A real-time data acquisition and intelligent feedback regulation method for fracturing fluid hydration process

Abstract

The present application relates to the technical field of feedback control of continuous mixing process of fracturing fluid, and discloses a real-time data acquisition and intelligent feedback regulation method for hydration process of fracturing fluid. The method determines the flow transmission time of fracturing fluid flowing from an upstream first detection node to a downstream second detection node, obtains real-time apparent viscosities of the two nodes, and establishes a corresponding relationship according to the flow transmission time. Based on the viscosity change amount and the time scale, a dynamic hydration rate gradient is determined. Then, a predicted terminal complete hydration viscosity is determined according to a preset hydration viscosity extrapolation relationship, and a limited regulation instruction acting on an upstream material proportioning actuator is generated accordingly. When the control process does not satisfy the effective control condition, the output of the limited regulation instruction is frozen or limited, and a protection state is generated. The present application can reduce the misregulation caused by the fact that the single-point instant apparent viscosity does not reflect the terminal complete hydration state, and improve the stability of the feedback control of continuous mixing of fracturing fluid.

Description

Technical Field

[0001] This invention relates to the field of feedback control technology for continuous mixing process of fracturing fluid, specifically to a method for real-time data acquisition and intelligent feedback adjustment of the hydration process of fracturing fluid. Background Technology

[0002] During the continuous mixing and delivery of fracturing fluid, after the thickener or liquid additive is added to the aqueous phase, it usually needs to undergo swelling, dispersion, and hydration evolution. The apparent viscosity of the fracturing fluid does not reach its final state immediately after the material is added. Especially under the condition of continuous online mixing at large flow rates, the fracturing fluid may still be in the early or transitional hydration state before flowing from the upstream mixing location to the downstream use.

[0003] In existing technologies, continuous mixing equipment typically collects industrial process parameters such as main flow rate, liquid level, and feeding status, and adjusts the feed pump, feed screw, valve, or other material proportioning actuators through a controller; some solutions also set up online viscosity detection positions at the manifold end, compare the detected instantaneous apparent viscosity with the target viscosity, and then generate adjustment commands based on the deviation to correct the upstream material feeding amount.

[0004] However, the above methods typically use the instantaneous apparent viscosity at a certain detection location as the feedback benchmark, failing to fully consider the spatial transport time lag of the fracturing fluid in the continuous mixing and delivery pipeline and the ongoing evolution of hydration. When the detected value corresponds to an incompletely hydrated state, the system may misjudge the instantaneous low viscosity as insufficient dosing, thereby inducing the upstream material proportioning actuator to make excessive adjustments.

[0005] The information disclosed in this background section is intended only to enhance the understanding of the overall background of the invention and should not be construed as an admission or in any way implying that the information constitutes prior art known to those skilled in the art. Summary of the Invention

[0006] The purpose of this invention is to provide a real-time data acquisition and intelligent feedback adjustment method for the hydration process of fracturing fluid. This method addresses the problem in existing technologies that directly use the instantaneous apparent viscosity at a single detection location as the feedback benchmark. This approach fails to adequately consider the spatial transmission time lag and the continued evolution of hydration in the continuous mixing and delivery pipeline of fracturing fluid, which can easily lead to erroneous adjustments by the upstream material proportioning actuator. Furthermore, it lacks a protective backoff boundary when there are invalid inputs, abnormal viscosity changes, out-of-bounds prediction results, or abnormal execution feedback.

