Controller for spill monitoring processing, spill monitoring processing system and spill monitoring processing method

Abstract

The invention provides a controller for overflow leakage monitoring processing, an overflow leakage monitoring processing system, an overflow leakage monitoring processing method, an overflow leakage monitoring processing device, computer equipment and a computer readable storage medium. The controller is configured to be used for receiving ground monitoring information from a ground monitoring unit and underground monitoring information from an underground monitoring unit; performing working condition identification on the ground monitoring information and the underground monitoring information through a working condition identification model to obtain a working condition identification result; performing overflow monitoring on the ground monitoring information and the underground monitoring information through an overflow monitoring model corresponding to the working condition identification result; and in response to the monitored overflow condition, the overflow amount is calculated, and in response to the situation that the overflow amount is within a preset overflow range, the controller starts corresponding overflow processing operation. Overflow monitoring of complex well bottom conditions under various working conditions is achieved, overflow leakage can be treated automatically, the well control risk is reduced, and safe and efficient drilling operation is guaranteed.

Description

Technical Field

[0001] The present invention relates to the technical field of oil drilling, and in particular to a controller for leak monitoring and processing, and a leak monitoring and processing system and method. Background Art

[0002] At present, oil and gas exploration is gradually advancing into deep-sea, deep-layer and ultra-deep reservoirs; deep-sea, deep-layer and ultra-deep reservoirs have problems such as narrow safety density windows and complex geological conditions. During the oil and gas exploration process, spills are prone to occur during drilling operations, and the well control risk is high. Overflow monitoring is an important early step in pressure-controlled drilling. If the overflow is not controlled in time, blowouts are likely to occur, causing a large amount of manpower and material losses, leading to a decline in economic efficiency.

[0003] In the prior art, overflow monitoring methods are mainly ground monitoring, including mud pool liquid level monitoring method, inlet and outlet flow monitoring method, vertical pressure casing pressure monitoring method, comprehensive logging monitoring method, etc. The above monitoring methods mainly monitor ground data. There is a delay from the overflow at the bottom of the well to the ground display. The ground monitoring means are not timely enough to warn, and there is still a high risk of well control. However, there is currently no mature technology for downhole overflow monitoring. Although ultrasonic monitoring is expected to measure while drilling at the bottom of the well, there are problems such as difficulty in data transmission, high noise, and inability to conduct quantitative analysis. In addition, during non-drilling conditions such as drilling, starting and stopping pumps, and connecting single roots during the drilling process, the flow display caused by ground operations will cause false alarms for ground overflow monitoring, reducing the effectiveness and reliability of ground overflow monitoring methods.

[0004] In summary, the current ground monitoring is not timely enough, the circulating exhaust and well pressure time is limited, the well control risk is high, and the leakage monitoring means under various drilling conditions are immature, making the ground monitoring means unreliable. Real-time downhole monitoring cannot be quantitatively analyzed or transmitted in real time, and the overflow monitoring accuracy is low. The existing monitoring means are difficult to cope with the occurrence of complex downhole situations under various drilling conditions. There is an urgent need for a leakage monitoring method and system that can transmit in real time, perform quantitative analysis, autonomously identify working conditions, and intelligently control. Summary of the invention

[0005] Based on this, it is necessary to provide a controller and a system and method for leak monitoring and processing to address the problems of existing leak monitoring methods, such as insufficient timeliness, inability to transmit in real time, inability to conduct quantitative analysis, and inability to automatically identify working conditions.

[0006] A controller for leak monitoring and processing, connected to a ground monitoring unit and an underground monitoring unit,

[0007] The controller is configured to receive ground monitoring information from the ground monitoring unit and downhole monitoring information from the downhole monitoring unit; perform working condition identification on the ground monitoring information and the downhole monitoring information through a working condition identification model to obtain a working condition identification result; perform overflow monitoring on the ground monitoring information and the downhole monitoring information through an overflow monitoring model corresponding to the working condition identification result; in response to monitoring the occurrence of overflow, the controller calculates the overflow amount, and in response to the overflow amount being within a preset overflow range, the controller initiates a corresponding overflow processing operation.

[0008] In one of the embodiments, the controller is also connected to a spill handling unit;

[0009] The controller initiating the corresponding spill handling operation includes the controller controlling the spill handling unit to perform at least one of throttling, overflow discharge, back pressure control and well killing.

[0010] In one of the embodiments, the controller is also connected to an alarm unit;

[0011] The controller initiating a corresponding spill handling operation includes the controller controlling the alarm unit to start an alarm mode corresponding to the spill amount.

[0012] A leakage monitoring and processing system comprises a ground monitoring unit, a downhole monitoring unit and the controller described above, wherein the ground monitoring unit is used to collect ground monitoring information and transmit the ground monitoring information to the controller; the downhole monitoring unit is used to collect downhole monitoring information and transmit the downhole monitoring information to the controller.

[0013] In one embodiment, the system also includes a fiber optic cable data transmission unit, and the ground monitoring unit and the downhole monitoring unit are respectively connected to the controller through the fiber optic cable data transmission unit; the ground monitoring unit is used to transmit the ground monitoring information to the controller through the fiber optic cable data transmission unit, and the downhole monitoring unit is used to transmit the downhole monitoring information to the controller through the fiber optic cable data transmission unit; the fiber optic cable data transmission unit includes a pre-buried or embedded fiber optic cable.

[0014] In one of the embodiments, the ground monitoring information includes pressure difference information of the mud pool; the ground monitoring unit includes a pressure difference sensor, and the pressure difference sensor is installed in the mud pool to monitor the pressure change in the mud pool and obtain the pressure difference information of the mud pool.

[0015] In one embodiment, the surface monitoring information includes the liquid level change information of the mud pit; the surface monitoring unit includes a high-frequency radar level gauge, which is located at the wellhead of the well and is used to perform multi-point real-time monitoring on the liquid level height in the mud to obtain the liquid level change information of the mud pit.

[0016] In one embodiment, the downhole monitoring information includes resistivity information, flow velocity information, and fluid component information in the wellbore annulus; the downhole monitoring unit includes an ultrasonic transceiver, which is connected to the controller and is installed on the casing of the wellbore. The ultrasonic transceiver is used to monitor the ultrasonic frequency shift and resistivity in the wellbore annulus and collect the resistivity information, flow velocity information, and fluid component information in the wellbore annulus.

[0017] In one embodiment, the downhole monitoring information includes downhole temperature information, pressure information, and viscosity change information; the downhole monitoring unit includes a temperature sensor, a pressure sensor, and a capacitor. The temperature sensor, the pressure sensor, and the capacitor are respectively connected to the controller and are installed on the casing of the wellbore. The temperature sensor is used to collect temperature information, the pressure sensor is used to collect pressure information, and the capacitor is used to collect viscosity change information.

[0018] A method for monitoring and processing spillage includes:

[0019] Receiving surface monitoring information and downhole monitoring information;

[0020] Performing working condition identification on the surface monitoring information and the downhole monitoring information through a working condition identification model to obtain a working condition identification result;

[0021] Performing overflow monitoring on the surface monitoring information and the downhole monitoring information through an overflow monitoring model corresponding to the working condition identification result;

[0022] In response to detecting an overflow situation, calculating the spillage amount;

[0023] In response to the spillage amount being within a preset spillage range, starting corresponding spillage treatment operations.

[0024] In one embodiment, the surface monitoring information includes at least one of the liquid level change information and the differential pressure information of the mud pit, and the downhole monitoring information includes at least one of the downhole temperature information, pressure information, viscosity change information, resistivity information, flow velocity information, and fluid component information in the wellbore annulus.

[0025] In one embodiment, the method further includes:

[0026] Provide sample surface monitoring information, sample downhole monitoring information, sample wellbore data information, sample surface equipment working status information, and similar working conditions information of adjacent wells or the same formation of the well in the same work area;

[0027] Analyze the sample surface monitoring information, sample downhole monitoring information, sample wellbore data information, sample surface equipment working status information, and similar working conditions information of adjacent wells or the same formation of the well in the same work area through a first neural network, and establish the change characteristics of the parameter information of multiple working conditions;

[0028] Determine the sensitive parameters of each of the working conditions according to the change characteristics of the parameter information of the multiple working conditions;

[0029] Construct the working condition identification model based on the sensitive parameters of each of the working conditions.

[0030] In one embodiment, the method further includes:

[0031] Provide multiple sample working conditions, sample surface monitoring information, and sample downhole monitoring information;

[0032] Analyze the sample working conditions, sample surface monitoring information, and sample downhole monitoring through a second neural network to determine the overflow characterization parameters corresponding to each of the sample working conditions;

[0033] Construct an overflow monitoring model corresponding to each of the sample working conditions based on the overflow characterization parameters corresponding to each of the sample working conditions.

[0034] In one embodiment, the step of initiating a corresponding overflow treatment operation in response to the overflow amount being within a preset overflow range includes:

[0035] In response to the overflow amount being within a preset overflow range, control the overflow treatment unit to perform at least one of throttling, overflow discharging, backpressure control, and well killing.

[0036] In one embodiment, the step of initiating a corresponding overflow treatment operation in response to the overflow amount being within a preset overflow range includes:

[0037] In response to the overflow amount being within a preset overflow range, calculate the overflow amount through a wellbore hydraulics model to obtain drilling fluid density ratio guidance information;

[0038] Control the overflow treatment unit to adjust the drilling fluid density according to the drilling fluid density ratio guidance information.

[0039] In one embodiment, the step of initiating a corresponding overflow treatment operation in response to the overflow amount being within a preset overflow range includes:

[0040] In response to the spillage amount being within a preset spillage range, control the alarm unit to activate an alarm mode corresponding to the spillage amount.

[0041] A spillage monitoring and processing device, comprising:

[0042] A receiving module, configured to receive ground monitoring information and downhole monitoring information;

[0043] A working condition identification module, configured to perform working condition identification on the ground monitoring information and the downhole monitoring information through a working condition identification model to obtain a working condition identification result;

[0044] An overflow monitoring module, configured to perform overflow monitoring on the ground monitoring information and the downhole monitoring information through an overflow monitoring model corresponding to the working condition identification result;

[0045] A calculation module, configured to calculate the spillage amount in response to detecting an overflow situation;

[0046] A control module, configured to initiate corresponding spillage handling operations in response to the spillage amount being within a preset spillage range.

[0047] A computer device, comprising a memory and a processor, where the memory stores a computer program, and when the processor executes the computer program, the following steps are implemented:

[0048] Receive ground monitoring information and downhole monitoring information;

[0049] Perform working condition identification on the ground monitoring information and the downhole monitoring information through a working condition identification model to obtain a working condition identification result;

[0050] Perform overflow monitoring on the ground monitoring information and the downhole monitoring information through an overflow monitoring model corresponding to the working condition identification result;

[0051] Calculate the spillage amount in response to detecting an overflow situation;

[0052] Initiate corresponding spillage handling operations in response to the spillage amount being within a preset spillage range.

