Advanced detection method of oil and gas well drill bit for unfavorable geology

Abstract

The invention relates to the technical field of oil-gas well exploration, in particular to an oil-gas well drill bit advanced detection method for unfavorable geology. According to the technical scheme, the method comprises the following steps of S1, installing a probe device, S2, exciting a detection signal while drilling, S3, receiving a reflection and scattering signal, S4, preprocessing an underground signal and extracting features, S5, compressing data and uploading the data in real time, S6, processing and imaging ground data, S7, interpreting geology and identifying risks, and S8, generating early warning and decision support. The advanced detection device has the beneficial effects that the advanced detection device is directly integrated on the drill bit, the drill bit is used as a part of a detection source or a sensor, drilling and detection are carried out at the same time, and early warning is sent to the drill bit before the drill bit encounters an unfavorable geologic body; therefore, precious time is won for adjusting drilling parameters, optimizing a well body track or starting a safety program, and the safety, efficiency and economic benefits of drilling are fundamentally improved.

Description

Technical Field

[0001] This invention relates to the field of oil and gas well exploration technology, and in particular to a method for advanced detection of oil and gas well drill bits in adverse geological conditions. Background Technology

[0002] In oil and gas drilling operations, drill bits often encounter unfavorable geological formations such as faults, fractures, high-pressure aquifers, caves, and salt deposits. These formations can easily lead to serious downhole complications and accidents, such as well kicks, lost circulation, stuck drill bits, and even blowouts, causing not only huge economic losses, such as non-producing time (NPT), but also significant safety and environmental risks.

[0003] Currently, the industry's understanding of the geological environment ahead of the drill bit mainly relies on the following types of technologies, but all of them have significant limitations: 1. Relying on seismic exploration data, the geological structure map obtained by surface seismic or 3D seismic before drilling has the limitation of low resolution and strong ambiguity. Seismic data can only provide macroscopic stratigraphic structure information and cannot accurately predict adverse geological bodies, such as small faults and fractures. Its prediction accuracy cannot meet the real-time decision-making needs of safe drilling. 2. Logging while drilling (LOD) technology involves real-time measurement of formation parameters around the drill bit and in the drilled section, such as resistivity, gamma, and acoustic waves. Its limitation is that it is essentially a "lagging" and "side-by-side" technology. It can only measure the wellbore environment behind the drill bit and cannot provide early warning for the un-drilled formation in front of the drill bit. When an anomaly is detected, the drill bit has often already entered the danger zone, and it is too late. 3. Pre-drilling early warning technology: Some people have tried to apply the principles of ground earthquake or tunnel earthquake prediction technology to drilling. However, its limitations are weak signal and strong noise: the drilling site environment is very noisy and the source energy is insufficient, resulting in an extremely low signal-to-noise ratio. Summary of the Invention

[0004] The purpose of this invention is to address the aforementioned deficiencies in existing technologies by providing a method for advanced detection of oil and gas well drill bits in adverse geological conditions. This method directly emits high-frequency sound waves through drill bit vibration and combines this with real-time data processing to provide early warnings of adverse geological conditions ahead of the drill bit.

[0005] The present invention discloses a method for advance detection of oil and gas well drill bits in adverse geological conditions, the technical solution of which includes the following steps: S1. Install the probe device and embed the excitation device into the drill bit, so that the excitation device remains intact while being integrated into one piece. S2. Drilling-while-drilling detection signal: Using the excitation device integrated in the drill bit, specific detection signals are emitted to the un-drilled formations in front of and around the drill bit at a preset cycle. S3. Receive reflected and scattered signals. Through a sensor array installed behind the drill bit, it receives and collects detection signals reflected and scattered from different geological interfaces in front in real time. S4. Downhole signal preprocessing and feature extraction: Using the signal processing module embedded in the downhole tool, the received raw detection signal is preprocessed in real time, and the effective signal is amplified and digitized. The weak effective signal is amplified and converted into a digital signal, and preliminary analysis is performed to extract the feature parameters of the signal. S5. Data compression and real-time upload: The processing unit will compress and package the data, and then transmit the key data to the ground in real time through the transmission system. S6. Ground data processing and imaging: After receiving the data from downhole, the ground computer system performs real-time preprocessing to generate a formation profile image at a certain distance in front of the drill bit. S7. Geological interpretation and risk identification: Combine regional geological data and real-time imaging results to interpret the images and identify the type, location and distance of adverse geological bodies; S8. Generate early warnings and provide decision support: Based on the interpretation results, the system generates tiered early warning information and displays the visualization results and early warning prompts on the drilling monitoring platform to provide decision support for engineers.