[0007] The technical solution of this invention is: a real-time data acquisition and intelligent feedback adjustment method for the hydration process of fracturing fluid. The method is applied to the main control processing unit in a continuous fracturing fluid mixing control system. The main control processing unit establishes data or control connections with a main flow detection unit, a first detection node, a second detection node, and an upstream material proportioning actuator. The method includes: determining the flow transmission time of the fracturing fluid from the first detection node to the second detection node based on the flow correspondence between the first and second detection nodes, wherein the first detection node is an apparent viscosity detection node located upstream along the fracturing fluid flow direction, and the second detection node is an apparent viscosity detection node located downstream along the fracturing fluid flow direction; acquiring the first real-time apparent viscosity at the first detection node and the second real-time apparent viscosity at the second detection node, and establishing a data acquisition and intelligent feedback adjustment method based on the sampling time matching of the flow transmission time. Establish the correspondence between the first real-time apparent viscosity and the second real-time apparent viscosity; based on the viscosity change between the corresponding first real-time apparent viscosity and the second real-time apparent viscosity, and using the flow transport time as the time scale, determine the dynamic hydration rate gradient of the fracturing fluid between the first detection node and the second detection node; according to the preset hydration viscosity extrapolation relationship, determine the predicted terminal fully hydrated viscosity based on the dynamic hydration rate gradient and the second real-time apparent viscosity; obtain the target viscosity, and based on the deviation of the predicted terminal fully hydrated viscosity from the target viscosity, generate a restricted adjustment command acting on the upstream material proportioning actuator; perform an effectiveness judgment on the control process that generates the restricted adjustment command based on the predicted terminal fully hydrated viscosity, and when the judgment result is that the effective control conditions are not met, freeze or limit the output of the restricted adjustment command and generate a protection state.

[0008] Preferably, determining the flow transmission time of fracturing fluid from the first detection node to the second detection node includes: acquiring the effective flow volume and the real-time volumetric discharge rate of the main pipeline between the first detection node and the second detection node; when the real-time volumetric discharge rate of the main pipeline meets the effective calculation conditions, determining the flow transmission time based on the effective flow volume and the real-time volumetric discharge rate of the main pipeline; when the real-time volumetric discharge rate of the main pipeline does not meet the effective calculation conditions, pausing the updating of the flow transmission time and restricting the output of the restricted adjustment command.

[0009] Preferably, establishing the correspondence between the first real-time apparent viscosity and the second real-time apparent viscosity through a sampling time matching method based on the flow transport time includes: obtaining sampling identification information corresponding to the first real-time apparent viscosity and the second real-time apparent viscosity respectively; performing data validity preprocessing on the first real-time apparent viscosity and the second real-time apparent viscosity; and matching the sampling time of the preprocessed first real-time apparent viscosity and the second real-time apparent viscosity according to the flow transport time and the sampling identification information to obtain two-point viscosity data corresponding to the same fluid evolution segment.

[0010] Preferably, the step of matching the sampling times of the preprocessed first real-time apparent viscosity and the second real-time apparent viscosity according to the flow transport time and the sampling identification information to obtain two-point viscosity data corresponding to the same fluid evolution segment includes: establishing a sampling buffer queue on the first detection node side; retrieving the corresponding first real-time apparent viscosity from the sampling buffer queue according to the flow transport time and matching it with the second real-time apparent viscosity; when the detection node data does not meet the valid matching conditions, using historical valid sampling values ​​for short-term holding; when the short-term holding cannot meet the matching conditions, restricting the output of the restricted adjustment command.

[0011] Preferably, determining the dynamic hydration rate gradient of the fracturing fluid between the first detection node and the second detection node includes: using the corresponding first real-time apparent viscosity as the upstream viscosity value and the corresponding second real-time apparent viscosity as the downstream viscosity value to determine the viscosity change; determining the apparent viscosity evolution state according to the direction of the viscosity change; and determining the dynamic hydration rate gradient based on the viscosity change and the flow transport time when the flow transport time meets the effective time scale condition.

[0012] Preferably, determining the apparent viscosity evolution state based on the direction of the viscosity change includes: determining the apparent viscosity evolution state based on the magnitude relationship between the first real-time apparent viscosity and the second real-time apparent viscosity characterized by the viscosity change, and using the apparent viscosity evolution state and the dynamic hydration rate gradient to determine the predicted terminal fully hydrated viscosity and the validity determination.

[0013] Preferably, determining the predicted terminal fully hydrated viscosity includes: determining the second real-time apparent viscosity as the current transition state viscosity; determining the viscosity evolution trend according to the dynamic hydration rate gradient; and performing a final state correction on the current transition state viscosity based on the preset hydration viscosity extrapolation relationship to obtain the predicted terminal fully hydrated viscosity.

