( 12 ) United States Patent
`Cavness et al .
`
`US 10,862,307 B2
`( 10 ) Patent No .:
`Dec. 8 , 2020
`( 45 ) Date of Patent :
`
`US010862307B2
`
`( * ) Notice :
`
`( 54 ) SYSTEMS AND METHODS FOR
`GENERATING AND CONSUMING POWER
`FROM NATURAL GAS
`( 71 ) Applicant : Crusoe Energy Systems Inc. , Denver ,
`CO ( US )
`( 72 ) Inventors : Charles Cavness , Denver , CO ( US ) ;
`Chase Lochmiller , Castle Rock , CO
`( US ) ; Kenneth Parker , Denver , CO
`( US )
`( 73 ) Assignee : Crusoe Energy Systems Inc. , Denver ,
`CO ( US )
`Subject to any disclaimer , the term of this
`patent is extended or adjusted under 35
`U.S.C. 154 ( b ) by 0 days .
`( 21 ) Appl . No .: 16 / 529,152
`Aug. 1 , 2019
`( 22 ) Filed :
`( 65 )
`Prior Publication Data
`US 2020/0040272 A1
`Feb. 6 , 2020
`Related U.S. Application Data
`( 60 ) Provisional application No. 62 / 713,368 , filed on Aug.
`1 , 2018 .
`( 51 ) Int . CI .
`H02J 3/38
`CIOL 3/10
`
`( 52 ) U.S. CI .
`CPC
`
`( 2006.01 )
`( 2006.01 )
`( Continued )
`HO2J 3/38 ( 2013.01 ) ; CIOL 3/104
`( 2013.01 ) ; E21B 43/16 ( 2013.01 ) ; GO6Q
`20/065 ( 2013.01 ) ;
`( Continued )
`( 58 ) Field of Classification Search
`CIOL 3/104 ; E21B 43/16 ; G06Q 20/065 ;
`CPC
`G06Q 2220/00 ; H02J 2300/10 ; HO2J
`3/40 ; HO2J 3/38 ; HO2J 3/381
`See application file for complete search history .
`
`110
`
`( 56 )
`
`References Cited
`U.S. PATENT DOCUMENTS
`7,998,227 B2
`8,070,863 B2
`
`8/2011 Mittricker
`12/2011 Tsangaris et al .
`( Continued )
`FOREIGN PATENT DOCUMENTS
`
`WO
`
`2013022501 A1
`
`2/2013
`
`OTHER PUBLICATIONS
`Bellusci , Michael : Why waste all that cheap Permian gas ? Make
`some bitcoins with it , Apr. 2018 , accessed Aug. 16 , 2019 at
`https://www.dallasnews.com/business/energy/2018/04/13/instead
`flaring - cheap - permian - natural - gas - could - used - power - bitcoin - mining
`rigs .
`BTU Analytics , Bitcoin to BTUs : Cryptocurrency Impacts on
`Natural Gas , Jan. 3 , 2018 , accessed Aug. 16 , 2019 at https : //
`btuanalytics.com/cryptocurrency-bitcoin-natural-gas/ .
`( Continued )
`
`Primary Examiner Carlos Amaya
`( 74 ) Attorney , Agent , or Firm -Zeller IP Group PLLC ;
`Kyle M. Zeller
`
`( 57 )
`ABSTRACT
`Systems and methods are provided to mitigate flaring of
`natural gas . A natural gas processing system may process
`raw natural gas into a fuel gas stream that may be used to
`power any number of on - site power generation modules . In
`turn , the power generation modules may convert the fuel gas
`stream into an electrical output , which may be employed to
`power any number of distributed computing units housed
`within one or more mobile data centers . In certain embodi
`ments , the distributed computing units may be adapted to
`mine cryptocurrency or perform other distributed computing
`tasks to generate revenue .
`
`20 Claims , 6 Drawing Sheets
`100 V
`
`101 WHA
`
`Natural Gas
`Processing
`System
`120
`
`102
`
`Electrical Power
`Generation
`System
`130
`
`105
`
`Distributed
`Computing
`System
`149
`
`181
`
`182
`
`183
`
`Network
`150
`
`Communication
`System
`165
`
`Monitoring &
`Control System
`180
`
`185
`
`Client Devices
`169
`
`Third - Party
`Systems
`170
`
`PGR2023-00039 - Upstream Data
`Ex. 2002 - Page 1
`
`

