# US 10,871,762 B2 · Real time analysis of fluid properties for drilling control > Agents: this data is available as JSON from the patentgrep API and MCP server — see https://patentgrep.com/llms.txt - Number: US 10,871,762 B2 - Document ID: US10871762B2 - Status: Granted - Kind: B2 - Application number: 16/295,788 - Filed: 2019-03-07 - Published: 2020-09-10 - Granted: 2020-12-22 - Earliest claimed: 2019-03-07 - Assignees: Saudi Arabian Oil Company - Applicants: Saudi Arabian Oil Company - Inventors: Odai Elyas; Abdullah Saleh Hussain Al-Yami; Salem H. Al Gharbi - Web page: https://patentgrep.com/patent/US10871762B2 ## CPC - E21B 44/00: Automatic control systems specially adapted for drilling operations, i.e. self-operating systems which function to carry out or modify a drilling operation without intervention of a human operator, e.g. computer-controlled drilling systems; Systems specially adapted for monitoring a plurality of drilling variables or conditions - G05B 19/406: characterised by monitoring or safety (G05B19/19 takes precedence) - E21B 21/082: {Dual gradient systems, i.e. using two hydrostatic gradients or drilling fluid densities} - G06N 20/00: Machine learning - E21B 2200/20: Computer models or simulations, e.g. for reservoirs under production, drill bits - G05B 2219/45129: Boring, drilling - E21B: EARTH OR ROCK DRILLING; OBTAINING OIL, GAS, WATER, SOLUBLE OR MELTABLE MATERIALS OR A SLURRY OF MINERALS FROM WELLS - G05B: CONTROL OR REGULATING SYSTEMS IN GENERAL; FUNCTIONAL ELEMENTS OF SUCH SYSTEMS; MONITORING OR TESTING ARRANGEMENTS FOR SUCH SYSTEMS OR ELEMENTS (systems for controlling or regulating non-electric variables G05D; systems for regulating electric or magnetic variables G05F; control devices or systems insofar as characterised by mechanical features only G05G) - G06N: COMPUTING ARRANGEMENTS BASED ON SPECIFIC COMPUTATIONAL MODELS ## Abstract Techniques are described for controlling drilling operations based on real time measurement and analysis of fluid properties in a drilling environment. Sensor data can be collected that provides measurement(s) of fluid properties (for example, density and rheology) of the drilling fluid (in other words, downhole mud) around the drill. The measurements can be provided to a hydraulic model that calculates downhole pressure loss in the annulus. Based on this calculation, a calculation of equivalent circulating density (ECD) can be performed. In some implementations, the calculations are performed in real time with respect to the collection of the sensor data. The real time pressure loss and ECD calculations can be used to control bottom hole circulating pressures. The results of the calculations may be used to automatically control drilling operations. ## Claims ### Claim 1 A computer-implemented method executed by at least one processor, the method comprising: accessing, by the at least one processor, sensor data that describes fluid properties of drilling fluid in a drilling environment, wherein the sensor data are generated by one or more sensor devices that are arranged in the drilling environment to periodically measure the fluid properties, and wherein assessing the sensor data includes generating a prediction model using artificial intelligence and machine learning operations to analyze the data; analyzing, by the at least one processor, the sensor data to generate an equivalent circulating density (ECD) value for the drilling fluid, wherein the analyzing of the sensor data to generate the ECD value is performed in real time with respect to the generation of the sensor data, and wherein generating the ECD value includes using the prediction model to predict pressure loss and the ECD value based on the sensor data, including determining the accuracy of the predicted pressure loss and the ECD value; and based at least partly on the ECD value, transmitting, by the at least one processor, at least one control signal to modify at least one operation of a drilling apparatus operating in the drilling environment, wherein the transmitting of the at least one control signal is performed in real time with respect to the generating and the analyzing of the sensor data. ### Claim 2 (depends on 1) The computer-implemented method of claim 1, wherein the sensor data describes one or more of density and rheology of the drilling fluid. ### Claim 3 (depends on 1) The computer-implemented method of claim 1, wherein: the sensor data is further analyzed to generate a total pressure loss for the drilling fluid; and the at least one control signal is sent further based on the total pressure loss. ### Claim 4 (depends on 1) The computer-implemented method of claim 1, further comprising: presenting, by the at least one processor, in a user interface (UI), a graphical representation of the ECD