| 序号 | 专利名 | 申请号 | 申请日 | 公开（公告）号 | 公开（公告）日 | 发明人 |
|---|---|---|---|---|---|---|
| 81 | MOBILE PRESSURE OPTIMIZATION UNIT FOR DRILLING OPERATIONS | EP11865460.7 | 2011-05-16 | EP2710216A1 | 2014-03-26 | LOVORN, James, R.; WHITTAKER, Malcolm, E.; LEWIS, Derrick, W. |
| A well drilling method can include transporting a pressure optimization unit to a rig site, the pressure optimization unit including a choke manifold, a control system which automatically controls operation of the choke manifold, and a flowmeter which measures flow of drilling fluid through the choke manifold, and then interconnecting the pressure optimization unit to rig drilling equipment. A pressure optimization unit for use with a well drilling system can include a choke manifold, a control system which automatically controls operation of the choke manifold, and a flowmeter which measures flow of drilling fluid through the choke manifold. The choke manifold, control system and flowmeter may be incorporated into a same conveyance which transports the pressure optimization unit to a rig site. | ||||||
| 82 | METHODS, SYSTEMS, AND COMPUTER-READABLE MEDIA FOR REAL-TIME OIL AND GAS FIELD PRODUCTION OPTIMIZATION USING A PROXY SIMULATOR | EP07762832.9 | 2007-01-31 | EP1982046B1 | 2011-03-30 | CULLICK, Alvin, Stanley; JOHNSON, William, Douglas |
| Methods, systems, and computer readable media are provided for real-time oil and gas field production optimization using a proxy simulator. A base model (30) of a reservoir (100), well (100), pipeline network (100), or processing system (100) is established in one or more physical simulators (26). A decision management system (24) is used to define control parameters, such as valve settings (410), for matching with observed data (114). A proxy model is used to fit the control parameters to outputs of the physical simulators (26), determine sensitivities of the control parameters, and compute correlations between the control parameters and output data from the simulators (26). Control parameters for which the sensitivities are below a threshold are eliminated. The decision management system (24) validates control parameters which are output from the proxy model in the simulators (26). The proxy model may be used for predicting future control settings for the control parameters. | ||||||
| 83 | ARTIFICIAL NEURAL NETWORK MODELS FOR DETERMINING RELATIVE PERMEABILITY OF HYDROCARBON RESERVOIRS | EP08795723.9 | 2008-08-27 | EP2198121A1 | 2010-06-23 | AL-FATTAH, Saud Mohammad, A. |
| A system and method for modeling technology to predict accurately water-oil relative permeability uses a type of artificial neural network (ANN) known as a Generalized Regression Neural Network (GRNN) The ANN models of relative permeability are developed using experimental data from waterflood core test samples collected from carbonate reservoirs of Arabian oil fields Three groups of data sets are used for training, verification, and testing the ANN models Analysis of the results of the testing data set show excellent correlation with the experimental data of relative permeability, and error analyses show these ANN models outperform all published correlations | ||||||
| 84 | METHODS, SYSTEMS, AND COMPUTER-READABLE MEDIA FOR REAL-TIME OIL AND GAS FIELD PRODUCTION OPTIMIZATION USING A PROXY SIMULATOR | EP07762832.9 | 2007-01-31 | EP1982046A1 | 2008-10-22 | CULLICK, Alvin, Stanley; JOHNSON, William, Douglas |
| Methods, systems, and computer readable media are provided for real-time oil and gas field production optimization using a proxy simulator. A base model (30) of a reservoir (100), well (100), pipeline network (100), or processing system (100) is established in one or more physical simulators (26). A decision management system (24) is used to define control parameters, such as valve settings (410), for matching with observed data (114). A proxy model is used to fit the control parameters to outputs of the physical simulators (26), determine sensitivities of the control parameters, and compute correlations between the control parameters and output data from the simulators (26). Control parameters for which the sensitivities are below a threshold are eliminated. The decision management system (24) validates control parameters which are output from the proxy model in the simulators (26). The proxy model may be used for predicting future control settings for the control parameters. | ||||||
| 85 | METHOD AND APPARATUS FOR DOWNHOLE FLUID CHARACTERIZATION USING FLXURAL MECHANICAL RESONATORS | EP02751971.9 | 2002-05-14 | EP1397661B1 | 2008-09-10 | ROCCO, DiFoggio |
| The present invention provides a downhole method and apparatus using flexural mechanical resonator, for example, a tuning fork (410) to provide real-time direct measurements and estimates of the viscosity, density and dielectric constant of formation fluid or filtrate in a hydrocarbon producing well. The present invention additionally provides a method and apparatus for monitoring cleanup from a leveling off of viscosity or density over time, measuring or estimating bubble point for formation fluid, measuring or estimating dew point for formation fluid, and determining the onset of asphaltene precipitation. The present invention also provides for intercalibration of plural pressure gauges used to determine a pressure differential downhole. | ||||||
