Saudi Arabian Oil Company

Klemens Katterbauer

Alberto F Marsala

Nouf Jabri

Vera Solovyeva

Abdallah A Alshehri

Abdulaziz S Al-Qasim

Martin E Poitzsch

Shouxiang Mark Ma

Ali Abdallah Alyousef

Ali Abdallah AlYousif

Shitong Sherry Zhu

Abdulrahman Aljedaani

Tareq Ghamdi

Abdallah Al Shehri

Sara Abu Alsaud

Ibrahim Alobaidan

A method that may include obtaining well path data describing a first well path through one or more formations. The method may include obtaining first acquired drilling parameter data in real-time during a drilling operation for a predetermined well, wherein the drilling operation corresponds to the first well path. The method may include determining, by a computer processor, first predicted drilling data using a machine-learning model, the well path data, and the first acquired drilling parameter data, wherein the first predicted drilling data may include a predicted well path. The method may include determining whether the first predicted drilling data satisfies a predetermined criterion. The method may include determining, in response to determining that the first predicted drilling data fails to satisfy the predetermined criterion, an adjusted well path. The method may include transmitting a first command to update the drilling operation to implement the adjusted well path.

Intelligent underbalanced coiled tubing drilling (UBCTD) geosteering operations advisory system and method of use

A method includes obtaining, with an edge computing device disposed in a bottom hole assembly of a drilling system, logging while drilling data. The method further includes determining, with the edge computing device, at least one interpreted quantity of a subsurface using one or more artificial intelligence (AI) models processing the logging while drilling (LWD) data. The method further includes determining, with the edge computing device, an optimal set of data transfer parameters for a telemetry system governed by a set of data transfer parameters, to telemeter the at least one interpreted quantity, where the set of data transfer parameters are continually updated to the optimal set of data transfer parameters while the logging while drilling data is being acquired. The method further includes transmitting, with the edge computing device, one or more guidance control parameters to a geosteering system based on the at least one interpreted quantity.

Methods and systems for logging while drilling and optimized telemetry using artifical intelligence

A method for optimizing a wireless sensor network for monitoring hydrogen production from fire flooding involves training a machine learning model to generate an estimate of communication performance of each of a multitude of sensors. The sensors are a component of the wireless sensor network disposed in a sub-surface hydrogen reservoir, with each of the multitude of sensors configured to obtain measurements of environmental variables of the hydrogen reservoir. The method further involves minimizing a cardinality of the multitude of sensors, using the machine learning model.

Wireless hydrogen subsurface sensing framework for reservoir optimization

A method for improving natural hydrogen recovery through hydrogen fracturing includes obtaining field data from a hydrogen-containing formation and generating, by a computer processor and a series of models, a surface production rate, a compression value where the compression value is a pressure of pressurized hydrogen used to fracture the hydrogen-containing formation, a well path, a set of well separation distances, a fracture half-length where the fracture half-length is half of a total length of a fracture caused by a fracturing of the hydrogen-containing formation using pressurized hydrogen, and a well production rate. Using a well analysis, the fracture half-length, the well path, the well separation distances, and the well production rate are evaluated. Based on the surface production rate, the compression value, the fracture half-length, the well path, the well separation distances, the well production rate, and the field data, field operations are performed on the hydrogen-containing formation.

Method for improving unconventional hydrogen development

A composition of matter including a fluorescent assembly and a drilling fluid is provided. The fluorescent assembly includes a matrix material and a plurality of fluorophores held within the matrix material and has an average particle size of at least one millimeter. A method includes introducing the fluorescent assembly into a drilling fluid and circulating the drilling fluid through a well during a drilling operation that creates formation cuttings such that the fluorescent assembly interacts with the formation cuttings, creating tagged cuttings. The method further includes collecting returned cuttings from the circulating drilling fluid at a surface of the well, detecting the presence of the fluorescent assembly on the returned cuttings to identify the tagged cuttings, and correlating the tagged cuttings with a drill depth in the well at a time during the drilling operation.

