors of the coiled tubing system comprise one or more downhole sensors disposed within the wellbore during performance of the coiled tubing cleanout operation. 7. The method of claim 1, wherein the one or more sensors of the coiled tubing system comprise one or more surface sensors disposed at a surface location of the coiled tubing system during performance of the coiled tubing cleanout operation. 8. The method of claim 1, wherein all of the recited steps of the method are performed in substantially real-time during performance of the coiled tubing cleanout operation. IS23.0420-WO-PCT 9. A processing and control system, comprising: one or more processors configured to execute processor-executable instructions stored in memory media of the processing and control system, wherein the processor-executable instructions, when executed by the one or more processors, cause the processing and control system to: receive, from one or more sensors of a coiled tubing system, data relating to a coiled tubing cleanout operation performed at least partially within a wellbore of the coiled tubing system; analyze the received data to provide real-time diagnostics of downhole conditions within the wellbore during performance of the coiled tubing cleanout operation; provide one or more outputs relating to the real-time diagnostics of the downhole conditions within the wellbore during performance of the coiled tubing cleanout operation; and adjust one or more operational parameters of the coiled tubing cleanout operation based at least in part on the one or more outputs. 10. The processing and control system of claim 9, wherein the one or more outputs relating to the real-time diagnostics of the downhole conditions within the wellbore comprise an indication that an amount of fluid leak-off into a reservoir through which the wellbore extends is minimized to prevent formation damage. IS23.0420-WO-PCT 11. The processing and control system of claim 9, wherein the one or more outputs relating to the real-time diagnostics of the downhole conditions within the wellbore comprise an indication that an amount of fluid inflow from a reservoir through which the wellbore extends is below a predetermined threshold to prevent fluid handling limitations at a surface location of the coiled tubing system. 12. The processing and control system of claim 9, wherein the one or more outputs relating to the real-time diagnostics of the downhole conditions within the wellbore comprise an indication that solids in the wellbore are being transported with injected fluids to a surface location of the coiled tubing system at or above a desired rate. 13. The processing and control system of claim 9, wherein the one or more outputs relating to the real-time diagnostics of the downhole conditions within the wellbore comprise an indication that operating conditions of the coiled tubing cleanout operation are adjustable during performance of the coiled tubing cleanout operation. 14. The processing and control system of claim 9, wherein the one or more sensors of the coiled tubing system comprise one or more downhole sensors disposed within the wellbore during performance of the coiled tubing cleanout operation. 15. The processing and control system of claim 9, wherein the one or more sensors of the coiled tubing system comprise one or more surface sensors disposed at a surface location of the coiled tubing system during performance of the coiled tubing cleanout operation. IS23.0420-WO-PCT 16. A tangible non-transitory computer-readable medium, comprising: processor-executable instructions configured to be executed by one or more processors, wherein the processor-executable instructions, when executed by the one or more processors, cause the one or more processors to: receive, from one or more sensors of a coiled tubing system, data relating to a coiled tubing cleanout operation performed at least partially within a wellbore of the coiled tubing system; analyze the received data to provide real-time diagnostics of downhole conditions within the wellbore during performance of the coiled tubing cleanout operation; provide one or more outputs relating to the real-time diagnostics of the downhole conditions within the wellbore during performance of the coiled tubing cleanout operation; and adjust one or more operational parameters of the coiled tubing cleanout operation based at least in part on the one or more outputs. 17. The tangible non-transitory computer-readable medium of claim 16, wherein the one or more outputs relating to the real-time diagnostics of the downhole conditions within the wellbore comprise an indication that an amount of fluid leak-off into a reservoir through which the wellbore extends is minimized to prevent formation damage. 18. The tangible non-transitory computer-readable medium of claim 16, wherein the one or more outputs relating to the real-time diagnostics of the downhole conditions within the IS23.0420-WO-PCT wellbore comprise an indication that an amount of fluid inflow from a reservoir through which the wellbore extends is below a predetermined threshold to prevent fluid handling limitations at a surface location of the coiled tubing system. 19. The tangible non-transitory computer-readable medium of claim 16, wherein the one or more outputs relating to the real-time diagnostics of the downhole conditions within the wellbore comprise an indication that solids in the wellbore are being transported with injected fluids to a surface location of the coiled tubing system at or above a desired rate. 20. The tangible non-transitory computer-readable medium of claim 16, wherein the one or more outputs relating to the real-time diagnostics of the downhole conditions within the wellbore comprise an indication that operating conditions of the coiled tubing cleanout operation are adjustable during performance of the coiled tubing cleanout operation.