Patent Application
20230128460
The present disclosure applies to monitoring and controlling flare systems.
Flare systems include gas flares (or flare stacks) that provide gas combustion at industrial plants such as at onshore and offshore oil and gas production sites. Flare systems can provide venting during start-up or shut-down, and for handling emergency releases from safety valves, blow-down, and de-pressuring systems.
The present disclosure describes techniques that can be used for analyzing flare systems emissions. In some implementations, a computer-implemented method includes the following. Flaring emissions are determined in real time for a flare stack based on: 1) a flaring volume in conjunction with heat and material balances of systems that discharge to a flare system, and 2) a composition of each relief source that discharges to the flare system. A molar balance around the flare stack is performed in real time using the flaring emissions to determine the emissions.
The previously described implementation is implementable using a computer-implemented method; a non-transitory, computer-readable medium storing computer-readable instructions to perform the computer-implemented method; and a computer-implemented system including a computer memory interoperably coupled with a hardware processor configured to perform the computer-implemented method, the instructions stored on the non-transitory, computer-readable medium.
The subject matter described in this specification can be implemented in particular implementations, so as to realize one or more of the following advantages. Using techniques of the present disclosure can eliminate limitations in reading range common to commercially available alternatives, which are designed with specific ranges of operation. The techniques can help to measure and monitor the life-stream of each flare header. Combustible fluid losses can be reduced (improving de-carbonization by implementing techniques that result in emitting less carbon to the environment). The accuracy of emissions calculations for sulfuric dioxide (SO2), nitrogen dioxide (NO2), carbon dioxide (CO2), and methane (CH4) can be improved. The monitoring and reporting of greenhouse gas (GHG) emissions can be automated. Techniques of the present disclosure can aid operators in conducting a thorough analysis of flaring events as real-time emissions calculations are available. Techniques of the present disclosure can be non-intrusive and can provide cost-effective, real-time estimations of flare system compositions, including flare system GHG emissions, with zero capital expenditures (CAPEX) and operating expenses (OPEX) costs. This can overcome limitations in conventional systems related to measuring range and requiring frequent calibration and maintenance. Also, conventional systems can have limitations of not being an online solution, requiring that readings occur during discrete periods of time. The techniques of the present disclosure have no limitations in reading range and require no maintenance, which can result in ensuring accurate results at all times. Facilities can measure and monitor emissions for each flare header without requiring the installation of an analyzer. The techniques of the present disclosure overcome limitations in conventional systems that do not disclose heat/material balances of systems that discharge to a flare system to determine flare emissions. The techniques can be used to implement systems that are able to determine GHG and SO2 emissions for a flare system.
The details of one or more implementations of the subject matter of this specification are set forth in the Detailed Description, the accompanying drawings, and the claims. Other features, aspects, and advantages of the subject matter will become apparent from the Detailed Description, the claims, and the accompanying drawings.
Like reference numbers and designations in the various drawings indicate like elements.
The following detailed description describes techniques for analyzing flare systems emissions. Various modifications, alterations, and permutations of the disclosed implementations can be made and will be readily apparent to those of ordinary skill in the art, and the general principles defined may be applied to other implementations and applications, without departing from the scope of the disclosure. In some instances, details unnecessary to obtain an understanding of the described subject matter may be omitted so as to not obscure one or more described implementations with unnecessary detail and inasmuch as such details are within the skill of one of ordinary skill in the art. The present disclosure is not intended to be limited to the described or illustrated implementations, but to be accorded the widest scope consistent with the described principles and features.
The present disclosure relates to computing flaring emissions, for example, sulfuric dioxide (SO2), nitrogen dioxide (NO2), carbon dioxide (CO2), and methane (CH4) for a flare stack based on: 1) the flaring volume in conjunction with heat/material balances of systems that discharge to the flare system, and 2) the composition of each relief source that discharges to the flare system. A molar balance around the flare stack is performed to determine the emissions. Input data may be received, and calculations performed in real time. The determined emissions may be reported (for example, in real time) to operators, and in response, the operators may adjust operation of the systems (that discharge to the flare) to alter the flaring emissions.