| 86 | Méthode pour former un module à réseaux neuronaux optimisé, destiné à simuler le mode d'écoulement d'une veine de fluides polyphasiques | EP01402991.2 | 2001-11-22 | EP1217474B1 | 2008-03-26 | Rey-Fabret, Isabelle; Duret, Emmanuel; Heintze, Eric; Henriot, Véronique |
| 87 | AUTONOMOUS DOWNHOLE OILFIELD TOOL | EP97944386.8 | 1997-09-23 | EP0862682B1 | 2005-12-21 | TUBEL, Paulo; ANGLE, Colin, M.; MCINTYRE, Thomas, W.; JOHNSON, Jeffrey, E. |
| An autonomous downhole oilfield tool having its own mobility and decision making capability so that it may be deployed in a downhole environment to monitor and control said environment by modifying operations of other devices and maintaining downhole structures. | ||||||
| 88 | FORMATION TESTING APPARATUS AND METHOD | EP99909756.1 | 1999-03-03 | EP1064452B1 | 2005-12-07 | BERGER, Per, Erik; REIMERS, Nils; MACUNE, Don, Thorton |
| An apparatus and method for obtaining samples of pristine formation or formation fluid, using a work string designed for performing other downhole work such as drilling, workover operations, or re-entry operations. An extendible element extends against the formation wall to obtain the pristine formation or fluid sample. While the test tool is in a standby condition, the extendible element is withdrawn within the work string, protected by other structure from damage during operation of the work string. The apparatus is used to sense or sample downhole conditions while using a work string, and the measurements or samples taken can be used to adjust working fluid properties without withdrawing the work string from the bore hole. When the extendible element is a packer, the apparatus can be used to prevent a kick from reaching the surface, adjust the density of the drilling fluid, and thereafter continuing use of the work string. The test apparatus can be mounted on a sliding, non-rotating, sleeve on the work string. | ||||||
| 89 | SPECTRAL POWER RATIO METHOD AND SYSTEM FOR DETECTING DRILL BIT FAILURE AND SIGNALING SURFACE OPERATOR | EP01993745 | 2001-11-07 | EP1340069A4 | 2005-04-13 | SCHULTZ ROGER L; DE JESUS ORLANDO; OSBORNE ANDREW J JR |
| 90 | Method for controlling the development of an oil or gas reservoir | EP98303548.6 | 1998-05-06 | EP0881357B1 | 2004-10-27 | Stephenson, Stanley V. |
| 91 | FIELD/RESERVOIR OPTIMIZATION UTILIZING NEURAL NETWORKS | EP01274015.5 | 2001-03-21 | EP1381921A1 | 2004-01-21 | STORM, Bruce, H., Jr.; SCHULTZ, Roger, L.; DENNIS, John, R.; RICHARDSON, John, M. |
| A method of optimizing performance of a well system utilizes a neural network. In a described embodiment, the method includes the step of accumulating data indicative of the performance of the well system in response to variable influencing parameters. The data is used to train a neural network to model an output of the well system in response to the influencing parameters. An output of the neural network may then be input to a valuing model, e.g., to permit optimization of a value of the well system. The optimization process yields a set of prospective influencing parameters which may be incorporated into the well system to maximize its value. | ||||||
| 92 | VERFAHREN ZUR STEUERUNG EINES HORIZONTALBOHRGERÄTES | EP99953710.3 | 1999-08-31 | EP1117901B1 | 2003-12-03 | JACUBASCH, Andreas; KUNTZE, Helge-Björn; BAYER, Hans-Joachim |
| The present invention relates to a control mechanism for a horizontal drilling machine that uses a drilling rod (2) to drive a drilling lance (1). The control mechanism is provided with an input interface for receiving actual values of control variables of the horizontal drilling machine and fitted with an output unit that emits control signals to control said horizontal drilling machine. A fuzzy regulator (7) is arranged between the input interface and the output unit. Said regulator determines the control signals that control the horizontal drilling machine on the basis of the actual values of the control variables and the desired values for the control variables, using fuzzy logic and taking heuristic process values into account. The control mechanism enables a horizontal drilling device to be operated automatically and provides good line guidance and target accuracy. | ||||||
| 93 | INTERNAL POWER SOURCE FOR DOWNHOLE DETECTION SYSTEM | EP01994177.2 | 2001-11-07 | EP1350309A2 | 2003-10-08 | SCHULTZ, Roger, L.; DE JESUS, Orlando; OSBORNE, Andrew, J., Jr. |
| A drill string is equipped with a downhole assembly having an instrumented sub and a drill bit (108). The instrumented sub (104) has a power source that requires no electrical chemical batter. A mass-spring system is used, which during drilling causes a magnet to oscillate past a coil. This induces current which is used to power downhole instruments. | ||||||
| 94 | Method and apparatus for prediction control in drilling dynamics using neural network | EP01308364.7 | 2001-10-01 | EP1193366A3 | 2002-10-09 | MacDonald, Robert P.; Krueger, Volker; Dubinsky, Vladimir; MacPherson, John D. |
The present invention provides a drilling system that utilizes a neural network for predictive control of drilling operations. A downhole processor controls the operation of the various devices in a bottom hole assembly to effect changes to drilling parameters and drilling direction to autonomously optimize the drilling effectiveness. The neural network iteratively updates a prediction model of the drilling operations and provides recommendations for drilling corrections to a drilling operator. |