[0014] Preferably, the step of correcting the current transition state viscosity to the final state based on the preset hydration viscosity extrapolation relationship to obtain the predicted terminal fully hydrated viscosity includes: correcting the hydration compensation parameter in the preset hydration viscosity extrapolation relationship according to the fracturing fluid conditions; determining the predicted terminal fully hydrated viscosity based on the corrected hydration compensation parameter, the dynamic hydration rate gradient, and the second real-time apparent viscosity; and performing boundary protection processing when the predicted terminal fully hydrated viscosity exceeds the effective prediction range.

[0015] Preferably, the generation of the restricted adjustment command acting on the upstream material proportioning actuator includes: determining the control deviation of the predicted terminal fully hydrated viscosity relative to the target viscosity; generating an adjustment amount based on the control deviation; and restricting the adjustment amount according to a preset output constraint rule to obtain the restricted adjustment command.

[0016] Preferably, the determination of the effectiveness of the control process for generating the restricted adjustment command based on the predicted terminal fully hydrated viscosity includes: monitoring the execution status of the first real-time apparent viscosity, the second real-time apparent viscosity, the dynamic hydration rate gradient, the predicted terminal fully hydrated viscosity, and the restricted adjustment command fed back by the upstream material proportioning actuator to obtain determination data; based on the determination data, determining whether the control process meets the effective control conditions; when the determination result fails, it is determined that the effective control conditions are not met, and the incremental output of the restricted adjustment command is frozen in the protection state; when the determination results pass in multiple consecutive effective control cycles, the protection state is released, and the output of the restricted adjustment command is restored.

[0017] The beneficial effects of this invention are as follows: By setting a first detection node and a second detection node along the fracturing fluid flow direction, and using the effective flow volume and the real-time volumetric displacement of the main channel to determine the flow transmission time, the first real-time apparent viscosity and the second real-time apparent viscosity can correspond to the same or a matching fluid evolution segment; then, by determining the dynamic hydration rate gradient through the viscosity change and the flow transmission time, and by determining the predicted terminal fully hydrated viscosity based on the dynamic hydration rate gradient and the second real-time apparent viscosity, the feedback benchmark is transformed from a single-point instantaneous apparent viscosity to a predicted terminal fully hydrated viscosity, thereby reducing the interference of incomplete hydration and spatial transmission time lag on feedback regulation, and reducing the risk of excessive correction by the upstream material proportioning actuator induced by instantaneous low viscosity signals; at the same time, by judging the input validity, prediction boundary, gradient anomaly, and execution status, the output of the restricted adjustment command is frozen or limited when there is an anomaly, so that the continuous mixing feedback control process has a protective backoff boundary. Attached Figure Description

[0018] Figure 1This is a schematic diagram of the continuous fracturing fluid mixing control system of the present invention;

[0019] Figure 2 This is a flowchart of the real-time data processing of the fracturing fluid hydration process according to the present invention.

[0020] Figure 3 This is a schematic diagram of the two-point viscosity matching and final viscosity extrapolation of the present invention;

[0021] Figure 4 This is a flowchart illustrating the generation and output constraints of the restricted adjustment instructions of the present invention.

[0022] Figure 5 This is a flowchart of the control process effectiveness determination and protection process of the present invention. Detailed Implementation

[0023] To make the objectives, technical solutions, and advantages of this invention clearer, the invention 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 for explaining the invention and are not intended to limit the invention; that is, the described embodiments are merely some embodiments of the invention, and not all embodiments. The components of the embodiments of the invention described and shown in the accompanying drawings can generally be arranged and designed in various different configurations.

[0024] Therefore, the following detailed description of the embodiments of the invention provided in the accompanying drawings is not intended to limit the scope of the claimed invention, but merely to illustrate selected embodiments of the invention. All other embodiments obtained by those skilled in the art based on the embodiments of the invention without inventive effort are within the scope of protection of the invention.

[0025] It should be noted that relational terms such as "first" and "second" are used merely to distinguish one entity or operation from another, and do not necessarily require or imply any such actual relationship or order between these entities or operations. Furthermore, the terms "comprising," "including," or any other variations thereof are intended to cover non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements includes not only those elements but also other elements not expressly listed, or elements inherent to such a process, method, article, or apparatus. Without further limitations, an element defined by the phrase "comprising one..." does not exclude the presence of other identical elements in the process, method, article, or apparatus that includes said element.