A flare systems emissions analyzer is a solution that has the capability to compute the actual flaring emissions of SO2, NO2, CO2, and CH4 for each flare stack. Techniques of the present disclosure can include receiving real-time data from each processing facility's flaring volumes. The data can be analyzed in conjunction with the heat and material balance of the processing facilities and the composition of each relief source connected to the flare system. Results of the analysis can be used to perform a comprehensive molar balance around the flare stack and to determine the emissions with high accuracy. The results of the analysis can be provided to operators in the form of reports that indicate the average daily emissions, providing a real-time display for tracking purposes. The reports and displays can aid operators in tracking and reducing gas emissions at the flare system.
where: HC is a molar flow of component (i), for example, in pound-moles per day (lb-mol/d); a, b, and c are stoichiometric coefficients of combustion reaction (dependent on the hydrocarbon component); O2 is a molar rate of oxygen required for combustion, for example, in lb-mol/d; H2S is a molar flow of hydrogen sulfide, for example, in lb-mol/d; CO2 is a rate of formation of H2S, for example, in lb-mol/d; and SO2 is a rate of formation of SO2, for example, lb-mol/d. In the term HCi, the component i represents a number of carbons in a given compound. For example, C3H6 has three carbon atoms, and thus will generate three times more CO2 as compared to CH4.
Using an API Compendium emission methodology (for example, API, Compendium of Green Gas methodologies for Oil and Natural Gas Industry, 2009):
where: Molar Volume Conversion is a conversion from molar volume to mass, for example, at a rate of 379.3 standard cubic feet per pound-mole (scf/lb-mol) or a conversion of 23.685 cubic meters per kilogram-mole (m3/kg-mole); MW CO2 is a CO2 molecular weight; mass conversion is, for example, tons/2204.62 lb or tons/1000 kg; A is a number of moles of carbon for a particular hydrocarbon; and B is a number of moles of CO2 present in the flared gas stream. Note that API Compendium recommends test data or vendor-specific information, such as flare combustion efficiency, for estimating flare emissions from gas streams. This is because this information is of higher quality than the default 98% combustion efficiency:
where: ECH4 is an amount of emissions of CH4 (for example, in lb); V is a volume flared (for example, in scf); % residual CH4 is a non-combusted fraction of flared stream (for example, with a default of 0.5% or 2%); molar volume conversion is a conversion from molar volume to mass, (for example, 379.3 scf/lb-mole or a conversion of 23.685 m3/kg-mole); and MWCH4 is a CH4 molecular weight. Note that because API Compendium indicates that flare systems have a combustion efficiency greater than 98%, the % residual CH4 can be set at a default of 2% as a conservative measure. Then, based on Equation (4):
E
N
O
=V×EF
N
O (5)
where: EN2O is an amount of emissions of N2O; V is a volume produced or refined (m3, scf, or
barrels (bbl)); and EFN2O is an N2O emission factor (for example, set to a value based on environmental protection data). A performance equation (PI Expiration) can use the previously described equations to create PI tags in the PI server. The PI Tags can be used for a real-time display of the facility and a monitoring dashboard to illustrate and monitor actual flaring compositions.
Techniques of the present disclosure can be used to provide a detailed breakdown of emissions at the device level. By identifying high-intensive emissions sources, operating facilities can effectively conduct root cause analysis and allocate financial resources to reduce the emissions at the source level. Emissions reporting can also be provided on a real-time basis, including identifying daily average values and automatically identifying reasons for the high-emission conditions and events. In some implementations, emissions information can be presented in user interfaces such as described with reference to
At 502, flaring emissions are determined in real time for a flare stack. Based on: 1) a flaring volume in conjunction with heat and material balances of systems that discharge to a flare system, and 2) a composition of each relief source that discharges to the flare system. For example, emissions can be determined as described with reference to Equations (1) to (5). From 502, method 500 proceeds to 504.
At 504, a molar balance around the flare stack is performed in real time using the flaring emissions to determine the emissions. Performing the molar balance can include determining a molar and mass flow for each emission in the set of emissions using a standard pressure (for example, 14.7 psia) and a standard pressure (for example, 60° F.). Determining flaring emissions includes computing hourly flaring emissions for each emission in a set of emissions including sulfuric dioxide (SO2), nitrogen dioxide (NO2), carbon dioxide (CO2), and methane (CH4). Determining the emissions for SO2 and CO2 can be based on combustion stoichiometric coefficients for calculating a rate of formation of SO2 and CO2, for example. Determining the emissions for NO2 and CH4 can be based on American Petroleum Institute (API) Compendium emission methodologies, for example. After 504, method 500 can stop.