Fluorescent assemblies for drilling depth correlation

A sonde adapted for determining one or more parameters related to hydrogen at a subsurface location. The sonde includes: a plurality of centralizer arms forming an interior space having a proximal portion and a distal portion; and a plurality of fiber optic Raman probes each disposed at the proximal portion or the distal portion of the interior space and proximate a respective one of the plurality of centralizer arms, the plurality of fiber optic Raman probes being adapted to measure a hydrogen concentration in a downhole measurement. The sonde also includes a plurality of optical probes each disposed at another of the distal portion or the proximal portion of the interior space and proximate a same or different one of the plurality of centralizer arms, the plurality of optical probes being adapted to measure downhole local gas holdup.

Apparatus and method for in-situ monitoring of hydrogen levels at a subsurface location

Techniques for correlating a depth of drill bit cuttings include circulating a drilling fluid into a wellbore during a drilling process to form the wellbore in a subterranean formation; circulating a portion of uniquely identifiable particles from a container into the drilling fluid during the drilling process; circulating a return drilling fluid that includes the drilling fluid, cuttings from the subterranean formation, and the uniquely identifiable particles; separating the drilling fluid from the cuttings from the subterranean formation and the uniquely identifiable particles; capturing at least one image of the separated cuttings and the uniquely identifiable particles; and determining, based on the image, a depth of the subterranean formation.

Control systems and methods for rock cuttings identification

A method may include obtaining well log data regarding a geological region of interest. The well log data may correspond to logging-while-drilling (LWD) measurements or measurement-while-drilling (MWD) measurements acquired from various wellbores. The method may further include generating image data regarding the geological region of interest using the well log data and a recurrent neural network. The method may further include determining a drilling parameter for a wellbore among the wellbores in real-time using the image data. The drilling parameter may be determined while the well log data is being acquired in the wellbore. The method may further include transmitting, based on the drilling parameter, a command to a drilling system coupled to the wellbore.

Method and system for processing well log data from multiple wells using machine learning

A method may include obtaining reservoir data for a geological region of interest. The method may further include obtaining production data regarding one or more wells coupled to the geological region of interest. The method may further include obtaining carbon emission data for the one or more wells. The method may further include determining predicted carbon emission data and predicted production data using a machine-learning model. The method may further include determining one or more stimulation parameters for a stimulation operation based on the predicted carbon emission data and the predicted production data. The method may further include transmitting a command to a control system coupled to an injection well. The command adjusts an amount of carbon dioxide that is supplied to the injection well based on the one or more stimulation parameters.

Method and system for managing carbon dioxide supplies using machine learning

A system for drilling a wellbore is disclosed. The injection pump releases the taggant into the mud stream traveling downhole. The taggant attaches to the rock cuttings and it is detected on the surface by the taggant detector. The taggant detector provides the data relating to the taggants detected in the drilling fluid. The data is analyzed by taggant analysis and control engine, which produces an injection profile. Based on the injection profile, the IoT Controller adapts the parameters of the taggant injection pump to achieve a real-time optimization of the taggant injection.

Systems and methods for drilling a wellbore using taggant analysis

A method includes taking at least one image of a plurality of returned cuttings from a well using a fluorescent imaging camera, analyzing the at least one image with an imaging processing system to obtain detection data including a calculated percentage of a first emitted fluorescent light to formation cuttings, sending the detection data to an analysis and control program to correlate the returned cuttings with a depth in the well, and automatically controlling at least one drilling parameter for drilling the well based on the detection data.

Intelligently characterizing reservoirs via fluorescent imaging rock cuttings

A method for depth determination of drilled rock cuttings is disclosed. The taggant is injected and transported downhole along the mud stream and attaches to the rock cuttings. Taggant impregnated cuttings are detected at the surface based on molecular weight, emission wavelengths or radio frequency characteristics for encoding the taggant. The identification code identifies the depth of the drill bit when the particular batch of the taggant is released into the mud. The detection data, in addition to mud properties, flow rates, drill volume and penetration rates, formation characteristics, and well specifications are transferred to and analyzed by a taggant analysis and control engine. The taggant analysis and control engine controls an IoT controller that adapts the parameters of the taggant injection pump to achieve an intelligent controlled release to optimize the depth characterization process.

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Dhahran, Saudi Arabia

Klemens Katterbauer