`

`US 10,862,307 B2
`Page 2
`
`( 2012.01 )
`( 2006.01 )
`( 2006.01 )
`
`OTHER PUBLICATIONS
`Emmanuel , Ogwu Osaemezu : Texas Oil Producers Could Channel
`Excess Gas into Bitcoin Mining Operations , Apr. 21 , 2018 , BTC
`Manager , accessed Aug. 16 , 2019 at https://btcmanager.com/texas
`oil - producers - could - channel - excess - gas - into - bitcoin - mining
`operations .
`International Search Report and Written Opinion issued for PCT /
`US2019 / 44646 , dated Oct. 11 , 2019 , 8 pp .
`Ray , Shaan : Cryptocurrency Strategies for Power and Energy Com
`panies , Oct. 15 , 2017 , Medium , accessed Aug. 16 , 2019 at https : //
`techburst.io/cryptocurrency-strategies-for-power-and-energy-companies
`198d0188e7da .
`Wilmoth , Josiah : Pipe Dream : Analysts Mull Natural Gas - Powered
`Bitcoin Mining Operation , Apr. 16 , 2018 , CCN , accessed Aug. 16 ,
`2019 at https://www.ccn.com/pipe-dream-analysts-mull-natural-gas
`powered - bitcoin - mining - operation / .
`York , Larrie : Generator Ratings Explained , Frontier Power Prod
`ucts , Jan. 2016 , accessed Aug. 16 , 2019 at http://frontierpower.com/
`wp - content / uploads / 2016 / 01 / Generator - Ratings - Explained - by - Larrie
`York.pdf .
`* cited by examiner
`
`( 51 ) Int . Ci .
`GO6Q 20/06
`E21B 43/16
`HO2J 3/40
`( 52 ) U.S. CI .
`CPC
`
`( 56 )
`
`HO2J 3/40 ( 2013.01 ) ; G06Q 2220/00
`( 2013.01 ) ; HO2J 2300/10 ( 2020.01 )
`References Cited
`U.S. PATENT DOCUMENTS
`9,337,704 B1
`5/2016 Leslie et al .
`9,637,433 B2
`5/2017 Zubrin et al .
`9,673,632 B1
`6/2017 Ramesh et al .
`8/2017 Young et al .
`9,719,024 B2
`2011/0115425 A1
`5/2011 Olsson
`12/2014 McKnight et al .
`2014/0372772 A1
`8/2017 Oehring et al .
`2017/0218843 A1
`2017/0271701 Al
`9/2017 Berlowitz et al .
`2018/0109112 Al
`4/2018 Paine et al .
`2019/0022580 A1
`1/2019 Muhsen
`2020/0006938 A1 *
`1/2020 Torvund
`2020/0051184 A1 *
`2/2020 Barbour
`
`HO2J 3/00
`HO4L 67/104
`
`PGR2023-00039 - Upstream Data
`Ex. 2002 - Page 2
`
`

`

`U.S. Patent
`
`Dec. 8 , 2020
`
`2
`
`Sheet 1 of 6
`
`US 10,862,307 B2
`
`110
`
`100
`
`101
`WH
`
`Natural Gas
`Processing
`System
`120
`
`102
`
`Electrical Power
`Generation
`System
`130
`
`105
`
`Distributed
`Computing
`System
`140
`
`181
`
`182
`
`183
`
`Network
`150
`
`Communication
`System
`155
`
`Monitoring &
`Control System
`180
`
`185
`
`Client Devices
`160
`
`Third - Party
`Systems
`170
`
`FIG . 1
`
`PGR2023-00039 - Upstream Data
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`
`