[0053] A computer-readable storage medium, on which a computer program is stored, and when the computer program is executed by a processor, the following steps are implemented:

[0054] Receive ground monitoring information and downhole monitoring information;

[0055] Perform working condition identification on the ground monitoring information and the downhole monitoring information through a working condition identification model to obtain a working condition identification result;

[0056] Perform overflow monitoring on the surface monitoring information and downhole monitoring information through an overflow monitoring model corresponding to the working condition recognition result;

[0057] In response to detecting an overflow situation, calculate the spillage volume;

[0058] In response to the spillage volume being within a preset spillage range, initiate corresponding spillage treatment operations.

[0059] The above-mentioned controller for spillage monitoring and processing, as well as the spillage monitoring and processing system, method, device, computer equipment, and computer-readable storage medium having this controller, can perform real-time data monitoring at any position in the wellbore underground, and at the same time monitor the liquid level change of the surface mud pit, etc., to obtain surface monitoring information and downhole monitoring information, identify the current drilling working condition through a working condition recognition model, and perform overflow monitoring for each working condition with an overflow monitoring model; achieve real-time, efficient, and accurate overflow monitoring of downhole complex conditions under each working condition;

[0060] Moreover, the overflow monitoring model can calculate the spillage volume when an overflow situation occurs; according to the spillage volume, the spillage treatment equipment can automatically handle the spillage, reduce the well control risk, and ensure safe and efficient drilling. BRIEF DESCRIPTION OF THE DRAWINGS

[0061] Figure 1 It is a block diagram of a controller for spillage monitoring and processing in an embodiment;

[0062] Figure 2 It is a partial structural schematic diagram of a spillage monitoring and processing system in an embodiment;

[0063] Figure 3 It is a flow schematic diagram of a spillage monitoring and processing method in an embodiment;

[0064] Figure 4 It is a schematic diagram of the implementation process of a spillage monitoring and processing method in an embodiment;

[0065] Figure 5 It is a block diagram of the structure of a spillage monitoring and processing device in an embodiment;

[0066] Figure 6 It is an internal structure diagram of a computer equipment in an embodiment. DETAILED DESCRIPTION OF THE EMBODIMENTS

[0067] In order to make the objectives, technical solutions, and advantages of the present application clearer, the present application will be further described in detail below with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are only used to explain the present application and are not used to limit the present application.

[0068] Embodiment 1

[0069] In this embodiment, Figure 1 As shown, a controller 830 for leakage monitoring and processing is provided, which is connected to a ground monitoring unit 810 and a downhole monitoring unit 820; the controller 830 is configured to receive ground monitoring information from the ground monitoring unit 810 and downhole monitoring information from the downhole monitoring unit 820; the working condition of the ground monitoring information and the downhole monitoring information is identified by a working condition identification model to obtain a working condition identification result; the ground monitoring information and the downhole monitoring information are monitored for overflow by an overflow monitoring model corresponding to the working condition identification result; in response to monitoring the occurrence of overflow, the leakage amount is calculated, and in response to the leakage amount being within a preset leakage range, the controller initiates a corresponding leakage processing operation.

[0070] In this embodiment, the controller 830 for leakage monitoring and processing can be used in deep ground drilling environments for oil and gas exploration; but it is not limited to deep drilling environments, and can also be used for leakage monitoring in deep-sea drilling or ultra-deep drilling environments, which is not limited in this embodiment.

[0071] In one embodiment, the ground monitoring information includes monitoring information such as the liquid level change information and pressure difference information of the mud pool; the downhole monitoring information includes monitoring information such as downhole temperature information, pressure information, viscosity change information, resistivity information in the wellbore annulus, flow rate information and fluid component information.

[0072] In one embodiment, the ground monitoring unit 810 may include a differential pressure sensor, a liquid level meter, etc. installed in the mud pool to monitor the ground information; and the downhole monitoring unit may include various sensors such as an ultrasonic transceiver, a temperature sensor, a pressure sensor, and a capacitor to monitor the downhole information, which is not limited in this embodiment.

[0073] In one embodiment, the drilling conditions include various non-drilling conditions such as pump start and stop, drilling, and single connection, as well as normal drilling conditions. Therefore, in this embodiment, the condition identification result output by the condition identification model is the condition type, which can be, for example, pump start and stop, drilling, or single connection.

[0074] In this embodiment, sample surface monitoring information, sample downhole monitoring information, sample wellbore data information, sample surface equipment working state information, and similar working condition information of adjacent wells or the same formation in the same work area are provided. The first neural network analyzes the sample surface monitoring information, sample downhole monitoring information, sample wellbore data information, sample surface equipment working state information, and similar working condition information of adjacent wells or the same formation in the same work area to establish the change characteristics of each parameter information of multiple working conditions. According to the change characteristics of each parameter information of the multiple working conditions, the sensitive parameters of each working condition are determined. Based on the sensitive parameters of each working condition, a working condition recognition model is constructed. By using this working condition recognition model to recognize the drilling working conditions of the surface monitoring information and downhole monitoring information, the working condition recognition result can be obtained.

[0075] Among them, the first neural network can be a Long Short-Term Memory (LSTM) network. Compared with traditional neural networks, the use of a long short-term memory network in this embodiment can effectively process long sequence data.

[0076] Specifically, the sensitive parameters of different drilling working conditions for downhole monitoring information and surface monitoring information are different. Therefore, in this embodiment, parameter information such as sample downhole monitoring information, sample surface monitoring information, sample wellbore data information, sample surface equipment working state information, and similar working condition information of adjacent wells or the same formation in the same work area is provided. Among them, the working state of surface equipment includes the working states of equipment such as the traveling block and the pump. Wellbore data is obtained by real-time measurement while drilling downhole by a measurement-while-drilling instrument, including monitoring information such as well depth, inclination angle, azimuth angle, temperature, pressure, and acoustic velocity. Similar working condition information of adjacent wells or the same formation in the same work area refers to similar or approximate drilling working conditions in the drilling work area at the same geographical location or in the same formation of the same wellbore. The drilling working conditions include wellbore information, bit state, pressure change information, etc. The first neural network analyzes the above parameter information to establish the change characteristics of the parameter information of each drilling working condition; that is, analyze the working states of surface equipment (traveling block, pump, etc.), combine the temperature, pressure, wellbore data measured while drilling, and parameter information such as downhole monitoring information and surface monitoring information, combine the working conditions of adjacent wells or the same formation in the same work area and historical parameter information, and establish the change characteristics of the above parameter information under each working condition through big data learning according to the change characteristics of the parameter information. According to the change characteristics of the parameter information, the sensitive parameters of each drilling working condition are obtained. Based on the sensitive parameters of each working condition, through comprehensive analysis of multi-source data, a working condition recognition model is constructed based on the first neural network.

[0077] In this embodiment, for different working condition recognition results, that is, different drilling working conditions, an overflow monitoring model corresponding one-to-one to the drilling working conditions is constructed respectively. That is, each drilling working condition corresponds to an overflow monitoring model. Among them, in this embodiment, a second neural network is used, and the provided sample downhole monitoring information, sample surface monitoring information and other information are used as the training set for the training of the second neural network to obtain an overflow monitoring model for different working conditions. Further, the second neural network used in the overflow monitoring model can be a Long Short-Term Memory (LSTM) network. In this way, for the working condition recognition result of the working condition recognition model, through the overflow monitoring model corresponding to the working condition recognition result, the surface monitoring information and the downhole monitoring information are monitored for overflow, and the overflow situation can be accurately monitored, avoiding false alarms caused by human operations and other reasons.

[0078] Specifically, the construction process of the overflow monitoring model is as follows: multiple sample working conditions, sample surface monitoring information and sample downhole monitoring information are provided. Among them, the sample working conditions are specifically the types of working conditions that may occur during the drilling process. The second neural network is used to analyze the sample working conditions and the sample surface monitoring information to determine the overflow characterization parameters corresponding to each of the sample working conditions; based on the overflow characterization parameters corresponding to each of the sample working conditions, an overflow monitoring model corresponding to each of the sample working conditions is constructed. In this embodiment, based on the neural network and through big data training, for the obtained downhole monitoring information, including temperature information, pressure information, viscosity change information, resistivity information, annular velocity information, dielectric constant, annular fluid component information; and the obtained surface monitoring information, including the pressure difference in the mud pit, the total liquid volume in the mud pit and other data, for different working conditions (such as various non-drilling working conditions and normal drilling working conditions like pump start / stop, pipe tripping, connection making), the parameter changes caused by human operation reasons are eliminated; the parameter information is processed and analyzed, and through big data learning, an overflow monitoring model corresponding to each working condition is established based on the artificial neural network. When the working condition recognition model obtains the current working condition recognition result, it switches to the overflow monitoring model corresponding to the working condition recognition result. This overflow monitoring model can accurately monitor the overflow situation, and when an overflow situation occurs, it calculates the leakage volume to avoid false alarms caused by human operations and other reasons.

[0079] In one embodiment, the controller 830 is further configured to be connected to the alarm unit 850; the controller 830 controls the start of corresponding leakage treatment operations, including the controller 830 controlling the alarm unit 850 to turn on the alarm mode corresponding to the leakage volume.

[0080] In this embodiment, the preset overflow range can be determined according to construction requirements and geological features. For example, the preset overflow range value can be set to 100 L, and when the leakage amount reaches 100 L, the controller starts the corresponding leakage treatment operation. Of course, in other embodiments, the preset overflow range can also be a range value of sequentially increasing gears, and the controller starts different leakage treatment operations according to different gear ranges, which is not limited in this embodiment.

[0081] In this embodiment, the alarm unit 850 can be an alarm device such as an alarm. The controller controls the alarm to use different ringing methods for alarm according to different leakage amounts. For example, three alarm gradients are set for the preset leakage range. When the leakage amount is within the first preset leakage range, the controller 830 controls the alarm unit 850 to start the first alarm mode, such as controlling the alarm to use an intermittent and uniform whistling alarm mode; when the leakage amount is within the second preset leakage range, the controller 830 controls the alarm unit 850 to start the second alarm mode, such as controlling the alarm to use a long-short whistling alarm mode; when the leakage amount is within the third preset leakage range, the controller 830 controls the alarm unit 850 to start the third alarm mode, such as controlling the alarm to use a long whistling alarm mode. In this embodiment, by controlling the alarm unit 850 to alarm through the controller 830, the pressure control engineer or the driller can be informed in case of an automatic control system failure and then switch to operations such as well killing by the driller or the pressure control engineer.

[0082] In one embodiment, the controller 830 is further configured to be connected to the leakage treatment unit 840; the controller 830 starting the corresponding leakage treatment operation includes the controller 830 controlling the leakage treatment unit 840 to perform at least one of throttling, overflow discharging, back pressure control, and well killing.

[0083] In this embodiment, the working modes that the leakage treatment unit 840 can perform include throttling, back pressure supplement, circulating overflow discharging, and automatic well killing, etc. The controller 830 controls the leakage treatment unit to use one of the above modes alone or in any combination according to different leakage amounts, and can dynamically adjust the working mode at any time according to the on-site situation.