[0026] As mentioned earlier, in existing technologies, continuous mixing equipment typically collects industrial process parameters such as main pipeline flow rate, liquid level, and feeding status, and adjusts the feed pump, feed screw, valves, or other material proportioning actuators through controllers. Some solutions also set up online viscosity detection points at the manifold end, comparing the detected instantaneous apparent viscosity with the target viscosity, and then generating adjustment commands based on the deviation to correct the upstream material dosage. However, these methods usually directly use the instantaneous apparent viscosity at a certain detection point as the feedback benchmark, failing to fully consider the spatial transport time lag of fracturing fluid in the continuous mixing and delivery pipeline and the ongoing evolution of hydration. When the detected value corresponds to an incompletely hydrated state, the system may misjudge the instantaneous low viscosity as insufficient dosage, thereby inducing excessive adjustment by the upstream material proportioning actuators.

[0027] To address this, the present invention provides a method for real-time data acquisition and intelligent feedback adjustment of fracturing fluid hydration process, in order to solve the above-mentioned technical problems.

[0028] Example 1:

[0029] Combination Figure 2 As shown in the embodiment of the present invention, a real-time data acquisition and intelligent feedback adjustment method for the hydration process of fracturing fluid can be executed by the main control processing unit in the continuous mixing control system of fracturing fluid. The method mainly includes the following steps:

[0030] S100. Based on the flow correspondence between the first detection node and the second detection node, determine the flow transmission time of the fracturing fluid from the first detection node to the second detection node, wherein the first detection node is an apparent viscosity detection node located upstream along the fracturing fluid flow direction, and the second detection node is an apparent viscosity detection node located downstream along the fracturing fluid flow direction.

[0031] S200: Obtain the first real-time apparent viscosity at the first detection node and the second real-time apparent viscosity at the second detection node, and establish the correspondence between the first real-time apparent viscosity and the second real-time apparent viscosity by a sampling time matching method based on the flow transport time.

[0032] S300. Based on the viscosity change between the corresponding first real-time apparent viscosity and the second real-time apparent viscosity, and using the flow transport time as a time scale, determine the dynamic hydration rate gradient of the fracturing fluid between the first detection node and the second detection node.

[0033] S400. Based on the preset hydration viscosity extrapolation relationship, and based on the dynamic hydration rate gradient and the second real-time apparent viscosity, determine the predicted terminal fully hydrated viscosity.

[0034] S500: Obtain the target viscosity; based on the deviation of the predicted terminal fully hydrated viscosity from the target viscosity, generate a restricted adjustment command acting on the upstream material proportioning actuator.

[0035] S600. The effectiveness of the control process that generates the restricted adjustment command based on the predicted terminal's fully hydrated viscosity is determined. When the determination result is that the effective control conditions are not met, the output of the restricted adjustment command is frozen or restricted, and a protection state is generated.

[0036] In this embodiment, the flow correspondence is used to indicate that the first detection node and the second detection node are not ordinary parallel detection points, but rather form an observation relationship along the fracturing fluid flow direction that can characterize the same or matching fluid evolution segment; the flow correspondence can be reflected by the effective flow volume between the first detection node and the second detection node, the real-time volumetric displacement of the main path, and the flow transmission time determined therefrom.

[0037] Based on the above steps, this invention establishes a hydration evolution observation foundation along the flow direction through a first detection node and a second detection node. It transforms spatial location differences into a time scale through flow transmission time, and uses dynamic hydration rate gradient and predicted terminal fully hydrated viscosity to replace the single-point instantaneous apparent viscosity in the adjustment judgment, so that the restricted adjustment command can be formed according to the subsequent hydration trend of the fracturing fluid. When the control process does not meet the effective control conditions, it freezes or restricts the output of the restricted adjustment command and generates a protection state, reducing the risk of mis-adjustment caused by incompletely hydrated data directly entering the closed-loop adjustment.