In some implementations, method 500 further includes a process for reporting emissions to a user and using inputs from the user to make adjustments to the flaring system. For example, the determined emissions can be provided in a report displayed to an operator in real time. Input can be received from the operator for an adjustment to be made to operation of the flaring system. Operation of the flaring system can be adjusted using the input received from the operator. The process for reporting emissions can include a display that the user/operator uses to monitor the process from the display, without adjusting the values used in operations. In some implementations, the adjustments can be made from the process facility system. The changes can be can monitored in real time using the user interface 200.
In some implementations, in addition to (or in combination with) any previously-described features, techniques of the present disclosure can include the following. Customized user interfaces can present intermediate or final results of the above described processes to a user. The presented information can be presented in one or more textual, tabular, or graphical formats, such as through a dashboard. The information can be presented at one or more on-site locations (such as at an oil well or other facility), on the Internet (such as on a webpage), on a mobile application (or “app”), or at a central processing facility. The presented information can include suggestions, such as suggested changes in parameters or processing inputs, that the user can select to implement improvements in a production environment, such as in the exploration, production, and/or testing of petrochemical processes or facilities. For example, the suggestions can include parameters that, when selected by the user, can cause a change or an improvement in drilling parameters (including speed and direction) or overall production of a gas or oil well. The suggestions, when implemented by the user, can improve the speed and accuracy of calculations, streamline processes, improve models, and solve problems related to efficiency, performance, safety, reliability, costs, downtime, and the need for human interaction. In some implementations, the suggestions can be implemented in real-time, such as to provide an immediate or near-immediate change in operations or in a model. The term real-time can correspond, for example, to events that occur within a specified period of time, such as within one minute or within one second. In some implementations, values of parameters or other variables that are determined can be used automatically (such as through using rules) to implement changes in oil or gas well exploration, production/drilling, or testing. For example, outputs of the present disclosure can be used as inputs to other equipment and/or systems at a facility. This can be especially useful for systems or various pieces of equipment that are located several meters or several miles apart, or are located in different countries or other jurisdictions.
The computer 602 can serve in a role as a client, a network component, a server, a database, a persistency, or components of a computer system for performing the subject matter described in the present disclosure. The illustrated computer 602 is communicably coupled with a network 630. In some implementations, one or more components of the computer 602 can be configured to operate within different environments, including cloud-computing-based environments, local environments, global environments, and combinations of environments.
At a top-level, the computer 602 is an electronic computing device operable to receive, transmit, process, store, and manage data and information associated with the described subject matter. According to some implementations, the computer 602 can also include, or be communicably coupled with, an application server, an email server, a web server, a caching server, a streaming data server, or a combination of servers.
The computer 602 can receive requests over network 630 from a client application (for example, executing on another computer 602). The computer 602 can respond to the received requests by processing the received requests using software applications. Requests can also be sent to the computer 602 from internal users (for example, from a command console), external (or third) parties, automated applications, entities, individuals, systems, and computers.
Each of the components of the computer 602 can communicate using a system bus 603. In some implementations, any or all of the components of the computer 602, including hardware or software components, can interface with each other or the interface 604 (or a combination of both) over the system bus 603. Interfaces can use an application programming interface (API) 612, a service layer 613, or a combination of the API 612 and service layer 613. The API 612 can include specifications for routines, data structures, and object classes. The API 612 can be either computer-language independent or dependent. The API 612 can refer to a complete interface, a single function, or a set of APIs.
The service layer 613 can provide software services to the computer 602 and other components (whether illustrated or not) that are communicably coupled to the computer 602. The functionality of the computer 602 can be accessible for all service consumers using this service layer. Software services, such as those provided by the service layer 613, can provide reusable, defined functionalities through a defined interface. For example, the interface can be software written in JAVA, C++, or a language providing data in extensible markup language (XML) format. While illustrated as an integrated component of the computer 602, in alternative implementations, the API 612 or the service layer 613 can be stand-alone components in relation to other components of the computer 602 and other components communicably coupled to the computer 602. Moreover, any or all parts of the API 612 or the service layer 613 can be implemented as child or sub-modules of another software module, enterprise application, or hardware module without departing from the scope of the present disclosure.