[0084] In this embodiment, real-time data monitoring can be performed at any position in the wellbore underground, and at the same time, the liquid level change of the surface mud pit, etc. is monitored to obtain surface monitoring information and underground monitoring information. The current drilling working condition is identified through the working condition identification model, and an overflow monitoring model is available for overflow monitoring for each working condition; real-time, efficient, and accurate overflow monitoring of the bottom hole complex situation under each working condition is realized; and, the overflow monitoring model can calculate the leakage amount when an overflow occurs; according to the leakage amount, the leakage treatment unit can automatically handle the leakage, reduce the well control risk, and ensure safe and efficient drilling.

[0085] Embodiment 2

[0086] In this embodiment, a spill monitoring and processing system is provided, which includes a ground monitoring unit, a downhole monitoring unit, and a controller according to any one of the above embodiments;

[0087] The ground monitoring unit and the downhole monitoring unit are respectively connected to the controller. The ground monitoring unit is used to collect ground monitoring information and transmit the ground monitoring information to the controller; the downhole monitoring unit is used to collect downhole monitoring information and transmit the downhole monitoring information to the controller.

[0088] The ground monitoring unit specifically refers to a device or system unit for monitoring and collecting ground environmental data, and usually includes components such as sensors, data acquisition devices, communication equipment, and data processing software. The downhole monitoring unit specifically refers to a device or system unit for monitoring and collecting downhole environmental data, which is usually installed downhole and used to monitor various parameters and conditions downhole, and may include components such as sensors, data acquisition devices, communication equipment, and data processing software.

[0089] In one embodiment, the downhole monitoring information includes resistivity information, flow velocity information, and fluid component information in the wellbore annulus; the downhole monitoring unit includes an ultrasonic transceiver, which is connected to the controller. The ultrasonic transceiver is installed on the casing of the wellbore and is used to monitor the ultrasonic frequency shift and resistivity in the wellbore annulus, and collect resistivity information, flow velocity information, and fluid component information in the wellbore annulus.

[0090] In this embodiment, the downhole monitoring unit is used to collect downhole monitoring information, and the downhole monitoring information includes resistivity information, flow velocity information, and fluid component information in the wellbore annulus. Specifically, the downhole monitoring unit includes an ultrasonic transceiver, and the ultrasonic transceiver is used to monitor the ultrasonic frequency shift and resistivity in the wellbore annulus and collect resistivity information, flow velocity information, and fluid component information in the wellbore annulus. In other embodiments, electrolyte sensors, flow meters and other acquisition devices can also be used to collect resistivity information, flow velocity information, and fluid component information in the wellbore annulus, and this embodiment is not limited.

[0091] In one embodiment, the downhole monitoring information includes downhole temperature information, pressure information, and viscosity change information; the downhole monitoring unit includes a temperature sensor, a pressure sensor, and a capacitor. The temperature sensor, the pressure sensor, and the capacitor are respectively electrically connected to the controller. The temperature sensor, the pressure sensor, and the capacitor are installed on the casing of the wellbore. The temperature sensor is used to collect temperature information, the pressure sensor is used to collect pressure information, and the capacitor is used to collect viscosity change information.

[0092] In this embodiment, the downhole monitoring unit is used to collect temperature information, pressure information, and viscosity change information in the well. Specifically, the downhole monitoring unit includes a temperature sensor, a pressure sensor, and a capacitor. The temperature sensor is used to collect temperature information, the pressure sensor is used to collect pressure information, and the capacitor is used to collect viscosity change information. In other embodiments, the downhole monitoring unit may also be provided with other sensors such as a flowmeter, which is not limited in this embodiment.

[0093] In one embodiment, the system further includes an optical fiber cable data transmission unit. The surface monitoring unit and the downhole monitoring unit are respectively connected to the controller through the optical fiber cable data transmission unit. The surface monitoring unit is used to transmit the surface monitoring information to the controller through the optical fiber cable data transmission unit, and the downhole monitoring unit is used to transmit the downhole monitoring information to the controller through the optical fiber cable data transmission unit. The optical fiber cable data transmission unit includes an embedded or buried optical fiber cable.

[0094] In one embodiment, the system is also provided with an optical fiber cable data transmission unit for transmitting downhole monitoring information and / or surface monitoring information to ensure stable data transmission and reduce the possibility of loss.

[0095] In this embodiment, as Figure 2 shown, the downhole monitoring unit includes equipment for monitoring the annulus leakage condition by non-contact ultrasonic waves at a certain position of the downhole casing 11. Specifically, a monitoring sub 8 is provided at a specified position of the casing 11, and a monitoring device 9 is arranged inside the monitoring sub 8. The monitoring device 9 includes various sensors such as ultrasonic transceivers, temperature, and pressure, as well as capacitors. The flow velocity in the annulus and the fluid dielectric constant are obtained by monitoring ultrasonic frequency shift and resistivity. At the same time, parameters such as temperature, pressure, density, and viscosity change are respectively obtained through various sensors, and each parameter information is transmitted to the controller for analyzing the intrusion phase content, fluid components, etc., and then the downhole monitoring information is collected. The downhole monitoring information includes temperature information, pressure information, viscosity change information, resistivity information, flow velocity information in the wellbore annulus, and fluid component information.

[0096] In this embodiment, the data transmission method of the downhole monitoring unit includes not only the mud pulse transmission commonly used during normal drilling, but also the optical fiber cable method for transmission, that is, an optical fiber cable data transmission unit is provided. Among them, continuing to refer to Figure 2 shown, the optical fiber and the cable can be placed in one cable to form an optical fiber cable 12. The optical fiber cable 12 is used to provide electrical energy and a data transmission channel.

[0097] In some embodiments, the fiber optic cable 12 can be lowered into the annulus 10 when lowering the casing 11 in various ways, such as being embedded within the casing 11, fixed to the surface layer of the casing 11, fixed to the centralizer, or semi-embedded within the casing 11. In this embodiment, the fiber optic cable 12 is fixedly installed by being pre-buried in the downhole cement sheath or embedded within the outer wall of the downhole casing.

[0098] In this embodiment, the external shape of the fiber optic cable 12 can be flat oval, and a semi-open groove with a matching size can be cut on the surface layer of the casing 11, enabling the fiber optic cable 12 to be easily embedded into the wall of the casing 11, or it can also be inserted into the groove of the casing 11 through a mechanical zipper method. In other embodiments, the external shape of the fiber optic cable 12 can also be designed into various suitable shapes such as rectangular, circular, etc. according to the wall thickness strength of the casing, and this embodiment is not limited.

[0099] Among them, the outer surface of the fiber optic cable 12 itself is coated with a coating layer having certain tensile and extrusion resistance capabilities. In some embodiments, the coating layer can be structures such as an insulating layer, steel wire braid, aluminum layer, rubber skin, etc., which are not listed one by one herein.

[0100] In other embodiments, the optical fiber and the cable are not limited to being placed within a single pipeline, and any arrangement passing through the casing wall or being buried within the cement sheath is within the scope of protection.

[0101] In one embodiment, the surface monitoring information includes the differential pressure information of the mud pit; the surface monitoring unit includes a differential pressure sensor, and the differential pressure sensor is installed in the mud pit and is used to monitor the pressure change in the mud pit to obtain the differential pressure information of the mud pit.

[0102] In this embodiment, the surface monitoring unit is used to collect surface monitoring information, and the surface monitoring information includes the differential pressure information of the mud pit. Specifically, the surface monitoring unit includes a differential pressure sensor, and the differential pressure sensor is used to monitor the pressure change in the mud pit to obtain the differential pressure information of the mud pit.

[0103] In one embodiment, the surface monitoring information includes the liquid level change information of the mud pit; the surface monitoring unit includes a high-frequency radar level gauge, and the high-frequency radar level gauge is located at the wellhead of the drilling and is used to perform multi-point real-time monitoring on the liquid level height in the mud to obtain the liquid level change information of the mud pit.

[0104] In this embodiment, the surface monitoring unit is used to collect surface monitoring information, and the surface monitoring information includes the differential pressure information of the mud pit. Specifically, the surface monitoring unit includes a high-frequency radar level gauge, and the high-frequency radar level gauge is used to perform multi-point real-time monitoring on the liquid level height in the mud to obtain the liquid level change information of the mud pit. Of course, in other embodiments, collection devices such as level gauges and flow meters can also be used to collect the liquid level height information in the mud, and this embodiment is not limited.

[0105] In this embodiment, continue to refer to Figure 2 As shown in the figure, the surface monitoring unit includes a differential pressure sensor 5 arranged in the mud pit 6, a temperature sensor installed at the bottom of the mud pit 6, a flowmeter 1 arranged at the outlet of the mud pit 6, a high-frequency radar liquid level gauge 4 installed at the wellhead, etc. The surface monitoring information is collected through the above devices. The surface monitoring information includes the liquid level change information and differential pressure information of the mud pit.

[0106] Among them, the high-frequency radar liquid level gauge 4 is used to monitor the liquid level height of the mud pit 6 at multiple points in real time, and the real-time change of the liquid level and the total liquid volume are obtained by the averaging method. The flowmeter 1 can accurately measure the flow rate at the outlet and is used to compare with the inlet flow rate converted by the pump stroke number, so as to judge whether there is a working condition or a leakage situation.

[0107] Among them, multiple measuring points of the differential pressure sensor 5 are evenly arranged in the mud pit and are transmitted through the above optical fiber cable method. Among them, multiple differential pressure sensors 5 can be fixed by being placed on the inner side wall of the mud pit 6 or fixed to the mud pit 6 through a fixing rod. By measuring the values of different differential pressure sensors, it is judged whether there is oil and gas overflow in the mud pit 6.

[0108] The specific monitoring principle is as follows: when the density of the drilling fluid remains unchanged, the vertical height difference between multiple differential pressure sensors 5 is the same, so the data output by the differential pressure sensors 5 should be consistent; if the bottom-hole fluid invades the wellbore and causes bubbles or low-density fluid in the drilling fluid, the measured differential pressures obtained by the differential pressure sensors 5 are inconsistent. Therefore, it is possible to judge whether there are complex conditions at the bottom hole by detecting the measurement data of the differential pressure sensors 5.

[0109] In one embodiment, the controller is further configured to receive sample surface monitoring information, sample downhole monitoring information, sample wellbore data information, sample surface equipment working state information, and similar working condition information of adjacent wells or the same formation of this well in the same work area; analyze the sample surface monitoring information, sample downhole monitoring information, sample wellbore data information, sample surface equipment working state information, and similar working condition information of adjacent wells or the same formation of this well in the same work area through a first neural network to establish the change characteristics of the parameter information of multiple working conditions; determine the sensitive parameters of each of the working conditions according to the change characteristics of the parameter information of multiple working conditions; and construct a working condition recognition model based on the sensitive parameters of each of the working conditions.

[0110] In one embodiment, the controller is further configured to receive a plurality of sample working conditions, sample surface monitoring information, and sample downhole monitoring information; parse the sample working conditions, sample surface monitoring information, and sample downhole monitoring through a second neural network to determine the overflow characterization parameters corresponding to each of the sample working conditions; and construct an overflow monitoring model corresponding to each of the sample working conditions based on the overflow characterization parameters corresponding to each of the sample working conditions.