`

`U.S. Patent
`
`Dec. 8 , 2020
`
`Sheet 2 of 6
`
`US 10,862,307 B2
`
`202
`
`297
`
`296
`
`295
`
`294
`
`FIG . 2
`
`| Refrigeration Module 230
`Dehydrator Module 226
`Desulfurization Module 224
`
`CO2 Removal Module 222
`Compressor Module 215
`Separator Module 210
`HX1201
`HD
`
`293
`
`292
`
`291
`
`200
`
`209
`
`PGR2023-00039 - Upstream Data
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`

`

`U.S. Patent
`
`Dec. 8 , 2020
`
`2
`
`Sheet 3 of 6
`
`US 10,862,307 B2
`
`300
`
`305
`
`Electrical
`Transformation
`Module
`335
`
`303
`
`Power
`Generation
`Module
`331
`
`302
`
`Fuel Gas Supply Line
`320
`
`FIG . 3
`
`308
`
`Backup Fuel
`Supply
`337
`
`PGR2023-00039 - Upstream Data
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`
`

`

`U.S. Patent
`
`Dec. 8 , 2020
`
`2
`
`Sheet 4 of 6
`
`US 10,862,307 B2
`
`400
`
`405
`
`Electrical
`Transformation
`Module
`435
`
`404
`
`Parallel Panel
`460
`
`408
`
`Backup Fuel
`Supply
`437
`
`Fuel Gas Supply Line
`420
`
`FIG . 4
`
`403a
`
`Power
`Generation
`Module
`431a
`
`402
`
`403b
`
`Power
`Generation
`Module
`431b
`
`402
`
`PGR2023-00039 - Upstream Data
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`
`

`

`U.S. Patent
`
`Dec. 8 , 2020
`
`2
`
`Sheet 5 of 6
`
`US 10,862,307 B2
`
`500
`
`Mobile Data Center
`510
`
`Monitoring &
`Control
`System
`580
`
`Comm .
`System
`555
`
`Mobile Data Center
`
`Monitoring &
`Control
`System
`
`Comm .
`System
`
`DCUS
`520
`
`DCUS
`
`Power
`System
`530
`
`Backup
`Power
`System
`540
`
`Power
`System
`
`Backup
`Power
`System
`
`505
`
`505
`
`FIG . 5
`
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`

`

`U.S. Patent
`
`Dec. 8 , 2020
`
`2
`
`Sheet 6 of 6
`
`US 10,862,307 B2
`
`600
`
`Processor
`610
`
`Network Interface
`660
`
`System Bus
`670
`
`System Memory
`620
`
`Storage Media
`640
`
`Input / Output
`Interface
`680
`
`Modules
`650
`
`FIG . 6
`
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`

