A distance of a water flow path and a velocity of the water flow is calculated using data obtained from both a pulsed neutron sensor and distributed acoustic sensors. The two distance and velocity values are compared to obtain a first calculated distance and velocity. The distance of the water flow path and the velocity of the water flow are calculated using the Doppler data obtained from distributed Doppler sensors. The distance and velocity values are compared with the first calculated distance and first calculated velocity to obtain a second calculated distance and velocity values. The distance of the water flow path and the velocity of the water flow are calculated using temperature data obtained from distributed temperature sensors. The distance and velocity values are compared with the second calculated distance and velocity to determine a distance of a cement interface, and a velocity of a water flow therein.

The method of monitoring carbon dioxide leakage in carbon capture and storage reservoirs estimates porosity and water saturation in a porous medium, such as brine-saturated shale, as is common in carbon capture and storage reservoirs, based upon measured electrical conductivity and seismic P-wave velocity. The estimated porosity and water saturation may be used for monitoring carbon dioxide leakage from a carbon dioxide reservoir to the overlying cap rock of the region. Measured electrical conductivity and seismic P-wave velocity data are used by the present method to estimate the porosity and water saturation in the cap rock. If a decrease in water saturation in the cap rock is found, this indicates that carbon dioxide may be leaking up from the carbon dioxide reservoir. An alert signal is then generated to indicate that there may be a carbon dioxide leak.

The method of monitoring carbon dioxide leakage in carbon capture and storage reservoirs estimates porosity and water saturation in a porous medium, such as brine-saturated shale, as is common in carbon capture and storage reservoirs, based upon measured electrical conductivity and seismic P-wave velocity. The estimated porosity and water saturation may be used for monitoring carbon dioxide leakage from a carbon dioxide reservoir to the overlying cap rock of the region. Measured electrical conductivity and seismic P-wave velocity data are used by the present method to estimate the porosity and water saturation in the cap rock. If a decrease in water saturation in the cap rock is found, this indicates that carbon dioxide may be leaking up from the carbon dioxide reservoir. An alert signal is then generated to indicate that there may be a carbon dioxide leak.

Stratigraphic picks data from at least one first database are processed to ensure conformance with data conditions. The stratigraphic picks data can be filtered by removing at least some of the stratigraphic picks data that does not conform with the data conditions to generate filtered stratigraphic picks data. At least some data in a second database that matches at least some of the filtered stratigraphic picks data is identified. The identified at least some data can be processed to remove the identified at least some data from the second database, and to process the filtered stratigraphic picks data to add the filtered stratigraphic picks data to the second database. Further, a report can be generated identifying any of the filtered stratigraphic picks data that were successfully added to the second database and any of the stratigraphic data that were not successfully added to the second database.

A method for determining a real-time pore pressure log of a well in a reservoir, including the steps: storing existing data logs of surface drilling parameters, logging while drilling (LWD), and mud gas of existing wells in a database, storing existing pore pressure logs of the existing wells in the database, wherein the existing pore pressure logs correspond to the existing data logs, determining a relationship between the existing data logs and the existing pore pressure logs, drilling a new well into the reservoir, determining new data logs of surface drilling parameters, LWD, and mud gas of the new well while drilling the new well, inputting the new data logs of the new well into the relationship while drilling the new well, determining a real-time pore pressure log of the new well by outputting an estimated pore pressure at a certain depth by the relationship while drilling the new well.

Disclosed are telemetry systems and methods that employ a plurality of electromagnetic transceivers disposed outside a well casing string at a corresponding plurality of depths along the casing string. Each transceiver includes one or more toroidal inductors circumferentially surrounding the casing string and inductively coupled thereto to allow signal transmission between transceivers via currents induced in the casing. In some embodiments, signals are relayed via a chain of transceivers to facilitate indirect communication between a surface facility and other transceivers located too deep for direct communication to the surface.

A method can include training a deep neural network to generate a trained deep neural network where the trained deep neural network represents functions of a nonlinear Kalman filter that represents a dynamic system of equipment and environment via an internal state vector of the dynamic system; generating a base internal state vector, that corresponds to a pre-defined operational procedure, using the trained deep neural network; receiving operation data from the equipment responsive to operation in the environment; generating an internal state vector using the operation data and the trained deep neural network; and comparing at least the internal state vector to at least the base internal state vector.

A method can include training a deep neural network to generate a trained deep neural network where the trained deep neural network represents functions of a nonlinear Kalman filter that represents a dynamic system of equipment and environment via an internal state vector of the dynamic system; generating a base internal state vector, that corresponds to a pre-defined operational procedure, using the trained deep neural network; receiving operation data from the equipment responsive to operation in the environment; generating an internal state vector using the operation data and the trained deep neural network; and comparing at least the internal state vector to at least the base internal state vector.

A method for configuring a logging module for logging sensors deployment based on a sensing data acquisition objective includes selecting a tool body, selecting at least one type of sensor, and selecting at least one type of roller. The method also includes incorporating the at least one selected type of sensor onto the at least one selected type of roller to provide at least one sensor roller, and mounting the at least one sensor roller into a compressible mounting assembly provided in the tool body to provide the logging module.

The object is provided with a system (1) for measuring at least one given physical quantity. The method comprises a step of measuring, by the measurement system (1), the time evolution of said physical quantity during the transportation of the object along the conveyance path, a step of recognising a plurality of indicia, each indicium corresponding to a path characteristic in the time evolution of the measured physical quantity, a step of determining a timeline of path characteristics corresponding to a sequence of recognised indicia, and a step of locating the object, which involves determining a match between the determined timeline of path characteristics and a predefined spatial representation relative to the conveyor machine.