Patent classifications
E21B45/00
CROSS-PLOT ENGINEERING SYSTEM AND METHOD
In one embodiment, a method includes facilitating a real-time cross-plot display of drilling-performance data for a current well. The real-time cross-plot display includes a plurality of data plots represented on a common graph such that each data plot specifying at least two drilling parameters. Each data plot includes a plurality of data points such that each data point is expressable as Cartesian coordinates in terms of the at least two drilling parameters. The method further includes receiving new channel data for the current well from a wellsite computer system. In addition, the method includes creating, from the new channel data, new data points for the plurality of data plots as the new channel data is received. Moreover, the method includes updating the plurality of data plots with the new data points as the new data points are created.
METHODOLOGY TO MAXIMIZE NET RESERVOIR CONTACT FOR UNDERBALANCED COILED TUBING DRILLING WELLS
The present disclosure describes computer-implemented method for monitoring a well operation, the method including: accessing a plurality of streams of data received from multiple sources during the well operation, wherein: the multiple sources include a well testing process, a biosteering process, a geosteering process, and a drilling process, and the well operation includes sidetracking and drilling one or more laterals from a motherbore; combining the plurality of streams of data on a single montage with a common horizontal axis to track the one or more laterals from the motherbore; and presenting the single montage on a display device to an operator running the well operation.
METHODOLOGY TO MAXIMIZE NET RESERVOIR CONTACT FOR UNDERBALANCED COILED TUBING DRILLING WELLS
The present disclosure describes computer-implemented method for monitoring a well operation, the method including: accessing a plurality of streams of data received from multiple sources during the well operation, wherein: the multiple sources include a well testing process, a biosteering process, a geosteering process, and a drilling process, and the well operation includes sidetracking and drilling one or more laterals from a motherbore; combining the plurality of streams of data on a single montage with a common horizontal axis to track the one or more laterals from the motherbore; and presenting the single montage on a display device to an operator running the well operation.
ADJUSTING WELL TOOL OPERATION TO MANIPULATE THE RATE-OF-PENETRATION (ROP) OF A DRILL BIT BASED ON MULTIPLE ROP PROJECTIONS
Multiple projected rate of penetration (ROP) values can be determined for purposes of adjusting well tools and well characteristics. For example, surface data can be determined based on a surface sensor signal. Downhole data can be determined based on a downhole sensor signal. A first value indicating a first projected ROP of a drill bit can be determined by providing the surface data as input to a first machine-learning model. A second value indicating a second projected ROP of the drill bit can be determined by providing the downhole data as input to a second machine-learning model. A third value indicating a third projected ROP of the drill bit can be determined by providing the first value and the second value input to a third machine-learning model. An operating characteristic of a well tool can be adjusted based on the third value.
ADJUSTING WELL TOOL OPERATION TO MANIPULATE THE RATE-OF-PENETRATION (ROP) OF A DRILL BIT BASED ON MULTIPLE ROP PROJECTIONS
Multiple projected rate of penetration (ROP) values can be determined for purposes of adjusting well tools and well characteristics. For example, surface data can be determined based on a surface sensor signal. Downhole data can be determined based on a downhole sensor signal. A first value indicating a first projected ROP of a drill bit can be determined by providing the surface data as input to a first machine-learning model. A second value indicating a second projected ROP of the drill bit can be determined by providing the downhole data as input to a second machine-learning model. A third value indicating a third projected ROP of the drill bit can be determined by providing the first value and the second value input to a third machine-learning model. An operating characteristic of a well tool can be adjusted based on the third value.
SYSTEM AND METHOD FOR MAG RANGING DRILLING CONTROL
System and method for controlling the drilling of a second wellbore in close proximity to a first well bore. A computer system obtains information regarding a previously drilled wellbore, as well as information regarding a second wellbore being drilled. Using information obtained from one or more magnetic sensors, the computer system determines an optimal target path for continued drilling of the second wellbore and may issue one or more control signals to one or more control systems coupled to a drilling rig to automatically drill in accordance with the selected path. The computer system can generate a plurality of potential paths using one or more cost curves and/or value curves to determine the optimal path for the second wellbore.
SYSTEM AND METHOD FOR MAG RANGING DRILLING CONTROL
System and method for controlling the drilling of a second wellbore in close proximity to a first well bore. A computer system obtains information regarding a previously drilled wellbore, as well as information regarding a second wellbore being drilled. Using information obtained from one or more magnetic sensors, the computer system determines an optimal target path for continued drilling of the second wellbore and may issue one or more control signals to one or more control systems coupled to a drilling rig to automatically drill in accordance with the selected path. The computer system can generate a plurality of potential paths using one or more cost curves and/or value curves to determine the optimal path for the second wellbore.
Drilling trouble prediction using stand-pipe-pressure real-time estimation
Raw, real-time drilling data is pulled from a centralized database for processing. The raw, real-time drilling data is re-formatted into a format required for processing by one or more predictive models. Real-time processing is performed with respect to one or more drilling parameters associated with the re-formatted data using the one or more predictive models to generate output data. The output data received from the one or more predictive models is re-formatted for storage in the centralized database. The reformatted output data is retrieved from the centralized database for analysis with respect to visualization, generating alerts, or generating recommendations.
SYNCHRONIZATION OF TOOL ACCELERATION VS TIME DATA AND DRILLER DEPTH VS TIME DATA
Processes and systems for synchronizing driller depth data as a function of time with downhole tool acceleration data as a function of time. In some embodiments, the process can include determining one or more in slips conditions for a drill pipe; determining one or more in slips conditions for a downhole tool; interpolating the in slips status indicators on to a common time grid; determining one or more shifts for which an allowed minimum overlapping time period between the acceleration data and the driller depth data is not less than an allowed minimum overlapping time period; determining a correlation coefficient between the interpolated in slips status indicators for each of the one or more shifts; determining a maximum correlation coefficient and a time shift associated with the maximum correlation; and synchronizing the acceleration data and the driller depth data.
SYNCHRONIZATION OF TOOL ACCELERATION VS TIME DATA AND DRILLER DEPTH VS TIME DATA
Processes and systems for synchronizing driller depth data as a function of time with downhole tool acceleration data as a function of time. In some embodiments, the process can include determining one or more in slips conditions for a drill pipe; determining one or more in slips conditions for a downhole tool; interpolating the in slips status indicators on to a common time grid; determining one or more shifts for which an allowed minimum overlapping time period between the acceleration data and the driller depth data is not less than an allowed minimum overlapping time period; determining a correlation coefficient between the interpolated in slips status indicators for each of the one or more shifts; determining a maximum correlation coefficient and a time shift associated with the maximum correlation; and synchronizing the acceleration data and the driller depth data.