The computer 602 includes an interface 604. Although illustrated as a single interface 604 in
The computer 602 includes a processor 605. Although illustrated as a single processor 605 in
The computer 602 also includes a database 606 that can hold data for the computer 602 and other components connected to the network 630 (whether illustrated or not). For example, database 606 can be an in-memory, conventional, or a database storing data consistent with the present disclosure. In some implementations, database 606 can be a combination of two or more different database types (for example, hybrid in-memory and conventional databases) according to particular needs, desires, or particular implementations of the computer 602 and the described functionality. Although illustrated as a single database 606 in
The computer 602 also includes a memory 607 that can hold data for the computer 602 or a combination of components connected to the network 630 (whether illustrated or not). Memory 607 can store any data consistent with the present disclosure. In some implementations, memory 607 can be a combination of two or more different types of memory (for example, a combination of semiconductor and magnetic storage) according to particular needs, desires, or particular implementations of the computer 602 and the described functionality. Although illustrated as a single memory 607 in
The application 608 can be an algorithmic software engine providing functionality according to particular needs, desires, or particular implementations of the computer 602 and the described functionality. For example, application 608 can serve as one or more components, modules, or applications. Further, although illustrated as a single application 608, the application 608 can be implemented as multiple applications 608 on the computer 602. In addition, although illustrated as internal to the computer 602, in alternative implementations, the application 608 can be external to the computer 602.
The computer 602 can also include a power supply 614. The power supply 614 can include a rechargeable or non-rechargeable battery that can be configured to be either user- or non-user-replaceable. In some implementations, the power supply 614 can include power-conversion and management circuits, including recharging, standby, and power management functionalities. In some implementations, the power supply 614 can include a power plug to allow the computer 602 to be plugged into a wall socket or a power source to, for example, power the computer 602 or recharge a rechargeable battery.
There can be any number of computers 602 associated with, or external to, a computer system containing computer 602, with each computer 602 communicating over network 630. Further, the terms “client,” “user,” and other appropriate terminology can be used interchangeably, as appropriate, without departing from the scope of the present disclosure. Moreover, the present disclosure contemplates that many users can use one computer 602 and one user can use multiple computers 602.
Described implementations of the subject matter can include one or more features, alone or in combination.
For example, in a first implementation, a computer-implemented method includes the following. Flaring emissions are determined in real time for a flare stack based on: 1) a flaring volume in conjunction with heat and material balances of systems that discharge to a flare system, and 2) a composition of each relief source that discharges to the flare system. A molar balance around the flare stack is performed in real time using the flaring emissions to determine the emissions.
The foregoing and other described implementations can each, optionally, include one or more of the following features:
A first feature, combinable with any of the following features, where computing flaring emissions includes computing hourly flaring emissions for each emission in a set of emissions comprising sulfuric dioxide (SO2), nitrogen dioxide (NO2), carbon dioxide (CO2), and methane (CH4).
A second feature, combinable with any of the previous or following features, where performing the molar balance includes determining a molar and mass flow for each emission in the set of emissions using a standard pressure and a standard pressure.
A third feature, combinable with any of the previous or following features, where the standard pressure is 14.7 pounds per square inch absolute (psia), and the standard temperature is 60 degrees Fahrenheit (° F.).
A fourth feature, combinable with any of the previous or following features, where determining the emissions for SO2 and CO2 is based on combustion stoichiometric coefficients for calculating a rate of formation of SO2 and CO2. A fifth feature, combinable with any of the previous or following features, where
determining the emissions for NO2 and CH4 is based on American Petroleum Institute (API) Compendium emission methodologies.
A sixth feature, combinable with any of the previous or following features, the method further including: providing, in real time, the determined emissions in a report displayed to an operator; receiving input from the operator for an adjustment to be made to operation of the flaring system; and adjusting operation of the flaring system using the input received from the operator.
In a second implementation, a non-transitory, computer-readable medium stores one or more instructions executable by a computer system to perform operations, including the following. Flaring emissions are determined in real time for a flare stack based on: 1) a flaring volume in conjunction with heat and material balances of systems that discharge to a flare system, and 2) a composition of each relief source that discharges to the flare system. A molar balance around the flare stack is performed in real time using the flaring emissions to determine the emissions.
