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1. 发明申请

WO2022146412A1 EFFECT OF HOLE CLEANING ON TORQUE AND DRAG 审中-公开
公开(公告)号：WO2022146412A1
公开(公告)日：2022-07-07
申请号：PCT/US2020/067176
申请日：2020-12-28
申请人： LANDMARK GRAPHICS CORPORATION
发明人： MITTAL, Manish Kumar , SAMUEL, Robello
IPC分类号： E21B47/12 , E21B37/02
摘要： The disclosure presents processes and methods for determining an adjusted drag friction factor, where the adjusting utilizes a hole cleaning function. In some aspects, the drag friction factor utilizes viscous drag. In some aspects, the drag friction factor utilizes viscous torque. In some aspects, the drag friction factor can be utilized to determine one or more decomposed friction factors. The decomposed friction factors or the adjusted drag friction factor can be utilized in a friction processor to improve the efficiency of borehole operations. The hole cleaning function can utilize various parameters, for example, a cuttings density, a cuttings load, a cuttings shape, a cuttings size, a deviation, a drill pipe rotation rate, a drill pipe size, a flow regime, a hole size, a mud density, a mud rheology, a mud velocity, a pipe eccentricity, and other parameters. A system is disclosed that is capable of implementing the processes and methods.

2. 发明申请

WO2022125099A1 UTILIZING MICRO-SERVICES FOR OPTIMIZATION WORKFLOWS OF BOREHOLE OPERATIONS 审中-公开
公开(公告)号：WO2022125099A1
公开(公告)日：2022-06-16
申请号：PCT/US2020/064278
申请日：2020-12-10
申请人： LANDMARK GRAPHICS CORPORATION [US]/[US]
发明人： MITTAL, Manish Kumar , SAMUEL, Robello
IPC分类号： E21B47/12 , E21B47/26 , G01V1/40
摘要： The disclosure presents processes and methods for utilizing one or more micro-services to generate a calibration of a factor of a borehole operation or to generate an optimization adjustment to the borehole operation. The micro-services selected for execution can be selected by an optimization workflow, where each type of borehole operation can have its own set of micro-services. The micro-services can be part of one or more computing systems, such as a downhole system, a surface system, a well site controller, a cloud service, a data center service, an edge computing system, other computing systems, or various combinations thereof. Also disclosed is a system for implementing micro-services on one or more computing systems to enable a light weight and fast response, e.g., real-time or near real-time response, to borehole operations.

3. 发明申请

WO2022125102A1 DECOMPOSED FRICTION FACTOR CALIBRATION 审中-公开
公开(公告)号：WO2022125102A1
公开(公告)日：2022-06-16
申请号：PCT/US2020/064330
申请日：2020-12-10
申请人： LANDMARK GRAPHICS CORPORATION [US]/[US]
发明人： SAMUEL, Robello , MITTAL, Manish Kumar
IPC分类号： E21B47/12 , E21B47/26
摘要： The disclosure presents processes and methods for decomposing friction factors and generating a calibrated friction factor and adjusted input parameters. The calibrated friction factor and adjusted input parameters can be utilized by a borehole system as an input to adjust borehole operations to improve the operational efficiency. The friction factors can be decomposed by type, such as geometrical, geomechanical, mechanical, and fluid. The disclosure also presents processes and methods for identifying an outlier portion of a friction factor, as identified by a deviation threshold that can be used to identify adjustments to borehole operations in that portion of the borehole. A system is disclosed that is capable of implementing the processes and methods in a borehole operation system, such as a downhole system, a surface system, or a distant system, for example, a data center, cloud environment, lab, corporate office, or other location.

4. 发明申请

WO2022186843A1 PREDICTING A DRILL STRING PACKOFF EVENT 审中-公开
公开(公告)号：WO2022186843A1
公开(公告)日：2022-09-09
申请号：PCT/US2021/029598
申请日：2021-04-28
申请人： LANDMARK GRAPHICS CORPORATION
发明人： SAMUEL, Robello , MITTAL, Manish Kumar , ADARI, Rishi , NOOKALA, Nanda Kumar
IPC分类号： E21B47/12 , E21B44/00
摘要： The disclosure presents processes and methods for determining a packoff event at a location in a borehole undergoing a drilling operation. The packoff event can be represented by a packoff risk indicator (PRI) that presents, for example, a percentage risk of the packoff event occurring. The PRI can be utilized to initiate a remediation operation prior to the packoff event becoming more severe, such as a stuck drill string. In some aspects, the generation of the PRI can utilize an uncertainty model to provide a range of input parameters and an uncertainty parameter used by other systems to evaluate the risk of the potential packoff event has on borehole operations. In some aspects, the generation of the PRI can utilize machine learning algorithms or deep neural network algorithms to pre-process the input parameters to improve the accuracy of the PRI and of the models used to generate the PRI.

5. 发明申请

WO2016022337A1 MODELING CASING/RISER WEAR AND FRICTION FACTOR USING DISCRETE INVERSION TECHNIQUES 审中-公开
标题翻译：使用离散反转技术建模铸造/升降器磨损和摩擦系数
公开(公告)号：WO2016022337A1
公开(公告)日：2016-02-11
申请号：PCT/US2015/042463
申请日：2015-07-28
申请人： LANDMARK GRAPHICS CORPORATION
发明人： SAMUEL, Robello , MITTAL, Manish Kumar , ANIKET, (None)
IPC分类号： E21B44/00 , G06F9/455 , E21B41/00
CPC分类号： G06F17/5009 , E21B41/00 , E21B41/0092 , E21B47/0006 , G05B17/02 , G06F17/13
摘要： Predicting casing wear, riser wear, and friction factors in drilling operations may be achieved with data-driven models that use discrete inversion techniques to updated casing wear models, riser wear models, and/or friction factor models. For example, a method may applying a linear inversion technique or a nonlinear inversion technique to one or more parameters of at least one of a casing wear model, a riser wear model, or a friction factor model using historical data from a previously drilled well as input data to produce at least one of an updated casing wear model, an updated riser wear model, or an updated friction factor model, respectively; and implementing the at least one of the updated casing wear model, the updated riser wear model, or the updated friction factor model when designing and/or performing a drilling operation.
摘要翻译：使用使用离散反演技术更新套管磨损模型，立管磨损模型和/或摩擦因子模型的数据驱动模型可以实现预测钻井操作中的套管磨损，提升管磨损和摩擦因素。例如，一种方法可以将线性反演技术或非线性反演技术应用于使用来自先前钻井的历史数据的套管磨损模型，立管磨损模型或摩擦因子模型中的至少一个的一个或多个参数，输入数据以分别产生更新的套管磨损模型，更新的冒口磨损模型或更新的摩擦因子模型中的至少一个; 以及在设计和/或执行钻井操作时实施更新的套管磨损模型，更新的提升管磨损模型或更新的摩擦因子模型中的至少一个。

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