[0006] Preferably, the above-mentioned excitation device is installed inside the drill bit body and emits detection signals to the formation directly in front of and to the side of the drill bit; the excitation device adopts a sound wave generator and a wideband piezoelectric ceramic transducer array, which is embedded in the lower outer wall of the short section in a ring, with a total of 8 transducer units arranged evenly.

[0007] Preferably, the aforementioned acoustic wave generator adopts a monopole mode, in which all broadband piezoelectric ceramic transducers are excited synchronously to generate longitudinal waves; or a dipole mode, in which broadband piezoelectric ceramic transducers of symmetrical units are excited in opposite phases to generate transverse waves, in order to detect different lithologies and fluids.

[0008] Preferably, the aforementioned sensor array uses an acoustic receiver, which is a three-component accelerometer sensor array with four groups of sensors arranged in a ring, each group containing three mutually orthogonal X / Y / Z accelerometers.

[0009] Preferably, the downhole signal preprocessing and feature extraction described above includes a control and preprocessing circuit compartment and a signal preprocessing module. The control and preprocessing circuit compartment uses a field-programmable gate array (FPGA) chip for precise control of transmission timing and synchronous acquisition. The signal preprocessing module includes a preamplifier, an anti-aliasing filter, and an analog-to-digital converter.

[0010] Preferably, the real-time preprocessing in step S6 includes noise reduction filtering to filter out strong noise interference generated by drill bit rock breaking, drill string vibration, and mud pump.

[0011] Preferably, the signal extraction in the module involves converting the current signal into a voltage signal at the acquisition end, followed by subsequent processing. This is achieved using a switched capacitor circuit, the core of which is a differential capacitor detection scheme. The workflow is as follows: 1) The sensor module outputs two capacitance values, C1 and C2, that change with acceleration; 2) Analog front-end - Capacitor-to-voltage conversion, operating through precise timing control: Phase 1, also known as the charging phase: The switch connects one end of C1 and C2 to the reference voltage Vref and the other end to the input of the operational amplifier; Phase 2, also known as the transfer phase: the switch is switched to transfer the charge of the capacitor to the feedback capacitor Cf of the operational amplifier; Since C1 and C2 have different charges, the net charge transferred to the feedback capacitor is proportional to the charge difference. The operational amplifier converts this charge difference into a voltage signal Vout. The formula is: Vout ∝ (C1 - C2) × Vref / Cf The output voltage signal Vout reflects the magnitude and direction of the acceleration. If C1 > C2, the output voltage is positive; if C1 < C2, the output voltage is negative. 3) Analog-to-digital conversion: An analog-to-digital converter converts analog voltage values ​​into digital values; 4) Digital signal processing and output: The digitized signal undergoes further calibration, filtering, and temperature compensation processing, and is then output to the main processor through a standard digital interface.

[0012] Compared with the prior art, the beneficial effects of the present invention are as follows: The advanced detection system can be directly integrated into the drill bit, using the drill bit itself as a detection source or sensor to achieve "drilling while detecting". It can issue early warnings to unfavorable geological bodies before the drill bit encounters them, thereby gaining valuable time to adjust drilling parameters, optimize well trajectory, or initiate safety procedures, fundamentally improving the safety, efficiency, and economic benefits of drilling. Attached Figure Description

[0013] Figure 1 This is a schematic diagram of the drill bit portion of the present invention; Figure 2 This is a schematic diagram of the overall installation; Figure 3 This is a schematic diagram of the detector's structure; In the diagram above: 1. Excitation device; 2. Drill bit; 3. Drill string; 4. Derrick; 5. Detector; 5. Detector sleeve; 5.1. Battery; 5.2. Detector acquisition card; 5.3. Sensor signal line; 5.4. Detailed Implementation

[0014] The preferred embodiments of the present invention will be described below with reference to the accompanying drawings. It should be understood that the preferred embodiments described herein are for illustration and explanation only and are not intended to limit the present invention.