[0111] For the specific limitations on the controller for leakage monitoring and processing, reference may be made to the specific limitations on the controller in Embodiment 1 above, which will not be elaborated here.

[0112] In one embodiment, the leakage monitoring and processing system further includes an alarm unit, and the alarm unit is connected to the controller. The controller starting the corresponding leakage processing operation includes the controller controlling the alarm unit to turn on an alarm mode corresponding to the leakage volume.

[0113] In this embodiment, the alarm unit analyzes the leakage volume calculated by the overflow monitoring model, establishes a leakage degree discrimination criterion, which is determined according to the construction requirements and geological characteristics, to obtain a preset leakage range value.

[0114] In one embodiment, the preset leakage range value is set at 100 L. When the calculated leakage volume reaches 100 L, the alarm mode corresponding to the leakage volume is turned on.

[0115] Furthermore, there are multiple alarm gradients set for the preset leakage range. If the controller determines that the leakage volume is within different preset leakage ranges, it controls the alarm unit to turn on different alarm modes.

[0116] In this embodiment, continue to refer to Figure 2 As shown, there are three alarm gradients preset in the leakage degree discrimination criterion according to the overflow degree. The alarm unit uses an alarm 7 to give alarms in different ringing manners. For example, when the leakage volume is within the first preset leakage range, the first alarm mode is controlled to be turned on, such as the alarm 7 using an intermittent and uniform whistling alarm mode; when the leakage volume is within the second preset leakage range, the second alarm mode is controlled to be turned on, such as the alarm 7 using a one-long-one-short whistling alarm mode; when the leakage volume is within the third preset leakage range, the third alarm mode is controlled to be turned on, such as the alarm 7 using a long whistling alarm mode. In this embodiment, by setting the alarm mode, the pressure control engineer or the driller can be informed in case of failure of the automatic control system so as to switch to operations such as the driller or the pressure control engineer conducting well killing.

[0117] In one embodiment, the spill monitoring and processing system further includes a spill processing unit, which is connected to the controller. The controller starting the corresponding spill processing operation includes the controller controlling the spill processing unit to perform at least one of throttling, overflow discharging, backpressure control, and well killing.

[0118] In one embodiment, the controller starting the corresponding spill processing operation includes calculating the spill volume through a wellbore hydraulics model to obtain drilling fluid density ratio guidance information; and controlling the spill processing unit to adjust the drilling fluid density according to the drilling fluid density ratio guidance information.

[0119] In this embodiment, continue to refer to Figure 2 As shown, the spill processing unit includes a surface drilling pump, a backpressure pump 3, an automatic choke valve 2, etc. When monitoring complex conditions such as a spill at the bottom of the well, the automatic choke valve 2 can be used to throttle and control the pressure in the wellbore or throttle and blow out to prevent a blowout; when the overflow condition is not suppressed after simple throttling, the drilling pump can be used for circulating overflow discharging or adjusting the drilling fluid density; when the circulating overflow discharging or adjusting the drilling fluid density fails to completely handle the overflow, the backpressure pump 3 can be used to supplement the drilling fluid in the annulus 10 to balance the bottom hole pressure; when the overflow degree is large, the backpressure pump 3 can assist the driller to perform the engineer's method of well killing. The automatic throttling, backpressure supplementing, circulating overflow discharging, and automatic well killing in the overflow processing equipment can be dynamically adjusted at any time, or used in combination or separately, and can be adjusted according to the on-site conditions.

[0120] In this embodiment, when the overflow degree is relatively light, the controller controls the overflow by controlling the automatic choke valve 2 or the surface backpressure pump 3 of the spill processing unit; at the same time, the controller is also used to establish a dynamic coupling relationship between the automatic choke valve 2, the backpressure pump 3, and the pressure in the wellbore, autonomously learn to regulate the wellbore pressure, calculate the spill volume based on the hydraulics model to obtain drilling fluid density ratio guidance information, and control the spill processing unit to perform circulating overflow discharging and well killing drilling fluid density ratio adjustment according to the drilling fluid density ratio guidance information. This enables autonomous dynamic regulation of the surface sequential drilling fluid density, backpressure supplementing, opening of the automatic choke valve 2, etc. for spill processing operations when a spill is detected.

[0121] In this embodiment, a monitoring tool is lowered at the casing, and data is transmitted in real time through an optical fiber cable. Differential pressure sensors are evenly installed in the surface mud pit to monitor the pressure fluctuations in the mud pit and the changes in the total liquid volume in the mud pit in real time, and the data is transmitted to the data processing center. A working condition recognition model is established based on the neural network algorithm according to the sensitivity parameters under various working conditions, and the sensitivity parameters of the data processing center are analyzed to identify the working conditions, and then switched to the overflow monitoring model corresponding to the working condition. According to the changes in the sensitivity parameters under various working conditions, an overflow monitoring model based on neural network autonomous learning is established through big data training based on the overflow and leakage occurrence conditions under the same working condition or in adjacent wells, and the parameters under this working condition are monitored, calculated, and the overflow and leakage conditions are displayed in real time. At the same time, a choke manifold and a backpressure pump are equipped, supplemented by a drilling pump, to provide equipment support for the overflow and leakage treatment equipment. According to the degree of overflow and leakage, an intelligent decision-making treatment algorithm for overflow and leakage is established based on the wellbore hydraulics theory. By adjusting the throttle valve, backpressure pump, drilling pump, drilling fluid density, etc. of the overflow and leakage treatment equipment, the bottom hole overflow and leakage are processed in time to avoid blowout.

[0122] Through the overflow and leakage monitoring and intelligent decision-making treatment under various working conditions, the false overflow and leakage alarms caused by human operation, working condition change, etc. are eliminated, and the reliability of the overflow and leakage monitoring alarm is increased. By real-time monitoring and alarming of the overflow and leakage conditions in the wellbore, the defect of insufficient timeliness of surface overflow and leakage monitoring is overcome, a longer operation time is given for overflow treatment, and the well control risk is reduced. The stability of the monitoring tool is ensured by transmitting through an optical fiber cable and installing it at a specified position on the casing, the noise is reduced, and the effectiveness and real-time nature of the data are ensured. The monitoring of the differential pressure sensor in the surface mud pit overcomes the influence of bubbles, etc. on the radar level gauge, ultrasonic level gauge, etc., and improves the accuracy of the surface overflow and leakage volume monitoring. The intelligent overflow and leakage decision-making treatment can select appropriate methods to balance the formation pressure for different overflow and leakage situations, greatly reducing the on-site manual workload, reducing the on-site operating personnel, and ensuring the safety of personnel's lives. This embodiment can be integrated into the drilling system and become an important part of intelligent drilling, which is of great significance for ensuring safe and efficient drilling.

[0123] Embodiment III

[0124] In this embodiment, as Figure 3 shown, a method for monitoring and treating overflow and leakage is provided, which includes:

[0125] Step 110, receiving surface monitoring information and downhole monitoring information.

[0126] In this embodiment, the surface monitoring information and downhole monitoring information include the liquid level change information and differential pressure information, temperature information, pressure information, viscosity change information, resistivity information in the wellbore annulus, flow velocity information, and fluid component information of the mud pit.

[0127] In one embodiment, an ultrasonic transceiver, various sensors such as temperature and pressure sensors, and capacitors can be used to monitor the downhole conditions and collect downhole monitoring information; and by setting differential pressure sensors, temperature sensors, liquid level gauges, etc. in the mud pit, the ground conditions can be monitored and ground monitoring information can be collected. In other embodiments, other sensors can also be set to monitor the ground and downhole, which are not listed one by one in this embodiment.

[0128] Step 120: Perform a working condition identification on the ground monitoring information and the downhole monitoring information through a working condition identification model to obtain a working condition identification result.

[0129] In this embodiment, through the working condition identification model to perform a working condition identification on the ground monitoring information and the downhole monitoring information, the working condition identification model can intelligently identify the current working condition and output a working condition identification result.

[0130] In one embodiment, the working conditions include various non-drilling working conditions such as pump start / stop, pipe tripping, and connection making, as well as normal drilling working conditions. Therefore, in this embodiment, the working condition identification result output by the working condition identification model is the working condition type. For example, it is pump start / stop, pipe tripping, or connection making.

[0131] Step 130: Perform a kick monitoring on the ground monitoring information and the downhole monitoring information through a kick monitoring model corresponding to the working condition identification result.

[0132] In this embodiment, for different drilling working conditions, a kick monitoring model corresponding to the drilling working condition is respectively constructed, that is, each drilling working condition corresponds to a kick monitoring model. Based on the current working condition identification result, the ground monitoring information and the downhole monitoring information are input into the kick monitoring model corresponding to the current working condition identification result for kick monitoring, which can accurately monitor the kick situation and avoid false alarms caused by human operations and other factors.

[0133] Step 140: In response to detecting a kick situation, calculate the kick volume.

[0134] In this embodiment, when the kick monitoring models corresponding to each working condition perform kick monitoring, they can calculate the kick volume when a kick situation occurs.

[0135] Step 150: In response to the kick volume being within a preset kick range, start a corresponding kick treatment operation.

[0136] In this embodiment, when the kick volume is within the preset kick range, starting a corresponding kick treatment operation can handle the kick situation that occurs, so as to reduce the well control risk and achieve safe and efficient drilling.

[0137] In one embodiment, the surface monitoring information includes at least one of the liquid level change information and the differential pressure information of the mud pit, and the downhole monitoring information includes at least one of the temperature information, pressure information, viscosity change information, resistivity information in the wellbore annulus, flow rate information, and fluid component information downhole.

[0138] In this embodiment, the downhole overflow monitoring device and the surface overflow monitoring device can be used to monitor the downhole and the surface respectively, so as to obtain the liquid level change information and differential pressure information of the mud pit, temperature information, pressure information, viscosity change information, resistivity information in the wellbore annulus, flow rate information, and fluid component information.

[0139] Among them, the downhole overflow monitoring device includes a device for monitoring the annulus leakage situation by non-contact ultrasonic waves at a certain position of the downhole casing. Specifically, a monitoring sub is set at a specified position of the casing, and a monitoring device is arranged inside the monitoring sub. The monitoring device includes various sensors such as ultrasonic transceivers, temperature, and pressure, as well as capacitors, etc.; the flow velocity in the annulus and the fluid dielectric constant are obtained by monitoring the ultrasonic frequency shift and resistivity. At the same time, parameters such as temperature, pressure, density, and viscosity are obtained through various sensors respectively, and the parameter information is transmitted to the controller to analyze the intrusion phase content, fluid components, etc., and then the downhole monitoring information is collected. The downhole monitoring information includes temperature information, pressure information, viscosity change information, resistivity information, flow velocity information in the wellbore annulus, and fluid component information.

[0140] In this embodiment, the data transmission method of the downhole overflow monitoring device includes not only the mud pulse transmission commonly used during normal drilling, but also the fiber optic cable method for transmission. Among them, the optical fiber and the cable can be placed in one cable to provide a power and data transmission channel. The fiber optic cable can be lowered into the annulus when the casing is lowered in various ways such as being embedded in the casing, fixed on the surface of the casing, fixed on the centralizer, and semi-embedded in the casing.