`

`US 10,862,307 B2
`
`15
`
`1
`SYSTEMS AND METHODS FOR
`GENERATING AND CONSUMING POWER
`FROM NATURAL GAS
`
`2
`“ Major Source Emitter ” rules . Violations of state or federal
`rules can result in oil wells being “ shut in , ” rejected permits
`and / or significant cash fines .
`Stranded natural gas , particularly in the case where liq
`5 uids - weighted wells are shut in due to gas takeaway con
`CROSS - REFERENCE TO RELATED
`straints , represents a very low - cost power generation oppor
`APPLICATIONS
`tunity . Stranded gas exists across most prominent shale
`The present application claims benefit of U.S. provisional
`fields today including in the D - J Basin , Permian Basin ,
`patent application No. 62 / 713,368 , titled “ Systems and
`Bakken , SCOOP / STACK , etc. Many oil and gas operators in
`Methods for Generating and Consuming Power from Natu- 10 pipeline - constrained environments readily offer their natural
`ral Gas , ” filed Aug. 1 , 2018 , which is incorporated by
`gas for low cost - even at a loss to the operator in some
`reference herein in its entirety .
`so that they can produce oil , which often represents
`cases
`the vast majority of a well's lifetime economics .
`BACKGROUND
`One potential solution to the natural gas problem lies in
`distributed computing . Cryptocurrency is a booming asset
`This specification relates to enabling the utilization of raw
`class with the combined market capitalization of digital
`natural gas , such as flare gas , stranded gas , and associated
`gas for power generation . More specifically , the specifica-
`currencies surpassing $ 380 billion in July 2018. Cryptocur
`tion relates to on - site generation of electricity from natural
`rencies operate on a distributed system of computers “ min
`gas to power modular processing units adapted to perform 20 ing ” the currencies essentially processing the underlying
`algorithms to continuously verify transactions and account
`distributed computing tasks .
`Extracting oil from unconventional resources , such as
`balances . The crypto mining process is a significant industry
`shale gas formations , through the combination of horizontal
`in its own right , projected to reach a value of $ 39 billion by
`drilling and hydraulic fracturing has increased at a rapid
`2025 with a projected CAGR of 29.7 % .
`pace in recent years . The Bakken , Powder River Basin , 25
`This high - growth industry requires innovative and inex
`Denver Julesburg ( “ D - J ” ) Basin , North Park Basin , and
`pensive electricity sources as it requires enormous amounts
`Permian Basin are just some of the important “ plays ” in the
`of power — approximately 29 TWh of electricity per year on
`United States . A “ play ” is the geographic area underlain by
`a global basis . For perspective , cryptocurrency mining con
`a gas- or oil - containing geologic formation .
`sumes more power annually than 159 countries , including
`Development of these gas plays and other unconventional 30 Hungary , Ireland , Nigeria or Slovakia . Indeed , electricity is
`resources presents significant potential for economic devel
`typically the single largest lifetime cost to a cryptocurrency
`opment and energy independence , but also presents the
`mining operation , with power costs offsetting approximately
`potential for environmental impacts on
`nd , water and air .
`30 % of total mining revenues in the US .
`For example , although oil production represents the most
`Accordingly , there remains a need for systems and meth
`important source of revenue for a given well , most wells also 35
`ods for generating electricity from natural gas produced
`produce natural gas as a low - value byproduct . Unfortu
`from oil wells . It would be beneficial if such electricity could
`nately , the liquids - rich natural gas byproduct often cannot be
`economically transported by trucks or trains from remote
`be produced and consumed on - site , for example , by using it
`well locations . Although such natural gases could be trans-
`to operate power - intensive , modular processing units . It
`ported via pipelines , many oil and natural gas wells are 40 would be further beneficial if such processing units could be
`located beyond the reach of such infrastructure . Absent gas
`employed to mine cryptocurrency or perform other distrib
`pipeline infrastructure , oil well operators must either “ vent ”
`uted computing tasks to generate additional revenue .
`or “ flare ” produced gasses for safety reasons . Venting is the
`controlled release of natural gases into the atmosphere in the
`SUMMARY
`course of oil and gas production operations , however natural 45
`gas accumulations around the wellbore create significant
`In accordance with the foregoing objectives and others ,
`safety hazards . Flaring is the controlled burning of natural
`exemplary systems and methods are disclosed herein to
`gas produced in association with oil in the course of routine
`convert raw natural gas into a fuel gas stream that may be
`oil and gas production operations , and is designed to mini-
`used to power any number of on - site power generation