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| 95 | WELL MANAGEMENT SYSTEM | EP00955874.3 | 2000-08-24 | EP1214499A1 | 2002-06-19 | VIDRINE, William, L.; FEECHAN, Michael |
| A system (10) and method for managing a new well or an existing well. The system (10) includes a sensor (32) and a control (34) disposed within a well, a surface control system (36) at the surface, a continuous tubing string (30) extending into the well, and a conductor (38) disposed on the continuous tubing string (30). The conductor (38) connects the sensor (32) and control (34) to the surface control system (36) to allow the surface control system (36) to monitor downhole conditions and to operate the control (34) in response to the downhole conditions. Another conductor (40) may also be provided along the continuous tubing string (30) to conduct power from a surface power supply (42) to the control (34). The conductors (38, 40) are preferably housed in the wall of the continuous tubing string (30) and may be electrical conductors, optical fibers, and/or hydraulic conduits. The control (34) is preferably equipped with a sensor that verifies operation and status of the device and provides the verification to the surface processor via the conductor. Contemplated controls include valves, sliding sleeves, chokes, filters, packers, plugs, and pumps. The system can be installed through the production tubing of an existing well. | ||||||
| 96 | Drill bit design using neural networks | EP00307034.9 | 2000-08-17 | EP1146200A1 | 2001-10-17 | Jelley, David John; Jarvis, Brian Peter |
The present invention is a method and apparatus which accurately predicts one or more operating characteristics of an earth boring drill bit operated under a set of known operating conditions. A range of operating conditions may be input so that the operating characteristic(s) of the drill bit may be predicted over, and perhaps beyond the range the drill bit designer has anticipated. In this manner, a new drill bit design may be refined and/or proven with a high level of confidence prior to manufacture. Only minimal field testing of the new design is required to verify its performance. |
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| 97 | Verfahren und Einrichtung zur Untersuchung und Identifizierung der Art eines Untergrundes | EP00811161.9 | 2000-12-07 | EP1109034A1 | 2001-06-20 | Bongers, Hans-Werner; Böni, Hans; Schaer, Roland; Schmitzer, Harald |
Das Verfahren und eine dieses Verfahren nutzende Einrichtung an oder in Zuordnung zu einem Gerät zum Abbau eines Untergrunds zur Untersuchung und Identifizierung der Art des abzubauenden Untergrunds und zur Bereitstellung mindestens eines Betriebsparatmeters zur optimierten Voreinstellung des Abbaugeräts, sieht die Verwendung eines Sensors (1), vorzugsweise in unmittelbarer Zuordnung zum Abbauwerkzeug (2), z. B. einen Bohrhammer, vor, um eine im Werkzeug erzeugte oder induzierte Stoßwelle zu erfassen. Aus dem gemessenen Stoßwellen-Signal wird mindestens ein für den zu bearbeitenden Untergrund charakteristiches Merkmal (M1 ... M4) extrahiert und zur vergleichenden Klassifizierung des Untergrunds mittels eines Algorithmus' ausgewertet. Vorzugsweise wird bei der algorithmischen Auswertung zusätzlich eine externe, auf das Abbaugerät wirkende Kraft, insbesondere die Anpreßkraft (p) berücksichtigt. |
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| 98 | PROCEDE POUR REALISER UNE REPRESENTATION DES TEXTURES D'UNE STRUCTURE GEOLOGIQUE | EP96931108.3 | 1996-09-11 | EP0796443B1 | 2000-12-13 | KESKES, Naamen; RABILLER, Philippe; YE, Shinju |
| 99 | MOLING APPARATUS AND A GROUND SENSING SYSTEM THEREFOR | EP97903441.0 | 1997-02-11 | EP0883729B1 | 2000-12-06 | RODGER, Albert, Alexander |
| The invention provides a ground sensing system (10) comprising: sensing means (19) located, in use, on a projectile being driven through ground by means of apparatus having a self adjustment between a vibration mode and a vibro-impact mode according to encountered ground resistance, the sensing means sensing the dynamic resistance of the ground that the projectile is passing through; signal processing means for processing the output of said sensing means to provide a dynamic resistance waveform (106); and waveform recognition means (108) for correlating said dynamic resistance waveform with stored dynamic waveforms for identifying a ground characteristic. The waveform recognition means may comprise a neural network system. | ||||||
| 100 | Method for controlling the development of an oil or gas reservoir | EP98303548.6 | 1998-05-06 | EP0881357A2 | 1998-12-02 | Stephenson, Stanley V. |
Development of an oil or gas reservoir is controlled using a neural network and genetic algorithm program to define a neural network topology and the optimal inputs for that topology. The topology is defined from identified and selected parameters (1) associated with the formation or formations in which actual wells are drilled in the reservoir, and (2) associated with the drilling, completion and stimulation of those wells, and (3) associated with the oil or gas production from the wells. Subsequent drilling, completion and stimulation of the reservoir is determined and applied based on hypothetical alternatives input to the topology and resulting outputs. |
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