[0141] In other embodiments, the optical fiber line and the cable line are not limited to being placed in one pipeline, and any setting through the casing wall or buried in the cement sheath is within the scope of protection.

[0142] Among them, the surface overflow monitoring device includes a differential pressure sensor arranged in the mud pit, a temperature sensor installed at the bottom of the mud pit, a flow meter arranged at the outlet of the mud pit, and a high-frequency radar level gauge installed at the wellhead, etc. The surface monitoring information is collected through the above devices. Among them, the surface monitoring information includes the liquid level change information and differential pressure information of the mud pit.

[0143] Among them, the high-frequency radar liquid level gauge is used for multi-point real-time monitoring of the liquid level height of the mud pit, and the real-time change of the liquid level and the total liquid volume are obtained through the averaging method. The flowmeter can accurately measure the flow rate at the outlet, which is used to compare with the inlet flow rate converted by the pump stroke number, and then used to judge whether there are working conditions or spillage situations.

[0144] Among them, a plurality of measuring points are evenly arranged in the mud pit by the differential pressure sensor, and are transmitted by the above optical fiber cable method. Among them, a plurality of differential pressure sensors can be fixed by being placed on the inner side wall of the mud pit or fixed to the mud pit by a fixing rod. By measuring the values of different differential pressure sensors, it is judged whether there is oil and gas overflow in the mud pit.

[0145] In one embodiment, the spillage monitoring and processing method further includes: providing sample surface monitoring information, sample downhole monitoring information, sample wellbore data information, sample surface equipment working state information, and similar working condition information of adjacent wells or the same formation of the well in the same work area; parsing the sample surface monitoring information, sample downhole monitoring information, sample wellbore data information, sample surface equipment working state information, and similar working condition information of adjacent wells or the same formation of the well in the same work area through a first neural network, and establishing the change characteristics of the parameter information of multiple working conditions; determining the sensitive parameters of each of the working conditions according to the change characteristics of the parameter information of the multiple working conditions; constructing a working condition identification model based on the sensitive parameters of each of the working conditions.

[0146] In this embodiment, the construction process of the working condition recognition model includes: providing parameter information such as sample downhole monitoring information, sample surface monitoring information, sample wellbore data information, sample surface equipment working state information, and similar upper working condition information of adjacent wells or the same formation of the well in the same work area. Among them, the working state of the surface equipment includes the working states of equipment such as the traveling block and the pump. The wellbore data is obtained by real-time downhole acquisition using a measurement-while-drilling instrument, and includes monitoring information such as well depth, inclination angle, azimuth angle, temperature, pressure, and acoustic wave velocity. The similar upper working condition information of adjacent wells or the same formation of the well in the same work area refers to similar or approximate drilling working conditions in a drilling work area at the same geographical location or in the same formation of the same wellbore. The drilling working conditions include wellbore information, bit state, pressure change information, etc. Analyze the above parameter information through a first neural network to establish the change characteristics of the parameter information of each drilling working condition; that is, analyze the working states of surface equipment (such as the traveling block and the pump), combine the temperature, pressure, wellbore data measured while drilling, as well as downhole monitoring information and surface monitoring information and other parameter information, combine the similar working conditions of adjacent wells or the same formation of the well in the same work area and historical parameter information, and establish the change characteristics of the above parameter information under each working condition through big data learning according to the change characteristics of the parameter information; according to the change characteristics of the parameter information, obtain the sensitive parameters of each drilling working condition, and based on the sensitive parameters of each working condition, through comprehensive analysis of multi-source data, construct a working condition recognition model based on the first neural network.

[0147] In one embodiment, the spill monitoring and processing method further includes: providing a plurality of sample working conditions, sample surface monitoring information, and sample downhole monitoring information; analyzing the sample working conditions, sample surface monitoring information, and sample downhole monitoring through a second neural network to determine the overflow characterization parameters corresponding to each sample working condition; and constructing an overflow monitoring model corresponding to each sample working condition based on the overflow characterization parameters corresponding to each sample working condition.

[0148] In this embodiment, the construction process of the overflow monitoring model includes providing a plurality of sample working conditions, sample surface monitoring information, and sample downhole monitoring information. Among them, the sample working conditions are specifically the types of working conditions that may occur during the drilling process. The second neural network is used to analyze the sample working conditions and sample surface monitoring information to determine the overflow characterization parameters corresponding to each of the sample working conditions; based on the overflow characterization parameters corresponding to each of the sample working conditions, an overflow monitoring model corresponding to each of the sample working conditions is constructed. In this embodiment, based on the neural network and through big data training, for the obtained downhole monitoring information, including temperature information, pressure information, viscosity change information, resistivity information, annular flow velocity information, dielectric constant, annular fluid component information; and the obtained surface monitoring information, including the pressure difference in the mud pit, total mud pit liquid volume, etc. data, for different working conditions (such as various non-drilling working conditions and normal drilling working conditions like pump start / stop, tripping in / out, connecting pipe), eliminate the parameter changes caused by human operation reasons; process and analyze each parameter information, through big data learning, establish an overflow monitoring model corresponding to each working condition based on the artificial neural network. When the working condition recognition model obtains the current working condition recognition result, switch to the overflow monitoring model corresponding to this working condition recognition result. This overflow monitoring model can accurately monitor the overflow situation, and when the overflow situation occurs, calculate the overflow and leakage amount to avoid false alarms caused by human operation and other reasons.

[0149] In one embodiment, the step of, in response to the overflow and leakage amount being within a preset overflow and leakage range, starting a corresponding overflow and leakage treatment operation includes: in response to the overflow and leakage amount being within a preset overflow and leakage range, controlling the overflow and leakage treatment unit to perform at least one of throttling, overflow discharging, backpressure control, and well killing.

[0150] In one embodiment, the step of, in response to the overflow and leakage amount being within a preset overflow and leakage range, starting a corresponding overflow and leakage treatment operation includes: in response to the overflow and leakage amount being within a preset overflow and leakage range, calculating the overflow and leakage amount through the wellbore hydraulics model to obtain drilling fluid density ratio guidance information; according to the drilling fluid density ratio guidance information, controlling the overflow and leakage treatment unit to adjust the drilling fluid density.

[0151] In this embodiment, when an overflow situation is detected and the leakage volume is within the preset leakage range, the leakage treatment unit is controlled to perform an overflow treatment operation to solve the leakage problem and reduce the well control risk. Specifically, the leakage treatment unit includes a surface drilling pump, a backpressure pump, an automatic choke valve, etc. When detecting complex situations such as bottom-hole leakage, the pressure in the wellbore can be controlled by throttling through the automatic choke valve or throttling and flowing back, to avoid blowout; when the overflow situation is not suppressed after simple throttling, the drilling pump can be used for circulating and discharging the overflow or adjusting the density of the drilling fluid; when the circulating and discharging the overflow or adjusting the density of the drilling fluid fails to completely dispose of the overflow, the backpressure pump can be used to supplement the drilling fluid in the annulus to balance the bottom-hole pressure; when the degree of overflow is large, the backpressure pump is used to assist the driller in performing the engineer's method of well killing. The automatic throttling, backpressure supplement, circulating and discharging the overflow, and automatic well killing in the overflow treatment equipment can be dynamically adjusted at any time, or used in combination or alone, and can be adjusted according to the on-site situation.

[0152] In this embodiment, when the degree of overflow is relatively light, the overflow is controlled by controlling the automatic choke valve or the surface backpressure pump of the leakage treatment unit; at the same time, a dynamic coupling relationship between the automatic choke valve, the backpressure pump and the pressure in the wellbore is established, and the wellbore pressure is autonomously learned and regulated. Based on the hydraulics model, the leakage volume is calculated to obtain the guidance information on the drilling fluid density ratio, and the leakage treatment unit is controlled according to the guidance information on the drilling fluid density ratio to perform circulating and discharging the overflow and adjusting the density ratio of the well-killing drilling fluid. So that when an overflow is detected, the ground sequential drilling fluid density, backpressure supplement, and opening of the automatic choke valve can be autonomously and dynamically regulated for leakage treatment.

[0153] In one embodiment, the step of starting the corresponding leakage treatment operation in response to the leakage volume being within the preset leakage range includes: in response to the leakage volume being within the preset leakage range, controlling the alarm unit to turn on the alarm mode corresponding to the leakage volume.

[0154] In this embodiment, when an overflow situation is detected and the leakage volume is within the preset leakage range, the alarm unit is controlled to perform an alarm unit operation to inform the pressure control engineer or the driller, in case of switching to operations such as the driller or the pressure control engineer performing well killing after the automatic control system fails. Specifically, the preset overflow range can be determined according to the construction requirements and geological characteristics. For example, the preset overflow range value can be set to 100L, and when the leakage volume reaches 100L, the controller starts the corresponding leakage treatment operation. Of course, in other embodiments, the preset overflow range can also be a stepwise increasing range value, and the controller starts different leakage treatment operations according to different range values. This embodiment is not limited.

[0155] In this embodiment, the alarm unit may be an alarm device such as an alarm. The controller controls the alarm to use different ringing methods for alarm according to different spillage amounts. For example, three alarm gradients are set in the preset spillage range. When the spillage amount is within the first preset spillage range, the controller controls the alarm unit to turn on the first alarm mode, such as controlling the alarm to use an intermittent uniform whistling alarm mode; when the spillage amount is within the second preset spillage range, the controller controls the alarm unit to turn on the second alarm mode, such as controlling the alarm to use a long-and-short whistling alarm mode; when the spillage amount is within the third preset spillage range, the controller controls the alarm unit to turn on the third alarm mode, such as controlling the alarm to use a long whistling alarm mode. In this embodiment, by controlling the alarm unit to alarm through the controller, the control pressure engineer or the driller can be informed for operations such as killing the well by the driller or the control pressure engineer after the automatic control system fails.

[0156] In this embodiment, real-time data monitoring can be performed at any position in the wellbore underground, and at the same time, the liquid level change of the surface mud pit, etc. is monitored to obtain surface monitoring information and underground monitoring information. The current drilling working condition is identified through the working condition identification model, and an overflow monitoring model is used for overflow monitoring for each working condition; real-time, efficient, and accurate overflow monitoring of the bottom hole complex conditions under each working condition is realized; and, the overflow monitoring model can calculate the spillage amount when an overflow occurs; according to the spillage amount, the spillage treatment equipment can automatically process the spillage, reduce the well control risk, and ensure safe and efficient drilling.

[0157] Embodiment 4

[0158] In this embodiment, a spillage monitoring and processing method is provided, which can take into account the human operation factors under each drilling working condition and eliminate false spillage situations caused by humans or working condition changes.

[0159] Please combine Figure 4 as shown, the implementation steps are as follows:

[0160] Step 21, obtaining multi-source parameter information such as drilling parameters, wellbore data, equipment operating status, annular flow velocity, and liquid tank liquid volume.

[0161] Among them, the equipment operating status includes the working status of equipment such as the traveling block and the pump.

[0162] The wellbore data and drilling parameters are obtained by real-time acquisition underground by a measurement-while-drilling instrument, including monitoring information such as well depth, inclination angle, azimuth angle, temperature, pressure, and acoustic velocity.