`mize the safety and environmental risks associated with 50 modules . In turn , the power generation modules may convert
`the fuel gas stream into electricity , which may be employed
`venting uncombusted natural gas .
`As of April 2016 , the NOAA estimates that there are over
`to power any number of modular distributed computing
`6,200 individual flares in the United States , which burn
`units . In certain embodiments , the distributed computing
`about 35 billion ft3 of natural gas annually enough to
`units may be adapted to mine cryptocurrency or perform
`supply about 6 million homes . Such large - scale flaring of 55 other distributed computing tasks to generate revenue .
`natural gas has raised serious environmental and health
`In one embodiment , a flare mitigation system is provided .
`concerns and various state and federal regulators have begun
`Such system may include an electrical power generation
`to take action by implementing strict regulations and
`system , which may include a power generation module
`enforcement policies . For example , Colorado generally lim-
`adapted to : receive a fuel gas stream , such as a fuel gas
`its flaring to 60 days and many new well permits require 60 associated with a heat value of at least about 1,000 Btu / scf ;
`producers to have a natural gas offtake solution prior to
`and consume the fuel gas stream to generate a high - voltage
`production ; North Dakota has recently implemented a
`electrical output associated with a first voltage . The electri
`requirement that 90 % of associated gas be captured by 2020 ;
`cal power generation system may also include an electrical
`and Texas only allows new wells to flare for 10 days before
`transformation module in electrical communication with the
`an additional 45 - day permit must be obtained . The EPA has 65 power generation module , the electrical transformation
`also implemented flaring regulations where sites that exceed
`module adapted to : receive the high - voltage electrical output
`100 tons per year of VOC , CO or NOX trigger Title V generated by the power generation module ; and transform
`
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`US 10,862,307 B2
`
`3
`4
`satellite antennas in order to provide a network . Moreover ,
`the high - voltage electrical output into a low - voltage electri-
`the distributed computing system may include a first mobile
`cal output associated with a second voltage that is lower than
`the first voltage .
`data center having an enclosure defining an interior space ; a
`plurality of distributed computing units located within the
`The flare mitigation system may also include a distributed
`computing system powered by the electrical power genera- 5 interior space of the enclosure , each of the plurality of
`tion system . The distributed computing system may include
`distributed computing units in communication with the
`a communications system with one or more data satellite
`network ; and a power system located at least partially within
`antennas in order to provide a network ; and a first mobile
`the interior space of the enclosure , the power system in
`data center . The mobile data center may include an enclosure
`electrical communication with the electrical transformation
`defining an interior space ; a plurality of distributed comput- 10 module and the plurality of distributed computing units such
`ing units located within the interior space of the enclosure ,
`that the power system receives the low - voltage electrical
`each of the plurality of distributed computing units in
`output and powers each of the plurality of distributed
`communication with the network ; and a power system
`computing units .
`located at least partially within the interior space of the
`The details of one or more embodiments of the subject
`enclosure , the power system in electrical communication 15 matter of this specification are set forth in the accompanying
`with the electrical transformation module and the plurality
`drawings and the description below . Other features , aspects ,
`of distributed computing units such that the power system
`and advantages of the subject matter will become apparent
`receives the low - voltage electrical output and powers each
`from the description , the drawings , and the claims .
`of the plurality of distributed computing units .
`In some cases , the power generation module may be an 20
`BRIEF DESCRIPTION OF THE DRAWINGS
`engine - type generator that generates a high - voltage electri
`cal output of from about 70 kW to about 2 MW ( e.g. , from
`FIG . 1 shows an exemplary flare mitigation system 100
`according to an embodiment .
`about 70 kW to about 300 kW , from about 300 kW to about
`400 kW , 400 kW to about 1 MW , or from about 1 MW to
`FIG . 2 shows an exemplary natural gas processing system
`about 2 MW ) . The first voltage of the high - voltage electrical 25 200 according to an embodiment .
`output may be from about 480 V to about 4.16 kV . And the
`FIG . 3 shows an exemplary electrical power generation
`second voltage of the low - voltage electrical output may be