The foregoing and other described implementations can each, optionally, include one or more of the following features:
A first feature, combinable with any of the following features, where computing flaring emissions includes computing hourly flaring emissions for each emission in a set of emissions comprising sulfuric dioxide (SO2), nitrogen dioxide (NO2), carbon dioxide (CO2), and methane (CH4).
A second feature, combinable with any of the previous or following features, where performing the molar balance includes determining a molar and mass flow for each emission in the set of emissions using a standard pressure and a standard pressure.
A third feature, combinable with any of the previous or following features, where the standard pressure is 14.7 pounds per square inch absolute (psia), and the standard temperature is 60 degrees Fahrenheit (° F.).
A fourth feature, combinable with any of the previous or following features, where determining the emissions for SO2 and CO2 is based on combustion stoichiometric coefficients for calculating a rate of formation of SO2 and CO2.
A fifth feature, combinable with any of the previous or following features, where determining the emissions for NO2 and CH4 is based on American Petroleum Institute (API) Compendium emission methodologies.
A sixth feature, combinable with any of the previous or following features, the operations further including: providing, in real time, the determined emissions in a report displayed to an operator; receiving input from the operator for an adjustment to be made to operation of the flaring system; and adjusting operation of the flaring system using the input received from the operator.
In a third implementation, a computer-implemented system includes one or more processors and a non-transitory computer-readable storage medium coupled to the one or more processors and storing programming instructions for execution by the one or more processors. The programming instructions instruct the one or more processors to perform operations, including the following. Flaring emissions are determined in real time for a flare stack based on: 1) a flaring volume in conjunction with heat and material balances of systems that discharge to a flare system, and 2) a composition of each relief source that discharges to the flare system. A molar balance around the flare stack is performed in real time using the flaring emissions to determine the emissions.
The foregoing and other described implementations can each, optionally, include one or more of the following features:
A first feature, combinable with any of the following features, where computing flaring emissions includes computing hourly flaring emissions for each emission in a set of emissions comprising sulfuric dioxide (SO2), nitrogen dioxide (NO2), carbon dioxide (CO2), and methane (CH4).
A second feature, combinable with any of the previous or following features, where performing the molar balance includes determining a molar and mass flow for each emission in the set of emissions using a standard pressure and a standard pressure.
A third feature, combinable with any of the previous or following features, where the standard pressure is 14.7 pounds per square inch absolute (psia), and the standard temperature is 60 degrees Fahrenheit (° F.).
A fourth feature, combinable with any of the previous or following features, where determining the emissions for SO2 and CO2 is based on combustion stoichiometric coefficients for calculating a rate of formation of SO2 and CO2.
A fifth feature, combinable with any of the previous or following features, where determining the emissions for NO2 and CH4 is based on American Petroleum Institute (API) Compendium emission methodologies.
Implementations of the subject matter and the functional operations described in this specification can be implemented in digital electronic circuitry, intangibly embodied computer software or firmware, in computer hardware, including the structures disclosed in this specification and their structural equivalents, or in combinations of one or more of them. Software implementations of the described subject matter can be implemented as one or more computer programs. Each computer program can include one or more modules of computer program instructions encoded on a tangible, non-transitory, computer-readable computer-storage medium for execution by, or to control the operation of, data processing apparatus. Alternatively, or additionally, the program instructions can be encoded in/on an artificially-generated propagated signal. For example, the signal can be a machine-generated electrical, optical, or electromagnetic signal that is generated to encode information for transmission to a suitable receiver apparatus for execution by a data processing apparatus. The computer-storage medium can be a machine-readable storage device, a machine-readable storage substrate, a random or serial access memory device, or a combination of computer-storage mediums.
The terms “data processing apparatus,” “computer,” and “electronic computer device” (or equivalent as understood by one of ordinary skill in the art) refer to data processing hardware. For example, a data processing apparatus can encompass all kinds of apparatuses, devices, and machines for processing data, including by way of example, a programmable processor, a computer, or multiple processors or computers. The apparatus can also include special purpose logic circuitry including, for example, a central processing unit (CPU), a field-programmable gate array (FPGA), or an application-specific integrated circuit (ASIC). In some implementations, the data processing apparatus or special purpose logic circuitry (or a combination of the data processing apparatus or special purpose logic circuitry) can be hardware- or software-based (or a combination of both hardware- and software-based). The apparatus can optionally include code that creates an execution environment for computer programs, for example, code that constitutes processor firmware, a protocol stack, a database management system, an operating system, or a combination of execution environments. The present disclosure contemplates the use of data processing apparatuses with or without conventional operating systems, such as LINUX, UNIX, WINDOWS, MAC OS, ANDROID, or IOS.