[0163] Annular velocity refers to the velocity at which drilling fluid flows through the annulus between the drill pipe and the wellbore during drilling operations. Annular velocity information can be obtained through downhole monitoring units. In this embodiment, the downhole monitoring unit is used to collect downhole monitoring information, and the downhole monitoring information includes temperature information, pressure information, viscosity change information, resistivity information in the wellbore annulus, flow velocity information, and fluid component information in the wellbore. Specifically, the downhole monitoring unit includes equipment for monitoring annulus leakage conditions using non-contact ultrasonic waves at a certain position of the downhole casing. Further, a monitoring sub is provided at a specified position of the casing, and a monitoring device is provided inside the monitoring sub. The monitoring device includes various sensors such as ultrasonic transceivers, temperature, pressure, etc., and capacitors, etc.; the flow velocity in the annulus and the fluid dielectric constant are obtained by monitoring ultrasonic frequency shift and resistivity, and at the same time, parameters such as temperature, pressure, density, and viscosity are obtained through various sensors respectively.

[0164] The liquid volume in the liquid tank is the total liquid volume in the mud pit, and the liquid volume information in the liquid tank can be obtained through the surface monitoring unit. In this embodiment, the surface monitoring unit includes a differential pressure sensor arranged in the mud pit, a temperature sensor installed at the bottom of the mud pit, a flowmeter arranged at the outlet of the mud pit, and a high-frequency radar level gauge installed at the wellhead, etc. The surface information obtained by the surface monitoring unit includes the liquid level change information, differential pressure information, and the total liquid volume of the mud pit, etc.

[0165] Among them, the high-frequency radar level gauge is used to perform multi-point real-time monitoring on the liquid level height of the mud pit, and the real-time change and total liquid volume of the liquid level are obtained through the averaging method. The flowmeter can accurately measure the flow rate at the outlet and is used to compare with the inlet flow rate converted by the pump stroke count, and is further used to judge whether there are working conditions or leakage occurrences.

[0166] Among them, a plurality of measuring points of the differential pressure sensor are evenly arranged in the mud pit and are transmitted through the above-mentioned optical fiber cable method. Among them, a plurality of differential pressure sensors can be fixed by being placed on the inner side wall of the mud pit or fixed to the mud pit through a fixing rod. By measuring the values of different differential pressure sensors, it is judged whether there is oil and gas overflow in the mud pit.

[0167] Step 22, autonomous working condition identification of multi-source data.

[0168] Autonomous identification of the working condition is performed according to the above-obtained multi-source parameter information.

[0169] Among them, the working conditions include normal drilling, starting and stopping the pump, tripping in and out of the pipe string, and making a connection, etc.

[0170] In this embodiment, a working condition identification model is used to autonomously identify the drilling working conditions, and an overflow monitoring model is provided for overflow monitoring for each working condition, so as to realize real-time, efficient, and accurate overflow monitoring of the bottomhole complex conditions under each working condition.

[0171] Among them, the construction process of the working condition recognition model includes obtaining sample surface monitoring information, sample downhole monitoring information, sample wellbore data information, sample surface equipment working state information, and similar working condition information of adjacent wells or the same formation of the well in the same work area; parsing the sample surface monitoring information, sample downhole monitoring information, sample wellbore data information, sample surface equipment working state information, and similar working condition information of adjacent wells or the same formation of the well in the same work area through a first neural network to establish the change characteristics of each parameter information of multiple working conditions; determining the sensitive parameters of each working condition according to the change characteristics of each parameter information of multiple working conditions; and constructing a working condition recognition model based on the sensitive parameters of each working condition.

[0172] Step 23, overflow monitoring program and display under the recognized working condition.

[0173] Perform overflow monitoring program and display according to the recognized working condition.

[0174] Among them, step 23 includes step 231, ground data acquisition, and step 232, acquisition of temperature, pressure, viscosity, density, dielectric constant, fluid composition, gas holdup, etc. in the wellbore.

[0175] Specifically, step 213 is the acquisition of surface monitoring information, where the surface monitoring information includes the flow rates at the inlet and outlet of the mud pit and the total liquid volume in the mud pit. Step 232 is the acquisition of downhole monitoring information, and the downhole monitoring information includes temperature, pressure, viscosity, density, dielectric constant, fluid composition, gas holdup, etc. in the wellbore. The surface monitoring information can be obtained through a surface monitoring unit, and the downhole monitoring information can be obtained through a downhole monitoring unit.

[0176] Input the obtained surface monitoring information and downhole monitoring information into the overflow monitoring model corresponding to the working condition recognition result for overflow monitoring, ensuring that the overflow situation can be accurately monitored and alarmed for any working condition, and avoiding false alarms caused by human operations, etc.

[0177] Specifically, the construction process of the overflow monitoring model is as follows: Based on a neural network, through big data training, for the obtained downhole monitoring information, including temperature information, pressure information, viscosity change information, resistivity information, annular flow velocity information, dielectric constant, annular fluid composition information; and the obtained surface monitoring information, including the pressure difference in the mud pit, the total liquid volume in the mud pit, etc. data, for different working conditions (such as various non-drilling working conditions and normal drilling working conditions like pump start / stop, tripping in and out, making connections, etc.), process and analyze each parameter information, and through big data learning, establish an overflow monitoring model corresponding to each working condition based on an artificial neural network.

[0178] Step 24, multi-source data acquisition, processing, and processing by the intelligent spill monitoring module.

[0179] Specifically, this step is to perform overflow monitoring on the obtained surface monitoring information and downhole monitoring information in real time through an intelligent spill monitoring module (in this embodiment, the intelligent spill monitoring module is the overflow monitoring model). When the overflow monitoring model detects an overflow situation, the spill volume is calculated.

[0180] Step 25: Judge the bottomhole spill standard and give an alarm.

[0181] Specifically, this step is to detect whether the spill volume is within a preset spill range; when the spill volume is within the preset spill range, control the activation of the alarm mode corresponding to the spill volume.

[0182] In this embodiment, the preset overflow range can be determined according to construction requirements and geological characteristics. Control the alarm unit to activate the alarm mode corresponding to the spill volume. Among them, the alarm unit can be an alarm device such as an alarm. The controller controls the alarm to use different ringing methods for alarm according to different spill volumes. For example, if there are three alarm gradients set for the preset spill range, when the spill volume is within the first preset spill range, the controller controls the alarm unit to activate the first alarm mode, such as controlling the alarm to use an intermittent uniform whistling alarm mode; when the spill volume is within the second preset spill range, the controller controls the alarm unit to activate the second alarm mode, such as controlling the alarm to use a one-long-one-short whistling alarm mode; when the spill volume is within the third preset spill range, the controller controls the alarm unit to activate the third alarm mode, such as controlling the alarm to use a long whistling alarm mode.

[0183] Step 26: Automatically circulate and drain the overflow, automatically throttle, and automatically kill the well.

[0184] Specifically, this step is to control the spill treatment equipment to work when the spill volume is within the preset spill range. Among them, according to the spill volume, control the spill treatment equipment to perform at least one of throttling, draining the overflow, backpressure control, and well killing; and input the spill volume into the wellbore hydraulics model to obtain drilling fluid density ratio guidance information; according to the drilling fluid density ratio guidance information, control the spill treatment equipment to adjust the drilling fluid density.

[0185] Step 27: Eliminate the blowout risk, continuously identify the working conditions, and perform real-time monitoring and real-time processing.

[0186] After controlling the start of the above-mentioned spill treatment, eliminate the blowout risk; at this time, the working condition identification model performs continuous working condition identification, and through the overflow monitoring model corresponding to the working condition identification result, perform real-time overflow monitoring on the surface monitoring information and downhole monitoring information, and when an overflow situation is detected, process the overflow situation in real time.

[0187] In this embodiment, based on multi-source parameter information such as wellbore data, ground equipment working status, changes in the liquid level of the mud pit monitored on the ground, and annular flow in the wellbore, the current working condition is identified through a working condition identification model. At the same time, an overflow and leakage monitoring model corresponding to the current working condition is used for overflow and leakage monitoring; continuously monitor parameters such as temperature, pressure, viscosity, resistivity, annular flow velocity, dielectric constant, fluid components in the wellbore annulus, and liquid volume and pressure difference of the ground mud pit, and transmit them to the overflow and leakage monitoring model under the current working condition for analysis in real time to monitor the overflow and leakage conditions at the bottom of the well; calculate the overflow and leakage volume when an overflow and leakage occurs, determine the degree of overflow and leakage according to the overflow and leakage volume, select different alarm modes according to the degree of overflow and leakage, and at the same time control the operation of the overflow and leakage treatment equipment, guide the density ratio of the ground drilling fluid, and eliminate the overflow and leakage situation by calling the drilling pump, backpressure pump, and automatic choke manifold to discharge overflow, kill the well, or balance the bottom hole pressure through the annulus. If no overflow and leakage situation is detected, continuously monitor the parameter information under this working condition.

[0188] Among them, the pre-drilling preparation work of this overflow and leakage monitoring and treatment method is specifically as follows:

[0189] Before running the casing, connect a monitoring nipple at the bottom of the casing or a specified position, fix the fiber optic cable on the outer wall of the casing. Here, an embedded type is selected, and an open structure consistent with the outer shape of the fiber optic cable is cut out on the casing wall. While running the casing on the ground, embed the fiber optic cable. After the casing is run to the bottom of the well, check the working status and signal integrity of the device. After ensuring that the device can work normally, inject cement and wait for it to set. After cementing is completed. For a new drilling section, the ground and downhole monitoring devices monitor in real time and the ground data is processed in real time. Judge the current working condition according to the opening state of the ground pump, the hook load of the crown block, wellbore data, and inlet and outlet flow rates.

[0190] Here, the normal drilling state is taken as an example for illustration. After the working condition identification model automatically identifies the working condition as the normal drilling working condition, it switches to the normal drilling intelligent overflow and leakage monitoring module (i.e., the overflow and leakage monitoring model corresponding to the normal drilling working condition) for overflow and leakage monitoring. Comprehensively judge the overflow and leakage situation in the well according to the annular flow velocity, annular fluid components, drilling fluid temperature, pressure, viscosity, dielectric constant measured downhole, and the liquid volume of the ground mud pit. Judge the degree of overflow and leakage according to the change amount of the liquid volume of the ground mud pit. According to different degrees of overflow and leakage, independently select methods such as throttling, backpressure supplement, circulating overflow discharge, and well killing to balance the bottom hole pressure until the overflow and leakage are eliminated, and continuously monitor the downhole and ground data.

[0191] This embodiment can take into account the human operation factors under various drilling working conditions, eliminate false overflow and leakage situations caused by humans or working condition changes, establish a working condition identification model that can sense multi-source parameter information through the change characteristics of different sensitive parameters under various working conditions, can identify the change of the working condition in real time, and can switch to the overflow and leakage monitoring model corresponding to this working condition.