`system 300 comprising a power generation module 331 in
`from about 208 V to about 240 V.
`electrical communication with an electrical transformation
`In other cases , the power generation module may be a
`module 335 .
`FIG . 4 shows another exemplary electrical power genera
`turbine - type generator that generates a high - voltage electri- 30
`cal output of from about 2 MW to about 30 MW . In such
`tion system 400 comprising a plurality of power generation
`cases , the first voltage of the high - voltage electrical output
`modules ( 431a , 431b ) in electrical communication with an
`may be from about 4.16 kV to about 12 kV . And the second
`electrical transformation module 435 via a parallel panel
`voltage of the low - voltage electrical output may be from
`460 .
`FIG . 5 shows an exemplary distributed computing system
`about 208 V to about 240 V.
`In another embodiment , a flare mitigation system is
`500 according to an embodiment .
`FIG . 6 shows an exemplary computing machine 600 and
`provided . The system may include an electrical power
`generation system having a first power generation module
`modules 650 according to an embodiment .
`and a second power generation module . The first power
`generation module may be adapted to receive a first fuel gas 40
`DETAILED DESCRIPTION
`stream , such as a fuel gas associated with a heat value of at
`least about 1,000 Btu / scf , and to consume the fuel gas stream
`System Overview
`to generate a first high - voltage electrical output associated
`Referring to FIG . 1 , an exemplary flare mitigation system
`with a first voltage . The second power generation module
`100 according to an embodiment is illustrated . As shown ,
`may be adapted to receive a second fuel gas stream including 45 the system 100 may comprise a natural gas processing
`the fuel gas , and to consume the second fuel gas stream to
`system 120 , an electrical power generation system 130 , a
`generate a second high - voltage electrical output associated
`distributed computing system 140 , a communication system
`with the first voltage .
`155 and a monitoring and control system 180 .
`The electrical power generation system may also include
`In one embodiment , the flare mitigation system 100 may
`a parallel panel in electrical communication with the first 50 comprise a natural gas processing system 120 adapted to
`power generation module and the second power generation
`receive a raw natural gas stream 101 from one or more
`module . The parallel panel may be adapted to receive the
`wellheads 110 in an oil and / or gas reservoir . The natural gas
`first and second high - voltage electrical outputs ; and combine
`processing system 120 is generally adapted to convert the
`and / or synchronize the first and second high - voltage elec-
`received raw natural gas 101 into a fuel gas stream 102 that
`trical outputs into a combined high - voltage electrical output . 55 may be introduced to an electrical power generation system
`The electrical power generation system may also include
`130. As discussed in detail below with respect to FIG . 2 , the
`an electrical transformation module in electrical communi-
`natural gas processing system 120 may employ a separator
`cation with the parallel panel . The electrical transformation
`module and , optionally , any number of additional modules
`module may be adapted to receive the combined high-
`( e.g. , a compressor module , a carbon dioxide removal mod
`voltage electrical output ; and transform the combined high- 60 ule , a desulfurization module and / or a refrigeration module )
`voltage electrical output into a low - voltage electrical output
`to produce a fuel gas stream 102 meeting the specific
`associated with a second voltage that is lower than the first
`requirements of the electrical power generation system 130
`voltage .
`and any number of secondary streams .
`The flare mitigation system may further include a distrib-
`The electrical power generation system 130 generally
`uted computing system powered by the electrical power 65 comprises any number of power generation modules adapted
`generation system . The distributed computing system may
`to consume the fuel gas 102 and convert the same into
`include a communications system having one or more data
`electrical power . As discussed in detail below with respect to
`
`35
`
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`US 10,862,307 B2
`
`5
`6
`mobile data centers and / or may be pole - mounted into the
`FIGS . 3-4 , each power generation module may be in elec-
`ground nearby such mobile data centers . A typical configu
`trical communication with an electrical transformation mod-
`ration is for two antennas to serve a single mobile data center
`ule adapted to receive the electrical output of the power
`in order to provide reliability and redundancy ; however , a
`generation module ( s ) and convert the same into an electrical
`flow 105 that may be employed to power the electrical 5 single antenna may be sufficient depending on bandwidth
`components of a distributed computing system 140 .
`requirements and total DCU count . Alternatively , many