A computer program, which can also be referred to or described as a program, software, a software application, a module, a software module, a script, or code, can be written in any form of programming language. Programming languages can include, for example, compiled languages, interpreted languages, declarative languages, or procedural languages. Programs can be deployed in any form, including as stand-alone programs, modules, components, subroutines, or units for use in a computing environment. A computer program can, but need not, correspond to a file in a file system. A program can be stored in a portion of a file that holds other programs or data, for example, one or more scripts stored in a markup language document, in a single file dedicated to the program in question, or in multiple coordinated files storing one or more modules, subprograms, or portions of code. A computer program can be deployed for execution on one computer or on multiple computers that are located, for example, at one site or distributed across multiple sites that are interconnected by a communication network. While portions of the programs illustrated in the various figures may be shown as individual modules that implement the various features and functionality through various objects, methods, or processes, the programs can instead include a number of sub-modules, third-party services, components, and libraries. Conversely, the features and functionality of various components can be combined into single components as appropriate. Thresholds used to make computational determinations can be statically, dynamically, or both statically and dynamically determined.
The methods, processes, or logic flows described in this specification can be performed by one or more programmable computers executing one or more computer programs to perform functions by operating on input data and generating output. The methods, processes, or logic flows can also be performed by, and apparatus can also be implemented as, special purpose logic circuitry, for example, a CPU, an FPGA, or an ASIC.
Computers suitable for the execution of a computer program can be based on one or more of general and special purpose microprocessors and other kinds of CPUs. The elements of a computer are a CPU for performing or executing instructions and one or more memory devices for storing instructions and data. Generally, a CPU can receive instructions and data from (and write data to) a memory.
Graphics processing units (GPUs) can also be used in combination with CPUs. The GPUs can provide specialized processing that occurs in parallel to processing performed by CPUs. The specialized processing can include artificial intelligence (AI) applications and processing, for example. GPUs can be used in GPU clusters or in multi-GPU computing.
A computer can include, or be operatively coupled to, one or more mass storage devices for storing data. In some implementations, a computer can receive data from, and transfer data to, the mass storage devices including, for example, magnetic, magneto-optical disks, or optical disks. Moreover, a computer can be embedded in another device, for example, a mobile telephone, a personal digital assistant (PDA), a mobile audio or video player, a game console, a global positioning system (GPS) receiver, or a portable storage device such as a universal serial bus (USB) flash drive.
Computer-readable media (transitory or non-transitory, as appropriate) suitable for storing computer program instructions and data can include all forms of permanent/non-permanent and volatile/non-volatile memory, media, and memory devices. Computer-readable media can include, for example, semiconductor memory devices such as random access memory (RAM), read-only memory (ROM), phase-change memory (PRAM), static random access memory (SRAM), dynamic random access memory (DRAM), erasable programmable read-only memory (EPROM), electrically erasable programmable read-only memory (EEPROM), and flash memory devices. Computer-readable media can also include, for example, magnetic devices such as tape, cartridges, cassettes, and internal/removable disks. Computer-readable media can also include magneto-optical disks and optical memory devices and technologies including, for example, digital video disc (DVD), CD-ROM, DVD+/−R, DVD-RAM, DVD-ROM, HD-DVD, and BLU-RAY. The memory can store various objects or data, including caches, classes, frameworks, applications, modules, backup data, jobs, web pages, web page templates, data structures, database tables, repositories, and dynamic information. Types of objects and data stored in memory can include parameters, variables, algorithms, instructions, rules, constraints, and references. Additionally, the memory can include logs, policies, security or access data, and reporting files. The processor and the memory can be supplemented by, or incorporated into, special purpose logic circuitry.