[0015] Example 1: A method for advance detection of oil and gas well drill bits in adverse geological conditions, as mentioned in this invention, includes the following steps: S1. Install the probe device and embed the excitation device 1 into the drill bit 2, so that the excitation device 1 remains intact while being integrated into one piece; S2. Drilling-while-drilling detection signal: Using the excitation device 1 integrated in the drill bit 2, specific detection signals are emitted to the un-drilled formations in front of and around the drill bit 2 at a preset cycle. S3. Receive reflected and scattered signals. Through the sensor array installed behind the drill bit 2, receive and collect detection signals reflected and scattered from different geological interfaces in front in real time. S4. Downhole signal preprocessing and feature extraction: Using the signal processing module embedded in the downhole tool, the received raw detection signal is preprocessed in real time, and the effective signal is amplified and digitized. The weak effective signal is amplified and converted into a digital signal, and preliminary analysis is performed to extract the feature parameters of the signal. S5. Data compression and real-time upload: The processing unit will compress and package the data, and then transmit the key data to the ground in real time through the transmission system. S6. Ground data processing and imaging: After receiving the data from downhole, the ground computer system performs real-time preprocessing to generate a formation profile image at a certain distance in front of drill bit 2. S7. Geological interpretation and risk identification: Combine regional geological data and real-time imaging results to interpret the images and identify the type, location and distance of adverse geological bodies; S8. Generate early warnings and provide decision support: Based on the interpretation results, the system generates tiered early warning information and displays the visualization results and early warning prompts on the drilling monitoring platform to provide decision support for engineers.

[0016] The aforementioned excitation device 1 is installed inside the drill bit 2 body, emitting detection signals to the front and sides of the drill bit 2 towards the formation. The excitation device 1 is an acoustic wave generator, employing a wideband piezoelectric ceramic transducer array, which is annularly embedded in the lower outer wall of the short section, with a total of 8 transducer units evenly distributed. In addition, the rear end of the excitation device 1 is connected to the detector acquisition card 5.3 via a sensor signal line 5.4. A battery 5.2 is installed on one side of the detector acquisition card 5.3. The aforementioned detector acquisition card 5.3, battery 5.2, and sensor signal line 5.4 are installed in the detector sleeve 5.1.

[0017] The aforementioned acoustic wave generator employs a monopole mode, where all broadband piezoelectric ceramic transducers are synchronously excited to generate longitudinal waves; or a dipole mode, where broadband piezoelectric ceramic transducers of symmetrical units are excited in opposite phases to generate transverse waves, in order to detect different lithologies and fluids.

[0018] The aforementioned sensor array uses an acoustic receiver and is a three-component accelerometer sensor array. Four groups of sensors are arranged in a ring, each group containing three mutually orthogonal X / Y / Z accelerometers.

[0019] The aforementioned downhole signal preprocessing and feature extraction includes a control and preprocessing circuit compartment and a signal preprocessing module. The control and preprocessing circuit compartment uses a field-programmable gate array (FPGA) chip for precise control of transmission timing and synchronous acquisition. The signal preprocessing module includes a preamplifier, an anti-aliasing filter, and an analog-to-digital converter.

[0020] The real-time preprocessing in step S6 includes noise reduction filtering to remove strong noise interference from drill bit rock breaking, drill string vibration, and mud pump.

[0021] Preferably, the signal extraction in the module involves converting the current signal into a voltage signal at the acquisition end, followed by subsequent processing. This is achieved using a switched capacitor circuit, the core of which is a differential capacitor detection scheme. The workflow is as follows: 1) The sensor module outputs two capacitance values, C1 and C2, that change with acceleration; 2) Analog front-end - Capacitor-to-voltage conversion, operating through precise timing control: Phase 1, also known as the charging phase: The switch connects one end of C1 and C2 to the reference voltage Vref and the other end to the input of the operational amplifier; Phase 2, also known as the transfer phase: the switch is switched to transfer the charge of the capacitor to the feedback capacitor Cf of the operational amplifier; Since C1 and C2 have different charges, the net charge transferred to the feedback capacitor is proportional to the charge difference. The operational amplifier converts this charge difference into a voltage signal Vout. The formula is: Vout ∝ (C1 - C2) × Vref / Cf The output voltage signal Vout reflects the magnitude and direction of the acceleration. If C1 > C2, the output voltage is positive; if C1 < C2, the output voltage is negative. 3) Analog-to-digital conversion: An analog-to-digital converter converts analog voltage values ​​into digital values; 4) Digital signal processing and output: The digitized signal undergoes further calibration, filtering, and temperature compensation processing, and is then output to the main processor through a standard digital interface.