[0038] Example 2:

[0039] To provide a more detailed explanation of the technical solutions provided in the above embodiments, the present invention also provides another preferred embodiment. For example... Figure 1 As shown, in Embodiment 2, a continuous data flow and control flow are formed between the main flow detection unit, the first detection node, the second detection node, the main control processing unit, the upstream material proportioning execution mechanism, and the feedback end of the upstream material proportioning execution mechanism. The main flow detection unit provides the main control processing unit with the real-time volumetric displacement of the main flow. The first and second detection nodes respectively provide the main control processing unit with apparent viscosity sampling data. The main control processing unit completes sampling matching, flow transport time calculation, dynamic hydration rate gradient determination, prediction of terminal fully hydrated viscosity determination, generation of restricted adjustment instructions, and validity determination. The restricted adjustment instructions are applied to the upstream material proportioning execution mechanism, and the feedback end then transmits the execution status back to the main control processing unit.

[0040] In Embodiment 2 of the present invention, the main control processing unit can perform the above-mentioned processing according to an effective control cycle. Within the effective control cycle (e.g., 1 second, derived from the main control processing unit's scanning cycle, the viscosity detection node refresh cycle, and the on-site control strategy), data acquisition, data matching, calculation, judgment, and output update are completed. If any necessary data fails to form a valid result within the effective control cycle, the predicted terminal fully hydrated viscosity is not updated, and the system enters a hold or limit output state.

[0041] In Embodiment 2 of the present invention, the flow correspondence between the first detection node and the second detection node in step S100 can be specifically reflected in the relationship of the observation pipe segments formed by the two detection nodes along the fracturing fluid flow direction, and the conversion relationship between the effective flow volume corresponding to the observation pipe segment and the real-time volumetric discharge of the main pipeline. Based on this flow correspondence, determining the flow transmission time of the fracturing fluid from the first detection node to the second detection node can include the following steps:

[0042] S110. Obtain the effective flow volume between the first detection node and the second detection node and the real-time volume displacement of the main road.

[0043] S120. When the real-time volumetric displacement of the main road meets the effective calculation conditions, the flow transmission time is determined based on the effective flow volume and the real-time volumetric displacement of the main road.

[0044] S130. When the real-time volume displacement of the main road does not meet the effective calculation conditions, the update of the flow transmission time is paused, and the output of the restricted adjustment command is limited.

[0045] Therefore, the flow transmission time is determined based on the flow correspondence between the two detection nodes; in another preferred embodiment, the flow correspondence is achieved by converting between the effective flow volume and the real-time volumetric displacement of the main road, so that the first real-time apparent viscosity and the second real-time apparent viscosity can correspond to the same or matching fluid evolution segment in subsequent steps.

[0046] For example, in Embodiment 2 of the present invention, steps S110 to S130 may further include the following process: First, a first detection node and a second detection node are determined along the fracturing fluid flow direction in the continuous fracturing fluid mixing and delivery pipeline. The first detection node is located upstream, and the second detection node is located downstream. The pipe section between the two detection nodes is used as the observation pipe section. The main control processing unit establishes node numbers for the first detection node and the second detection node respectively, and records their relationship in the downstream direction of water flow to avoid interpreting the two apparent viscosity detection nodes as ordinary parallel sampling points.

[0047] Secondly, the main control processing unit obtains the effective flow volume between the first detection node and the second detection node (e.g., 0.080 m³, derived from the geometric dimensions of the pipe sections between the nodes, the equivalent volume correction of the auxiliary pipe fittings, and the system's pre-stored calibration results). In one specific implementation, the effective flow volume can be determined according to the following relationship:

[0048]

[0049] in, The effective flow volume between the first and second detection nodes is expressed in m³, and it is derived from the calibration results of the equivalent length between nodes, the effective flow cross-sectional area, and the equivalent volume correction of the auxiliary pipe fittings. The effective flow cross-sectional area of ​​the observed pipe section is measured in m², and its source is the converted value of the pipe section's inner diameter or the calibration value in the equipment ledger (e.g., 0.030 m²). The equivalent length between the first and second detection nodes is expressed in meters (m) and is derived from pipeline layout diagrams, field measurements, or pre-stored system parameters (e.g., 2.50m). This is the equivalent volume correction for auxiliary pipe fittings, in m³, and is derived from the equivalent calibration values ​​(e.g., 0.005 m³) of valves, elbows, joints, dead zones, or auxiliary structures. When the effective flow volume calibration has been completed on-site, the main control processing unit can directly call the pre-stored effective flow volume calibration value in the system, without recalculating it in each control cycle.