[0192] Among them, the acquisition of ground monitoring information and downhole monitoring information, that is, the acquisition of multi-source parameter information, is carried out by installing monitoring devices at designated positions of the casing to measure characteristic parameters such as temperature, pressure, density, fluid components, dielectric constant, and annular flow velocity in the annulus, and installing differential pressure sensors in the surface mud pit to monitor the pressure fluctuations in the mud pit caused by density and temperature changes in real time. Combining downhole and ground monitoring data and sensitive parameters under various working conditions, based on neural networks, training and learning are carried out on historical data of adjacent wells or similar working conditions, and an overflow monitoring model is established, which can accurately monitor the real overflow situation under any working condition and reduce the false alarm rate. At the same time, the real-time monitoring in the wellbore reduces the delay of surface overflow display, overcomes the lack of timeliness of surface overflow monitoring, extends the time for overflow disposal, and reduces the well control risk. According to different overflow degrees, the overflow treatment equipment is controlled to work, that is, an automatic throttling, automatic kill, and automatic overflow discharge model and control method are established, realizing targeted treatment methods for different overflow degrees and reducing the well control risk.

[0193] It should be understood that although Figure 3 the steps in the flowchart of Figure 3 are shown in sequence according to the indication of the arrows, these steps are not necessarily executed in the order indicated by the arrows. Unless otherwise clearly stated in this article, there is no strict order restriction for the execution of these steps, and these steps can be executed in other orders. Moreover,

[0194] Embodiment 4

[0195] In this embodiment, as Figure 5 shown, an overflow monitoring and processing device is provided, including:

[0196] A receiving module 210, configured to receive ground monitoring information and downhole monitoring information;

[0197] A working condition identification module 220, configured to perform working condition identification on the ground monitoring information and the downhole monitoring information through a working condition identification model to obtain a working condition identification result;

[0198] An overflow monitoring module 230, configured to perform overflow monitoring on the ground monitoring information and the downhole monitoring information through an overflow monitoring model corresponding to the working condition identification result;

[0199] A calculation module 240, configured to calculate the overflow amount in response to detecting an overflow situation;

[0200] A control module 250, configured to start corresponding spill handling operations in response to the spill amount being within a preset spill range.

[0201] In one embodiment, the spill monitoring and handling device further includes:

[0202] A working condition identification model construction module, configured to obtain sample surface monitoring information, sample downhole monitoring information, sample wellbore data information, sample surface equipment working state information, and working condition information similar to adjacent wells or the same layer of the well in the same work area; analyze the sample surface monitoring information, sample downhole monitoring information, sample wellbore data information, sample surface equipment working state information, and working condition information similar to adjacent wells or the same layer of the well in the same work area through a first neural network to establish variation characteristics of each parameter information of multiple working conditions; determine sensitive parameters of each of the working conditions according to the variation characteristics of each parameter information of the multiple working conditions; and construct a working condition identification model based on the sensitive parameters of each of the working conditions.

[0203] In one embodiment, the spill monitoring and handling device further includes:

[0204] An overflow monitoring model construction module, configured to obtain multiple sample working conditions, sample surface monitoring information, and sample downhole monitoring information; analyze the sample working conditions, sample surface monitoring information, and sample downhole monitoring to determine overflow characterization parameters corresponding to each of the sample working conditions through a second neural network; and construct an overflow monitoring model corresponding to each of the sample working conditions based on the overflow characterization parameters corresponding to each of the sample working conditions.

[0205] In one embodiment, the control module further includes:

[0206] An alarm module, configured to turn on an alarm mode corresponding to the spill amount in response to the spill amount being within a preset spill range.

[0207] In one embodiment, the control module further includes:

[0208] A spill handling module, configured to perform at least one of throttle control, overflow discharge, backpressure control, and well killing in response to the spill amount being within a preset spill range.

[0209] In one embodiment, the control module further includes:

[0210] A spill handling module, configured to calculate the spill amount through a wellbore hydraulics model in response to the spill amount being within a preset spill range to obtain drilling fluid density ratio guidance information; and adjust the drilling fluid density according to the drilling fluid density ratio guidance information.

[0211] Specifically, the spill handling module includes a surface drilling pump, a backpressure pump, an automatic choke valve, etc. When monitoring complex conditions such as wellbore leakage at the bottom of the well, the wellbore pressure can be throttled and controlled or throttled and flowed back through the automatic choke valve to avoid blowout; when the overflow condition is not suppressed after simple throttling, the drilling pump can be used for circulating drainage or adjusting the density of the drilling fluid; when the circulating drainage or adjusting the density of the drilling fluid fails to completely handle the overflow, the backpressure pump can be used to supplement the drilling fluid through the annulus to balance the bottom hole pressure; when the degree of overflow is large, the backpressure pump is used to assist the driller in conducting the engineer method of well killing. The automatic throttling, backpressure supplement, circulating drainage and automatic well killing in the spill handling module can be dynamically adjusted at any time, or used in combination or alone, and can be adjusted according to the on-site conditions.

[0212] In this embodiment, when the degree of overflow is relatively light, the overflow is controlled by controlling the automatic choke valve or the surface backpressure pump of the spill handling module; at the same time, a dynamic coupling relationship between the automatic choke valve, the backpressure pump and the wellbore pressure is established, and the wellbore pressure is autonomously learned and regulated. Based on the hydraulic model, the spillage volume is calculated to obtain the guidance information for the drilling fluid density ratio. According to the guidance information of the drilling fluid density ratio, the spill handling unit is controlled to conduct circulating drainage and adjust the density ratio of the well killing drilling fluid. So that when overflow is detected, the ground sequential drilling fluid density, backpressure supplement, automatic choke valve opening, etc. can be autonomously and dynamically regulated for spill handling.

[0213] For the specific limitations of the spill monitoring and handling device, reference can be made to the limitations of the spill monitoring and handling method in the above text, which will not be elaborated here. Each unit in the above spill monitoring and handling device can be implemented in whole or in part through software, hardware and their combination. The above units can be embedded in the processor of the computer device in hardware form or independent of it, or stored in the memory of the computer device in software form, so that the processor can call and execute the operations corresponding to the above units.

[0214] Embodiment Five

[0215] In this embodiment, a computer device is provided. Its internal structure diagram can be as Figure 6As shown in the figure. The computer device includes a processor, a memory, a network interface, a display screen, and an input device connected through a system bus. Among them, the processor of the computer device is used to provide computing and control capabilities. The memory of the computer device includes a non-volatile storage medium and an internal memory. The non-volatile storage medium stores an operating system and computer programs. The internal memory provides an environment for the operation of the operating system and computer programs in the non-volatile storage medium. The network interface of the computer device is used to communicate with other computer devices that have deployed application software. When the computer program is executed by the processor, it realizes a method for monitoring and processing spills based on the ground and underground. The display screen of the computer device can be a liquid crystal display screen or an electronic ink display screen. The input device of the computer device can be a touch layer covered on the display screen, or a button, trackball, or touchpad set on the shell of the computer device, or an external keyboard, touchpad, or mouse, etc.

[0216] Those skilled in the art can understand that Figure 6 The structure shown in the figure is only a block diagram of some structures related to the solution of the present application, and does not constitute a limitation on the computer device to which the solution of the present application is applied. The specific computer device may include more or fewer components than those shown in the figure, or combine some components, or have different component arrangements.

[0217] In one embodiment, a computer device is provided, including a memory and a processor. The memory stores a computer program. When the processor executes the computer program, the following steps are realized:

[0218] Receive ground monitoring information and underground monitoring information;

[0219] Perform working condition identification on the ground monitoring information and the underground monitoring information through a working condition identification model to obtain a working condition identification result;

[0220] Perform overflow monitoring on the ground monitoring information and the underground monitoring information through an overflow monitoring model corresponding to the working condition identification result;

[0221] In response to detecting an overflow situation, calculate the spill volume;

[0222] In response to the spill volume being within a preset spill range, initiate corresponding spill treatment operations.

[0223] In one embodiment, when the processor executes the computer program, the following steps are also realized:

[0224] The ground monitoring information includes the liquid level change information and differential pressure information of the mud pit. The underground monitoring information includes the temperature information, pressure information, viscosity change information, resistivity information in the wellbore annulus, flow rate information, and fluid component information underground.

[0225] In one embodiment, when the processor executes the computer program, the following steps are further implemented:

[0226] Obtain sample surface monitoring information, sample downhole monitoring information, sample wellbore data information, sample surface equipment working status information, and working condition information similar to adjacent wells or the same formation of the well in the same work area;

[0227] Parse the sample surface monitoring information, sample downhole monitoring information, sample wellbore data information, sample surface equipment working status information, and working condition information similar to adjacent wells or the same formation of the well in the same work area through a first neural network, and establish the change characteristics of the parameter information of multiple working conditions;

[0228] Determine the sensitive parameters of each of the multiple working conditions according to the change characteristics of the parameter information of each of the multiple working conditions;

[0229] Construct a working condition recognition model based on the sensitive parameters of each of the working conditions.

[0230] In one embodiment, when the processor executes the computer program, the following steps are further implemented:

[0231] Obtain multiple sample working conditions, sample surface monitoring information, and sample downhole monitoring information;

[0232] Parse the sample working conditions, sample surface monitoring information, and sample downhole monitoring to determine the overflow characterization parameters corresponding to each of the sample working conditions through a second neural network;

[0233] Construct an overflow monitoring model corresponding to each of the sample working conditions based on the overflow characterization parameters corresponding to each of the sample working conditions.

[0234] In one embodiment, when the processor executes the computer program, the following steps are further implemented:

[0235] In response to the amount of leakage being within a preset leakage range, control the leakage treatment unit to perform at least one of throttling, overflow drainage, backpressure control, and well killing.

[0236] In one embodiment, when the processor executes the computer program, the following steps are further implemented:

[0237] In response to the amount of leakage being within a preset leakage range, calculate the amount of leakage through a wellbore hydraulics model to obtain drilling fluid density ratio guidance information;

[0238] Control the leakage treatment unit to adjust the drilling fluid density according to the drilling fluid density ratio guidance information.

[0239] In one embodiment, when the processor executes the computer program, the following steps are further implemented:

[0240] In response to the spillage amount being within a preset spillage range, control the alarm unit to activate an alarm mode corresponding to the spillage amount.

[0241] Embodiment Six

[0242] In this embodiment, a computer-readable storage medium is provided, on which a computer program is stored. When the computer program is executed by a processor, the following steps are implemented:

[0243] Receive surface monitoring information and downhole monitoring information;

[0244] Perform working condition identification on the surface monitoring information and the downhole monitoring information through a working condition identification model to obtain a working condition identification result;

[0245] Perform overflow monitoring on the surface monitoring information and the downhole monitoring information through an overflow monitoring model corresponding to the working condition identification result;

[0246] In response to detecting an overflow situation, calculate the spillage amount;

[0247] In response to the spillage amount being within a preset spillage range, initiate corresponding spillage treatment operations.

[0248] In one embodiment, when the computer program is executed by a processor, the following steps are further implemented:

[0249] The surface monitoring information includes liquid level change information and differential pressure information of the mud pit, and the downhole monitoring information includes downhole temperature information, pressure information, viscosity change information, resistivity information in the wellbore annulus, flow rate information, and fluid component information.