Implementations of the subject matter described in the present disclosure can be implemented on a computer having a display device for providing interaction with a user, including displaying information to (and receiving input from) the user. Types of display devices can include, for example, a cathode ray tube (CRT), a liquid crystal display (LCD), a light-emitting diode (LED), and a plasma monitor. Display devices can include a keyboard and pointing devices, including, for example, a mouse, a trackball, or a trackpad. User input can also be provided to the computer through the use of a touchscreen, such as a tablet computer surface with pressure sensitivity or a multi-touch screen using capacitive or electric sensing. Other kinds of devices can be used to provide for interaction with a user, including to receive user feedback, including, for example, sensory feedback including visual feedback, auditory feedback, or tactile feedback. Input from the user can be received in the form of acoustic, speech, or tactile input. In addition, a computer can interact with a user by sending documents to, and receiving documents from, a device that the user uses. For example, the computer can send web pages to a web browser on a user's client device in response to requests received from the web browser.
The term “graphical user interface,” or “GUI,” can be used in the singular or the plural to describe one or more graphical user interfaces and each of the displays of a particular graphical user interface. Therefore, a GUI can represent any graphical user interface, including, but not limited to, a web browser, a touchscreen, or a command-line interface (CLI) that processes information and efficiently presents the information results to the user. In general, a GUI can include a plurality of user interface (UI) elements, some or all associated with a web browser, such as interactive fields, pull-down lists, and buttons. These and other UI elements can be related to or represent the functions of the web browser.
Implementations of the subject matter described in this specification can be implemented in a computing system that includes a back-end component, for example, as a data server, or that includes a middleware component, for example, an application server. Moreover, the computing system can include a front-end component, for example, a client computer having one or both of a graphical user interface or a Web browser through which a user can interact with the computer. The components of the system can be interconnected by any form or medium of wireline or wireless digital data communication (or a combination of data communication) in a communication network. Examples of communication networks include a local area network (LAN), a radio access network (RAN), a metropolitan area network (MAN), a wide area network (WAN), Worldwide Interoperability for Microwave Access (WIMAX), a wireless local area network (WLAN) (for example, using 802.11 a/b/g/n or 802.20 or a combination of protocols), all or a portion of the Internet, or any other communication system or systems at one or more locations (or a combination of communication networks). The network can communicate with, for example, Internet Protocol (IP) packets, frame relay frames, asynchronous transfer mode (ATM) cells, voice, video, data, or a combination of communication types between network addresses.
The computing system can include clients and servers. A client and server can generally be remote from each other and can typically interact through a communication network. The relationship of client and server can arise by virtue of computer programs running on the respective computers and having a client-server relationship.
Cluster file systems can be any file system type accessible from multiple servers for reading and updating. Locking or consistency tracking may not be necessary since the locking of exchange file system can be done at the application layer. Furthermore, Unicode data files can be different from non-Unicode data files.
While this specification contains many specific implementation details, these should not be construed as limitations on the scope of what may be claimed, but rather as descriptions of features that may be specific to particular implementations. Certain features that are described in this specification in the context of separate implementations can also be implemented, in combination, in a single implementation. Conversely, various features that are described in the context of a single implementation can also be implemented in multiple implementations, separately, or in any suitable sub-combination. Moreover, although previously described features may be described as acting in certain combinations and even initially claimed as such, one or more features from a claimed combination can, in some cases, be excised from the combination, and the claimed combination may be directed to a sub-combination or variation of a sub-combination.
Particular implementations of the subject matter have been described. Other implementations, alterations, and permutations of the described implementations are within the scope of the following claims, as will be apparent to those skilled in the art. While operations are depicted in the drawings or claims in a particular order, this should not be understood as requiring that such operations be performed in the particular order shown or in sequential order, or that all illustrated operations be performed (some operations may be considered optional), to achieve desirable results. In certain circumstances, multitasking or parallel processing (or a combination of multitasking and parallel processing) may be advantageous and performed as deemed appropriate.
Moreover, the separation or integration of various system modules and components in the previously described implementations should not be understood as requiring such separation or integration in all implementations. It should be understood that the described program components and systems can generally be integrated together in a single software product or packaged into multiple software products.
Accordingly, the previously described example implementations do not define or constrain the present disclosure. Other changes, substitutions, and alterations are also possible without departing from the spirit and scope of the present disclosure.
Furthermore, any claimed implementation is considered to be applicable to at least a computer-implemented method; a non-transitory, computer-readable medium storing computer-readable instructions to perform the computer-implemented method; and a computer system including a computer memory interoperably coupled with a hardware processor configured to perform the computer-implemented method or the instructions stored on the non-transitory, computer-readable medium.