[0022] Example 2, a method for advance detection of oil and gas well drill bits in adverse geological conditions mentioned in this invention, includes the following steps: S1. System initialization and calibration: The drill string assembly is lowered to the bottom of the well and normal drilling begins. The surface system sends a command to start the near-bit sub. Self-calibration process: In a section of well with known lithology (such as a pure mudstone section), the excitation unit emits a standard test pulse, the receiving unit records the response, and a benchmark database of "background noise and known formation response" is established for subsequent data normalization processing. S2. Drilling Excitation and Reception: Automatically executes detection cycles during drilling intervals, such as when connecting a single joint or at an extremely low duty cycle; The FPGA-controlled transmitting circuit is activated to apply a high-voltage pulse to the piezoelectric ceramic transducer, generating an acoustic pulse pointing in front of drill bit 2. After activation, all accelerometers are activated synchronously to continuously record waveform data for 100ms at a sampling rate of 100kHz, recording the "quiet period" before the first arrival wave to capture the weak reflection signal from the foremost stratum. S3. Real-time downhole signal processing: This is crucial for ensuring data quality and reducing transmission burden. A field-programmable gate array (FPGA) chip executes an adaptive noise cancellation algorithm in parallel, using strong drill string vibration noise received from the upper sensor of the sub-section as a reference signal. The least mean square adaptive filtering algorithm is used to subtract noise components related to the reference signal from the lower sensor signal in real time, which greatly improves the signal-to-noise ratio; digital filtering is used to filter out noise outside the frequency band, such as 10-30kHz bandpass; data compression is performed by using a lossless compression algorithm to compress the filtered waveform data. S4. Data Upload: The compressed data packet is uploaded to the ground. S5. High-speed ground processing and imaging: After receiving the data, the ground server initiates the core imaging process: data unpacking and preprocessing, decoding, decompressing, and channel equalization of the data; establishing a velocity model: a preliminary formation velocity model is established by combining LWD logging data from the drilled section; the imaging stage adopts reverse time migration imaging, with the wave field propagating forward, simulating the process of the acoustic pulse propagating from the excitation point to the front of the formation in the computer; wave field reverse propagation: the actual received reflected wave signal is used as the source, and the wave field is simulated to propagate backward in time. During the output process, a depth-offset profile is generated in front of drill bit 2. Abnormal bright spots in the image are strong reflectors, such as formation interfaces, fractures, and caverns. S6. Geological Interpretation and Intelligent Early Warning: Artificial Intelligence-Assisted Interpretation: Imaging results are input into a pre-trained deep learning model, such as a convolutional neural network (CNN). This model is trained using a large amount of historical drilling data and corresponding seismic and well logging data. It can identify patterns such as "karst caves," "faults," and "high-pressure anomalies" in the images and output the identification results and confidence levels. Finally, a three-dimensional visualization is formed, which overlays the imaging results in three dimensions onto the real-time drilling trajectory and seismic profile, providing engineers with an extremely intuitive display.

[0023] The above description is merely a partial preferred embodiment of the present invention. Any person skilled in the art can modify the above-described technical solutions or modify them into equivalent technical solutions. Therefore, any simple modifications or equivalent transformations made based on the technical solutions of the present invention fall within the scope of protection claimed by the present invention.

Claims

1. A method for advance detection of oil and gas well drill bits in adverse geological conditions, characterized by: Includes the following steps: S1. Install the probe device and embed the excitation device into the drill bit, so that the excitation device remains intact while being integrated into one piece. S2. Drilling-while-drilling detection signal: Using the excitation device integrated in the drill bit, specific detection signals are emitted to the un-drilled formations in front of and around the drill bit at a preset cycle. S3. Receive reflected and scattered signals. Through a sensor array installed behind the drill bit, it receives and collects detection signals reflected and scattered from different geological interfaces in front in real time. S4. Downhole signal preprocessing and feature extraction: Using the signal processing module embedded in the downhole tool, the received raw detection signal is preprocessed in real time, and the effective signal is amplified and digitized. The weak effective signal is amplified and converted into a digital signal, and preliminary analysis is performed to extract the feature parameters of the signal. S5. Data compression and real-time upload: The processing unit will compress and package the data, and then transmit the key data to the ground in real time through the transmission system. S6. Ground data processing and imaging: After receiving the data from downhole, the ground computer system processes it and generates a formation profile image at a certain distance in front of the drill bit. S7. Geological interpretation and risk identification: Combine regional geological data and real-time imaging results to interpret the images and identify the type, location and distance of adverse geological bodies; S8. Generate early warnings and provide decision support: Based on the interpretation results, the system generates tiered early warning information and displays the visualization results and early warning prompts on the drilling monitoring platform to provide decision support for engineers.