[0250] In one embodiment, when the computer program is executed by a processor, the following steps are further implemented:

[0251] Obtain sample surface monitoring information, sample downhole monitoring information, sample wellbore data information, sample surface equipment working state information, and working condition information similar to adjacent wells or the same layer of the well in the same work area;

[0252] Analyze the sample surface monitoring information, sample downhole monitoring information, sample wellbore data information, sample surface equipment working state information, and working condition information similar to adjacent wells or the same layer of the well in the same work area through a first neural network to establish change characteristics of each parameter information of multiple working conditions;

[0253] Determine sensitive parameters of each of the multiple working conditions according to the change characteristics of each parameter information of the multiple working conditions;

[0254] Construct a working condition identification model based on the sensitive parameters of each of the working conditions.

[0255] In one embodiment, when the computer program is executed by a processor, the following steps are further implemented:

[0256] Obtain a plurality of sample working conditions, sample surface monitoring information, and sample downhole monitoring information;

[0257] Parse the sample working conditions, sample surface monitoring information, and sample downhole monitoring through a second neural network to determine the overflow characterization parameters corresponding to each of the sample working conditions;

[0258] Based on the overflow characterization parameters corresponding to each of the sample working conditions, construct an overflow monitoring model corresponding to each of the sample working conditions.

[0259] In one embodiment, when the computer program is executed by a processor, the following steps are further implemented:

[0260] In response to the leakage amount being within a preset leakage range, control the leakage treatment unit to perform at least one of throttling, overflow discharging, back pressure control, and well killing.

[0261] In one embodiment, when the computer program is executed by a processor, the following steps are further implemented:

[0262] In response to the leakage amount being within a preset leakage range, calculate the leakage amount through a wellbore hydraulics model to obtain drilling fluid density ratio guidance information;

[0263] According to the drilling fluid density ratio guidance information, control the leakage treatment unit to adjust the drilling fluid density.

[0264] In one embodiment, when the computer program is executed by a processor, the following steps are further implemented:

[0265] In response to the leakage amount being within a preset leakage range, control the alarm unit to turn on an alarm mode corresponding to the leakage amount.

[0266] Those of ordinary skill in the art can understand that all or part of the processes in the methods of the above embodiments can be completed by instructing relevant hardware through a computer program. The computer program can be stored in a non-volatile computer-readable storage medium. When the computer program is executed, it can include the processes of the embodiments of the above methods. Among them, any reference to a memory, storage, database, or other medium used in the various embodiments provided in the present application can include non-volatile and / or volatile memories. Non-volatile memories can include read-only memory (ROM), programmable ROM (PROM), electrically programmable ROM (EPROM), electrically erasable programmable ROM (EEPROM), or flash memory. Volatile memories can include random access memory (RAM) or external cache memory. By way of illustration and not limitation, RAM is available in many forms, such as static RAM (SRAM), dynamic RAM (DRAM), synchronous DRAM (SDRAM), double data rate SDRAM (DDR SDRAM), enhanced SDRAM (ESDRAM), synchronous link DRAM (SLDRAM), Rambus direct RAM (RDRAM), direct memory bus dynamic RAM (DRDRAM), and Rambus dynamic RAM (RDRAM), etc.

[0267] The technical features of the above embodiments can be combined arbitrarily. For the sake of brevity of description, not all possible combinations of the technical features in the above embodiments are described. However, as long as there is no contradiction in the combination of these technical features, it should be considered as the scope recorded in this specification.

[0268] The above-described embodiments merely represent several implementation manners of the present application. The description thereof is relatively specific and detailed, but it should not be construed as a limitation on the scope of the invention patent. It should be noted that for those of ordinary skill in the art, without departing from the concept of the present application, several modifications and improvements can still be made, and these all belong to the protection scope of the present application. Therefore, the protection scope of the patent of the present application should be subject to the appended claims.

Claims

1. A controller for spill monitoring and treatment, connected to a ground monitoring unit and a downhole monitoring unit, characterized in that, the controller is configured to receive ground monitoring information from the ground monitoring unit and downhole monitoring information from the downhole monitoring unit; perform condition identification on the ground monitoring information and the downhole monitoring information through a condition identification model to obtain a condition identification result; perform overflow monitoring on the ground monitoring information and the downhole monitoring information through an overflow monitoring model corresponding to the condition identification result; in response to detecting an overflow situation, the controller calculates the spill volume, and in response to the spill volume being within a preset spill range, the controller initiates corresponding spill treatment operations.

2. The controller according to claim 1, wherein The controller is also connected to a spill treatment unit; The controller initiating corresponding spill treatment operations includes the controller controlling the spill treatment unit to perform at least one of throttling, overflow discharging, backpressure control, and well killing.

3. The controller according to claim 1 or 2, characterized in that, The controller is also connected to an alarm unit; The controller initiating corresponding spill treatment operations includes the controller controlling the alarm unit to turn on an alarm mode corresponding to the spill volume.

4. A spill monitoring and handling system, characterized in that, It includes a ground monitoring unit, a downhole monitoring unit, and the controller according to any one of claims 1 to 3, wherein the ground monitoring unit is used to collect ground monitoring information and transmit the ground monitoring information to the controller; the downhole monitoring unit is used to collect downhole monitoring information and transmit the downhole monitoring information to the controller.

5. The spill monitoring and processing system according to claim 4, wherein, The system further includes an optical fiber cable data transmission unit, and the ground monitoring unit and the downhole monitoring unit are respectively connected to the controller through the optical fiber cable data transmission unit; the ground monitoring unit is used to transmit the ground monitoring information to the controller through the optical fiber cable data transmission unit, and the downhole monitoring unit is used to transmit the downhole monitoring information to the controller through the optical fiber cable data transmission unit; The optical fiber cable data transmission unit includes an optical fiber cable that is buried or embedded.

6. The spill monitoring and processing system according to claim 4, characterized in that, The ground monitoring information includes differential pressure information of the mud pit; the ground monitoring unit includes a differential pressure sensor, and the differential pressure sensor is installed in the mud pit and is used to monitor the pressure change in the mud pit to obtain the differential pressure information of the mud pit.

7. The spill monitoring and processing system according to claim 4, wherein The ground monitoring information includes liquid level change information of the mud pit; the ground monitoring unit includes a high-frequency radar level gauge, and the high-frequency radar level gauge is located at the wellhead of the drilling and is used to perform multi-point real-time monitoring on the liquid level height in the mud to obtain the liquid level change information of the mud pit.

8. The spill monitoring and processing system according to claim 4, characterized in that The downhole monitoring information includes resistivity information, flow velocity information, and fluid component information in the wellbore annulus; the downhole monitoring unit includes an ultrasonic transceiver, the ultrasonic transceiver is connected to the controller, the ultrasonic transceiver is installed on the casing of the wellbore, and the ultrasonic transceiver is used to monitor the ultrasonic frequency shift and resistivity in the wellbore annulus and collect the resistivity information, flow velocity information, and fluid component information in the wellbore annulus.

9. The spill monitoring and processing system according to claim 4, wherein The downhole monitoring information includes temperature information, pressure information, and viscosity change information downhole; the downhole monitoring unit includes a temperature sensor, a pressure sensor, and a capacitor. The temperature sensor, the pressure sensor, and the capacitor are respectively connected to the controller, and the temperature sensor, the pressure sensor, and the capacitor are installed on the casing of the wellbore. The temperature sensor is used to collect temperature information, the pressure sensor is used to collect pressure information, and the capacitor is used to collect viscosity change information.

10. A method for monitoring and handling spills, characterized in that, including: receiving surface monitoring information and downhole monitoring information; performing a working condition identification on the surface monitoring information and the downhole monitoring information through a working condition identification model to obtain a working condition identification result; performing an overflow monitoring on the surface monitoring information and the downhole monitoring information through an overflow monitoring model corresponding to the working condition identification result; in response to detecting an overflow situation, calculating the leakage amount; in response to the leakage amount being within a preset leakage range, initiating a corresponding leakage handling operation.

11. The spill monitoring and processing method according to claim 10, wherein The surface monitoring information includes at least one of liquid level change information and differential pressure information of the mud pit, and the downhole monitoring information includes at least one of temperature information, pressure information, viscosity change information, resistivity information in the wellbore annulus, flow rate information, and fluid component information downhole.

12. The spill monitoring and processing method according to claim 10, wherein The method further includes: providing sample surface monitoring information, sample downhole monitoring information, sample wellbore data information, sample surface equipment working state information, and similar working condition information of adjacent wells or the same layer of this well in the same work area; analyzing the sample surface monitoring information, sample downhole monitoring information, sample wellbore data information, sample surface equipment working state information, and similar working condition information of adjacent wells or the same layer of this well in the same work area through a first neural network to establish the change characteristics of each parameter information of multiple working conditions; determining the sensitive parameters of each of the working conditions according to the change characteristics of each parameter information of the multiple working conditions; constructing the working condition identification model based on the sensitive parameters of each of the working conditions.

13. The spill monitoring and processing method according to claim 10, wherein The method further includes: providing multiple sample working conditions, sample surface monitoring information, and sample downhole monitoring information; analyzing the sample working conditions, sample surface monitoring information, and sample downhole monitoring information through a second neural network to determine the overflow characterization parameters corresponding to each of the sample working conditions; constructing the overflow monitoring model corresponding to each of the sample working conditions based on the overflow characterization parameters corresponding to each of the sample working conditions.

14. The spill monitoring and handling method according to claim 10, wherein The step of in response to the leakage amount being within a preset leakage range, controlling the leakage handling unit to perform at least one of throttling, overflow discharging, backpressure control, and well killing. The step of in response to the leakage amount being within a preset leakage range, calculating the leakage amount through a wellbore hydraulics model to obtain drilling fluid density ratio guidance information; 15. The spill monitoring and processing method according to claim 10, characterized in that, controlling the leakage handling unit to adjust the drilling fluid density according to the drilling fluid density ratio guidance information. The step of in response to the leakage amount being within a preset leakage range, initiating a corresponding leakage handling operation includes: ​ 16. The spill monitoring and processing method according to claim 10, characterized in that ​ In response to the spillage amount being within a preset spillage range, control the alarm unit to activate an alarm mode corresponding to the spillage amount.

17. A spill monitoring and processing device, characterized in that, Comprising: a receiving module, configured to receive surface monitoring information and downhole monitoring information; a working condition identification module, configured to perform working condition identification on the surface monitoring information and the downhole monitoring information through a working condition identification model to obtain a working condition identification result; a blowout monitoring module, configured to perform blowout monitoring on the surface monitoring information and the downhole monitoring information through a blowout monitoring model corresponding to the working condition identification result; a calculation module, configured to calculate the spillage amount in response to detecting a blowout situation; a control module, configured to initiate corresponding spillage treatment operations in response to the spillage amount being within a preset spillage range.

18. A computer device, comprising a memory and a processor, the memory storing a computer program, characterized in that, When the processor executes the computer program, the steps of the method according to any one of claims 10 to 16 are implemented.

19. A computer-readable storage medium having a computer program stored thereon, characterized in that, When the computer program is executed by a processor, the steps of the method according to any one of claims 10 to 16 are implemented.

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