[0050] Next, the main control processing unit acquires the real-time volumetric displacement of the main pipeline (e.g., 0.020 m³ / s, derived from the real-time output of the main pipeline flow detection unit) and determines whether it meets the valid calculation conditions. The valid calculation conditions may include the real-time volumetric displacement of the main pipeline being greater than the minimum effective displacement threshold (e.g., 0.005 m³ / s, derived from the lower limit of the flow detection unit's range, pump stop protection strategy, and historical calibration results), the flow signal being within the effective range, and no communication anomalies occurring. If the real-time volumetric displacement of the main pipeline meets the valid calculation conditions, the main control processing unit determines the flow transmission time based on the effective flow volume and the real-time volumetric displacement of the main pipeline.

[0051]

[0052] in, The flow transport time of fracturing fluid from the first detection node to the second detection node is expressed in seconds. Effective flow volume, in m³; The real-time volumetric displacement of the main pipeline, in m³ / s, is derived from the main pipeline flow detection unit. Continuing with the example above, when the effective flow volume is 0.080 m³ and the real-time volumetric displacement of the main pipeline is 0.020 m³ / s, the flow transmission time is 4 s. This flow transmission time is incorporated into the subsequent sampling time matching process and the dynamic hydration rate gradient calculation process. If the calculated flow transmission time exceeds the effective time scale boundary (e.g., 0.5 s to 60 s, derived from the observed pipe section volume, displacement fluctuation range, and equipment safety strategy), the main control processing unit suspends updating the flow transmission time and restricts the output of limited adjustment commands.

[0053] In Embodiment 2 of the present invention, step S200, which establishes the correspondence between the first real-time apparent viscosity and the second real-time apparent viscosity by means of a sampling time matching method based on the flow transport time, may include the following steps:

[0054] S210. Obtain the sampling identification information corresponding to the first real-time apparent viscosity and the second real-time apparent viscosity respectively;

[0055] S220. Perform data validity preprocessing on the first real-time apparent viscosity and the second real-time apparent viscosity;

[0056] S230. Based on the flow transport time and the sampling identification information, the sampling time of the preprocessed first real-time apparent viscosity and the second real-time apparent viscosity is matched to obtain two-point viscosity data corresponding to the same fluid evolution segment.

[0057] S240. Establish a sampling buffer queue on the side of the first detection node;

[0058] S250. Based on the flow transmission time, retrieve the corresponding first real-time apparent viscosity from the sampling buffer queue and match it with the second real-time apparent viscosity;

[0059] S260. When the data of the detection node does not meet the valid matching conditions, the historical valid sampled value is used for short-term retention.

[0060] S270. When the short-term hold cannot meet the matching conditions, the output of the restricted adjustment command is limited.

[0061] For example, in Embodiment 2 of the present invention, steps S210 to S270 may further include the following process: a first detection node collects a first real-time apparent viscosity, a second detection node collects a second real-time apparent viscosity, and the main control processing unit adds sampling identification information to each viscosity sample value. The sampling identification information may include the sampling time, control cycle number, detection node number, and data validity flag. The sampling cycle (e.g., 1 second, derived from the main control processing unit's scanning cycle and the apparent viscosity detection node's refresh frequency) is used to constrain the update rhythm of the cache queue.

[0062] Subsequently, the main control processing unit performs data validity preprocessing on the first and second real-time apparent viscosities. This preprocessing may include range validity judgment, line break judgment, boundary violation judgment, spike rejection, and short-term filtering. The effective apparent viscosity range (e.g., 5 mPa·s to 80 mPa·s, derived from the apparent viscosity detection node range, the target fracturing fluid process viscosity range, and equipment calibration results) is used to exclude obviously invalid sampled values; the spike change threshold (e.g., a change exceeding 15 mPa·s within two adjacent effective control cycles, derived from historical noise statistics and detection node repeatability tests) is used to identify abnormal abrupt changes caused by undissolved micelle impacts, transient bubbles, or communication jitter. For data that fails preprocessing, the main control processing unit does not directly send it to the subsequent dynamic hydration rate gradient calculation.