`In one embodiment , the distributed computing system 140
`( e.g. , three or more ) antennas may be mounted to a roof of
`may comprise any number distributed computing units
`a single mobile data center , and communications cables may
`( “ DCUs ” ) in electrical communication with the electrical
`extend from the mobile data center to other nearby mobile
`power generation system 130 , such that the DCUs are 10 data centers to provide a centralized communications solu
`powered via the electrical flow 105 output by the system .
`tion .
`The DCUs may comprise a modular computing installation ,
`The one or more data satellite antennas of the communi
`for example , a data center , cryptocurrency mine or graphics
`cation system 155 may be specified for continuous outdoor
`computing cell . And the DCUs are generally adapted to
`conduct any number of processing - intensive tasks . For 15 use , and may be installed using robust mounting hardware to
`ensure alignment even during heavy wind or other storms
`example , the DCUs may be employed to execute graphics
`common in the oilfield . Antenna modems may be housed
`intensive distributed computing processes , artificial intelli
`gence ( " AI " ) research , machine learning model training ,
`inside a mobile data center for warmth , security and weath
`data analysis , server functions , storage , virtual reality and / or
`erproofing , and such modems may be connected to the
`augmented reality applications , tasks relating to the Golem 20 power system of the mobile data center .
`Project , non - currency blockchain applications and / or cryp-
`In one embodiment , the communication system 155 may
`tocurrency mining operations .
`provide an internal network that includes automatic load
`In certain embodiments , the DCUs may be employed to
`balancing functionality such that bandwidth is allocated
`execute mathematical operations in relation to the mining of
`proportionately among all active antennas . In such embodi
`cryptocurrencies including computing the following hashing 25 ment , if a single antenna fails , the lost bandwidth is auto
`algorithms : SHA - 256 , ETHash , scrypt , CryptoNight , RIP-
`matically redistributed among all functioning antennas . This
`EMD160 , BLAKE256 , X11 , Dagger - Hashimoto , Equihash ,
`is an important reliability feature for oilfield operations ,
`LBRY , X13 , NXT , Lyra2RE , Qubit , Skein , Groest1 , BOINC ,
`where equipment failures due to storms are possible .
`X1 Igost , Scrypt - jane , Quark , Keccak , Scrypt - OG , X14 ,
`In another embodiment , the antennas and satellite internet
`Axiom , Momentum , SHA - 512 , Yescrypt , Scrypt - N , Cun- 30 systems of the communication system 155 may be specified
`Fresh , AES ,
`2Skein , Equilhash ,
`based on the needs of the distributed computing system 140 ,
`ningham , NISTS ,
`Fresh ,
`KSHAKE320 , Sidechain , Lyra2RE , HybridScryptHash256 ,
`with specific attention paid to bandwidth and latency
`Momentum , HEFTY1 , Skein - SHA2 , Qubit , SpreadX11 ,
`requirements . For lower bandwidth applications such as
`Pluck , and / or Fugue256 . Additionally or alternatively , the
`certain blockchain processing , cryptocurrency mining and /
`DCUs may be adapted to execute mathematical operations 35 or long - term bulk data processing jobs , high - orbit satellite
`in relation to training computationally intensive machine
`connectivity ranging from 10 MB / s to 100 MB / s may be
`learning , artificial intelligence , statistical or deep learning
`specified . For higher bandwidth or low latency requirements
`models , such as neural networks , recurrent neural networks ,
`such as artificial intelligence model training , iterative dataset
`convolutional neural networks , generative adversarial net-
`download and boundary spamming projects , visual process
`works , gradient boosting machines , random forests , classi- 40 ing such as images or videos , natural language processing ,
`fication and regression trees , linear , polynomial , exponential
`iterative protein folding simulation jobs , videogaming , or
`and generalized linear regressions , logistic regression , rein-
`any other high capacity data streaming or rapid communi
`forcement learning , deep reinforcement learning , hyperpa-
`cation jobs , low - orbit satellites may be specified to provide
`rameter optimization , cross validation , support vector
`significantly increased speeds and reduced latency .
`machines , principal component analysis , singular value 45
`In any event , the communication system 155 may provide
`decomposition , convex optimization , and / or independent
`a network 150 to which various components of the flare
`component analysis .
`mitigation system 100 may be connected . The network 150
`As discussed in detail below with respect to FIG . 5 , the
`may include wide area networks ( “ WAN ” ) , local area net
`distributed computing system 140 may comprise one or
`works ( “ LAN ” ) , intranets , the Internet , wireless access net
`more mobile data centers , wherein each mobile data center 50 works , wired networks , mobile networks , telephone net