value in real time with respect to the generation and analyzing of the sensor data. ### Claim 5 (depends on 4) The computer-implemented method of claim 4, wherein the graphical representation shows a variation of the ECD value with respect to one or more of time and depth. ### Claim 6 (depends on 1) The computer-implemented method of claim 1, wherein analyzing the sensor data includes providing the sensor data as input to at least one model that has been trained, using at least one machine learning (ML) algorithm, to output the ECD value based on the sensor data. ### Claim 7 (depends on 6) The computer-implemented method of claim 6, wherein the output ECD value is further employed to retrain the at least one model. ### Claim 8 (depends on 1) The computer-implemented method of claim 1, wherein the at least one control signal is transmitted to modify the at least one operation that alters one or more of the weight and the rheology of the drilling fluid. ### Claim 9 (depends on 1) The computer-implemented method of claim 1, wherein the at least one control signal is transmitted to modify the at least one operation that alters the circulation rate of the drilling fluid. ### Claim 10 (depends on 1) The computer-implemented method of claim 1, wherein the at least one control signal is transmitted to modify the at least one operation that adjusts downhole pressure of the drilling fluid by applying surface back pressure from a choke. ### Claim 11 A system comprising: at least one processor; and a memory communicatively coupled to the at least one processor, the memory storing instructions that when executed cause the at least one processor to perform operations comprising: accessing sensor data that describes fluid properties of drilling fluid in a drilling environment, wherein the sensor data are generated by one or more sensor devices that are arranged in the drilling environment to periodically measure the fluid properties, and wherein assessing the sensor data includes generating a prediction model using artificial intelligence and machine learning operations to analyze the data; analyzing the sensor data to generate an equivalent circulating density (ECD) value for the drilling fluid, wherein the analyzing of the sensor data to generate the ECD value is performed in real time with respect to the generation of the sensor data, and wherein generating the ECD value includes using the prediction model to predict pressure loss and the ECD value based on the sensor data, including determining the accuracy of the predicted pressure loss and the ECD value; and based at least partly on the ECD value, transmitting at least one control signal to modify at least one operation of a drilling apparatus operating in the drilling environment, wherein the transmitting of the at least one control signal is performed in real time with respect to the generating and the analyzing of the sensor data. ### Claim 12 (depends on 11) The system of claim 11, wherein the sensor data describes one or more of density and rheology of the drilling fluid. ### Claim 13 (depends on 11) The system of claim 11, wherein: the sensor data is further analyzed to generate a total pressure loss for the drilling fluid; and the at least one control signal is sent further based on the total pressure loss. ### Claim 14 (depends on 11) The system of claim 11, the operations further comprising: presenting, in a user interface (UI), a graphical representation of the ECD value in real time with respect to the generation and analyzing of the sensor data. ### Claim 15 (depends on 14) The system of claim 14, wherein the graphical representation shows a variation of the ECD value with respect to one or more of time and depth. ### Claim 16 (depends on 11) The system of claim 11, wherein analyzing the sensor data includes providing the sensor data as input to at least one model that has been trained, using at least one machine learning (ML) algorithm, to output the ECD value based on the sensor data. ### Claim 17 (depends on 16) The system of claim 16, wherein the output ECD value is further employed to retrain the at least one model. ### Claim 18 (depends on 11) The system of claim 11, wherein the at least one control signal is transmitted to modify the at least one operation that alters one or more of the weight and the rheology of the drilling fluid. ### Claim 19 (depends on 11) The system of claim 11, wherein the at least one control signal is transmitted to modify the at least one operation that alters the circulation rate of the drilling fluid. ### Claim 20 (depends on 11) The system of claim 11, wherein the at least one control signal is transmitted to modify the at least one operation that adjusts downhole pressure of the drilling fluid by applying surface back pressure from a choke.