A computer system receives data obtained from multiple hydrocarbon wells. The data includes a first set of downhole temperature logs recorded before detection of one or more wellbore leaks in the multiple hydrocarbon wells. A second set of downhole temperature logs is recorded after detection of the one or more wellbore leaks. The computer system extracts multiple features from the data to generate an N-dimensional feature space. The computer system performs dimensionality reduction on the N-dimensional feature space to generate an M-dimensional feature space, wherein M is less than N. The computer system generates one or more machine learning models trained to determine the one or more wellbore leaks in the multiple hydrocarbon wells based on the M-dimensional feature space.

Locating a loss zone while cementing a well casing in a well bore includes: inserting a fiber-optic cable into the well bore, wherein the fiber optic cable is part of one or more Distributed Fiber-Optic Sensing (DFOS) systems; detecting a loss circulation signature, while cementing the well casing, at a point along the fiber-optic cable by at least one of the one or more DFOS systems; and locating the loss zone within the well bore based on the point along the fiber-optic cable at which the loss circulation signature was detected.

A method of determining fluid inflow locations comprises determining a plurality of temperature features from a distributed temperature sensing signal originating in a wellbore, using the plurality of temperature features in a fluid inflow identification model, and determining the presence of fluid inflow at one or more locations along the wellbore based on an output from the fluid inflow identification model.

A method of determining fluid inflow locations comprises determining a plurality of temperature features from a distributed temperature sensing signal originating in a wellbore, using the plurality of temperature features in a fluid inflow identification model, and determining the presence of fluid inflow at one or more locations along the wellbore based on an output from the fluid inflow identification model.

A water content sensor is positioned within a flowline downstream of a well-choke. The water content sensor is configured to determine a water content percentage of a production fluid flowing through the flowline. A temperature sensor is positioned downstream of the well-choke. The temperature sensor is configured to determine a temperature of the production fluid flowing through the flowline. A heating jacket surroundings at least a portion of the flowline. The heating-jacket is configured to transfer heat into the flowline. A controller is configured to receive a signal from each of the water content sensor and the temperature sensor, and control the heating jacket in response to a signal from each of the water content sensor and the temperature sensor.

A water content sensor is positioned within a flowline downstream of a well-choke. The water content sensor is configured to determine a water content percentage of a production fluid flowing through the flowline. A temperature sensor is positioned downstream of the well-choke. The temperature sensor is configured to determine a temperature of the production fluid flowing through the flowline. A heating jacket surroundings at least a portion of the flowline. The heating-jacket is configured to transfer heat into the flowline. A controller is configured to receive a signal from each of the water content sensor and the temperature sensor, and control the heating jacket in response to a signal from each of the water content sensor and the temperature sensor.

Locating a loss zone while cementing a well casing in a well bore includes: inserting a fiber-optic cable into the well bore, wherein the fiber optic cable is part of one or more Distributed Fiber-Optic Sensing (DFOS) systems; detecting a loss circulation signature, while cementing the well casing, at a point along the fiber-optic cable by at least one of the one or more DFOS systems; and locating the loss zone within the well bore based on the point along the fiber-optic cable at which the loss circulation signature was detected.

A method can include measuring temperature along a relief wellbore, thereby detecting a temperature anomaly in an earth formation penetrated by the relief wellbore, and determining a location of an influx into a target wellbore, based on the temperature anomaly detecting. A thermal anomaly ranging system for use with a subterranean well can include a temperature sensor in a relief wellbore that penetrates an earth formation, the temperature sensor detecting a temperature anomaly in the formation, and the temperature anomaly being caused by an influx into a target wellbore. Another method can include measuring optical scattering in an optical waveguide positioned in a relief wellbore, thereby detecting a temperature anomaly in an earth formation penetrated by the relief wellbore, and determining a location of an influx into a target wellbore, based on the temperature anomaly detecting.

A method can include measuring temperature along a relief wellbore, thereby detecting a temperature anomaly in an earth formation penetrated by the relief wellbore, and determining a location of an influx into a target wellbore, based on the temperature anomaly detecting. A thermal anomaly ranging system for use with a subterranean well can include a temperature sensor in a relief wellbore that penetrates an earth formation, the temperature sensor detecting a temperature anomaly in the formation, and the temperature anomaly being caused by an influx into a target wellbore. Another method can include measuring optical scattering in an optical waveguide positioned in a relief wellbore, thereby detecting a temperature anomaly in an earth formation penetrated by the relief wellbore, and determining a location of an influx into a target wellbore, based on the temperature anomaly detecting.

The present invention discloses a method for interpreting and evaluating production profile of multi-layer gas reservoir based on downhole distributed temperature monitoring, including: obtaining downhole distributed temperature monitoring data of target well; preprocessing the downhole distributed temperature monitoring data; segmenting the temperature monitoring data according to test curve characteristics of the target well and logging interpretation results; using a multi-layer gas reservoir seepage pressure fieldtemperature field coupled model to calculate temperatures of each layer in the borehole production profile of the target well by numerical simulation method; comparing the temperatures of each layer of the borehole production profile with the temperature monitoring data after segmentation, obtaining the optimal flow rate of each production layer with optimization theories, and obtaining the production profile of the target well based on the optimal flow rate of each production layer.