`houses a plurality of DCUs therein . In addition to the DCUS ,
`works , optical networks , or combinations thereof . The
`each mobile data center may further house an electrical
`network 150 may be packet switched , circuit switched , of
`power system , one or more backup power systems , an
`any topology , and may use any communication protocol .
`environment control system , and / or various monitoring and
`Communication links within the network 150 may involve
`control equipment 183 .
`55 various digital or an analog communication media such as
`In certain embodiments , the mobile data center ( and any
`fiber optic cables , free - space optics , waveguides , electrical
`electronic components contained therein ) may be in com-
`conductors , wireless links , antennas , radio - frequency com
`munication with a communication system 155. For example ,
`munications , and so forth .
`the mobile data center may be in direct communication with
`As shown , the flare mitigation system further 100 com
`the communication system 155 via a wired connection . As 60 prises a MC system 180 , which is generally adapted to
`another example , the DCUs may be in indirect communi-
`maintain processing conditions within acceptable opera
`cation with the communication system 155 via a network
`tional constraints throughout the system . Such constraints
`may be determined by economic , practical , and / or safety
`150 .
`In one embodiment , the communication system 155 may
`requirements . The MC system 180 may handle high - level
`comprise one or more data satellite antennas in communi- 65 operational control goals , low - level PID loops , communi
`cation with one or more high - orbit and / or low - orbit satel-
`cation with both local and remote operators , and communi
`lites . The antennas may be roof - mounted to one or more
`cation with both local and remote systems . The MC system
`
`PGR2023-00039 - Upstream Data
`Ex. 2002 - Page 11
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`US 10,862,307 B2
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`7
`8
`environment . Such software may correspond to a file in a file
`180 may also be in communication with ancillary systems ,
`system . A program can be stored in a portion of a file that
`such as storage systems , backup systems and / or power
`generation systems .
`holds other programs or data . For example , a program may
`include one or more scripts stored in a markup language
`In one embodiment , the MC system 180 may be in
`communication with various monitoring and control equip- 5 document ; in a single file dedicated to the program in
`ment ( 181-183 ) , such as sensors and / or controllers , via the
`question ; or in multiple coordinated files ( e.g. , files that store
`network 150. Such monitoring and control equipment ( 181-
`one or more modules , sub programs , or portions of code ) .
`183 ) may be in further communication with various com-
`Each of the MC system application ( s ) and / or distributed
`ponents of the natural gas processing system 120 , the
`computing system application ( s ) can be deployed and / or
`electrical power generation system 130 and / or the distrib- 10 executed on one or more computing machines that are
`uted computing system 140 , such that the MC system 18Q
`located at one site or distributed across multiple sites and
`may remotely monitor and control operating parameters
`interconnected by a communication network . In one
`throughout the flare mitigation system 100. Exemplary
`embodiment , an application may be installed on ( or accessed
`operating parameters may include , but are not limited to ,
`by ) one or more client devices 160 .
`profile of the raw natural gas supply , gas flow rate at various 15
`In certain embodiments , the MC system 180 and / or the
`locations , gas pressure at various locations , temperature at
`client device 160 may be adapted to receive , determine ,
`various locations , electrical output at one or more locations ,
`record and / or transmit application information relating to
`electrical load at one or more locations , and / or others .
`one or more components of the flare mitigation system 100 .
`As an example , the MC system 180 may determine a
`The application information may be received from and / or
`change in the profile , flow rate and / or pressure of the raw 20 transmitted to the natural gas processing system 120 , the
`natural gas 101 and then automatically modulate electrical
`electrical power generation system 130 and / or the distrib
`Iload of a mobile data center accordingly . And as another
`uted computing system 140 via , for example , monitoring
`example , the MC system 180 may automatically reduce a
`and / or control equipment ( 181 , 182 , 183 , respectively ) in
`processing rate of one or more DCUs in response to receiv-
`communication with one or more components of such
`ing an indication that supply gas pressure has decreased .
`25 systems and in further communication with the network 150 .
`In one embodiment , any number of users may access the
`Moreover , any of such application information may be
`