2. The system and method for advanced detection of adverse geological conditions using oil and gas well drill bits according to claim 1, characterized in that: The excitation device is installed inside the drill bit body and emits detection signals to the formation directly in front of and to the side of the drill bit. The excitation device uses a sound wave generator and a wideband piezoelectric ceramic transducer array, which is embedded in the lower outer wall of the short section in a ring. A total of 8 transducer units are arranged and evenly distributed.

3. The system and method for advanced detection of adverse geological conditions using oil and gas well drill bits according to claim 2, characterized in that: The aforementioned acoustic wave generator employs a monopole mode, where all broadband piezoelectric ceramic transducers are synchronously excited to generate longitudinal waves; or a dipole mode, where the broadband piezoelectric ceramic transducers of the symmetrical unit are excited in opposite phases to generate transverse waves, in order to detect different lithologies and fluids.

4. The system and method for advanced detection of adverse geological conditions using oil and gas well drill bits according to claim 3, characterized in that: The sensor array in step S3 uses an acoustic receiver and is a three-component accelerometer sensor array. Four groups of sensors are arranged in a ring, and each group contains three accelerometers that are orthogonal to each other (X / Y / Z).

5. The system and method for advanced detection of adverse geological conditions using oil and gas well drill bits according to claim 4, characterized in that: Step S4, downhole signal preprocessing and feature extraction, includes a control and preprocessing circuit compartment and a signal preprocessing module. The control and preprocessing circuit compartment uses a field-programmable gate array (FPGA) chip for precise control of transmission timing and synchronous acquisition. The signal preprocessing module includes a preamplifier, an anti-aliasing filter, and an analog-to-digital converter.

6. The system and method for advanced detection of adverse geological conditions using oil and gas well drill bits according to claim 5, characterized in that: The real-time preprocessing in step S4 includes noise reduction filtering to remove strong noise interference from drill bit rock breaking, drill string vibration, and mud pump.

7. The system and method for advanced detection of adverse geological conditions using oil and gas well drill bits according to claim 6, characterized in that: The workflow for amplifying and converting the weak effective signal into a digital signal in step S4 is as follows: 1) Acceleration causes inertial force: When the accelerometer chip is subjected to external acceleration, according to Newton's second law, an inertial force will be generated acting on the mass block. The direction of this force is opposite to the direction of acceleration. 2) Displacement of the mass block: This inertial force will overcome the elastic force of the spring, causing the mass block to undergo a small displacement relative to the chip frame. The greater the acceleration, the greater the inertial force, and the greater the displacement. 3) Displacement changes capacitance: Fixed plates are fixed on both sides of the mass block and the chip frame, while the mass block itself acts as a movable electrode, thus forming two capacitors: C1 and C2. When there is no acceleration, the mass block is in the middle position, and C1 = C2. When there is acceleration, the mass block moves closer to one fixed electrode and away from the other, causing one capacitor to increase, C1 to increase because the distance d decreases, and the other capacitor to decrease, C2 to decrease because the distance d increases. 4) Capacitance changes are detected: Nanoscale mechanical displacement is converted into a measurable electrical signal by measuring the difference between C1 and C2.

8. The system and method for advanced detection of adverse geological conditions using oil and gas well drill bits according to claim 7, characterized in that: The signal extraction in the module involves converting the current signal into a voltage signal at the acquisition end, followed by subsequent processing. This is achieved using a switched capacitor circuit, the core of which is a differential capacitance detection scheme. The workflow is as follows: 1) The sensor module outputs two capacitance values, C1 and C2, that change with acceleration; 2) Analog front-end - Capacitor-to-voltage conversion, operating through precise timing control: Phase 1, also known as the charging phase: The switch connects one end of C1 and C2 to the reference voltage Vref and the other end to the input of the operational amplifier; Phase 2, also known as the transfer phase: the switch is switched to transfer the charge of the capacitor to the feedback capacitor Cf of the operational amplifier; Since C1 and C2 have different charges, the net charge transferred to the feedback capacitor is proportional to the charge difference. The operational amplifier converts this charge difference into a voltage signal Vout. The formula is: Vout ∝ (C1 - C2) × Vref / Cf The output voltage signal Vout reflects the magnitude and direction of the acceleration. If C1 > C2, the output voltage is positive; if C1 < C2, the output voltage is negative. 3) Analog-to-digital conversion: An analog-to-digital converter converts analog voltage values ​​into digital values; 4) Digital signal processing and output: The digitized signal undergoes further calibration, filtering, and temperature compensation processing, and is then output to the main processor through a standard digital interface.

Images