[0063] like Figure 3 As shown, the main control processing unit establishes a sampling buffer queue on the first detection node side. The sampling buffer queue stores the first real-time apparent viscosity and its sampling identifier information in the order of sampling time. The buffer depth (e.g., 120 sampling points corresponding to 120s, derived from the maximum flow transport time boundary and sampling period) should cover the maximum possible flow transport time. When the second detection node generates the second real-time apparent viscosity at the current time, the main control processing unit retrieves the first real-time apparent viscosity at the corresponding historical time from the sampling buffer queue of the first detection node based on the current flow transport time. For example, when the second detection node collects the second real-time apparent viscosity at 100s, and the current flow transport time is 4s, the main control processing unit retrieves the first real-time apparent viscosity of the first detection node near 96s, and combines it with the second real-time apparent viscosity at 100s to form two-point viscosity data corresponding to the same fluid evolution segment.

[0064] During the matching process, the main control processing unit can set a sampling time matching tolerance window (e.g., ±0.5s, derived from the sampling period, the clock accuracy of the main control processing unit, and the flow fluctuation calibration results). If there is a first real-time apparent viscosity in the buffer queue that falls within the matching tolerance window, then the first real-time apparent viscosity is matched with the current second real-time apparent viscosity. If no data that meets the matching conditions is found, but the detection node only experiences a short-term sampling loss, then historical valid sampling values ​​are used for short-term retention. The trend of the predicted terminal's fully hydrated viscosity is not updated within the short-term retention period (e.g., 3 valid control periods, derived from the detection node's communication jitter tolerance strategy and output safety strategy). If the short-term retention still cannot meet the matching conditions, the main control processing unit restricts the output of the limited adjustment command and marks this period as a data corresponding failure state.

[0065] In Embodiment 2 of the present invention, step S300, which involves determining the dynamic hydration rate gradient of the fracturing fluid between the first detection node and the second detection node, may include the following steps:

[0066] S310. Using the corresponding first real-time apparent viscosity as the upstream viscosity value and the corresponding second real-time apparent viscosity as the downstream viscosity value, determine the viscosity change.

[0067] S320. Determine the apparent viscosity evolution state based on the direction of the viscosity change.

[0068] S330. When the flow transport time meets the effective time scale condition, determine the dynamic hydration rate gradient based on the viscosity change and the flow transport time.

[0069] S340. Based on the relationship between the first real-time apparent viscosity and the second real-time apparent viscosity characterized by the viscosity change, determine the apparent viscosity evolution state, and use the apparent viscosity evolution state and the dynamic hydration rate gradient to determine the predicted terminal fully hydrated viscosity and the validity determination.

[0070] For example, in Embodiment 2 of the present invention, steps S310 to S340 may further include the following process: After obtaining the two-point viscosity data corresponding to the same fluid evolution segment, the main control processing unit uses the corresponding first real-time apparent viscosity as the upstream viscosity value and the corresponding second real-time apparent viscosity as the downstream viscosity value. The viscosity change is represented by the change in the downstream viscosity value relative to the upstream viscosity value. If the downstream viscosity value is higher than the upstream viscosity value and exceeds the noise tolerance range, it indicates that the fracturing fluid undergoes hydration and viscosity enhancement evolution between the first and second detection nodes; if the difference between the two does not exceed the noise tolerance range, it indicates that the viscosity evolution within the observed pipe segment is weak; if the downstream viscosity value is lower than the upstream viscosity value and exceeds the noise tolerance range, it indicates that there may be an abnormal inversion. The noise tolerance range (e.g., ±2 mPa·s, derived from the repeatability of the apparent viscosity detection nodes, historical noise statistics, and on-site calibration results) is used to avoid misjudging normal detection fluctuations as abnormal evolution.

[0071] When the flow transport time meets the effective time scale condition, the main control processing unit calculates the dynamic hydration rate gradient based on the viscosity change and the flow transport time:

[0072]

[0073] in, The dynamic hydration rate gradient is expressed in mPa·s / s. The first real-time apparent viscosity after the corresponding measurement is in mPa·s and is derived from the first detection node and its sampling buffer queue. The corresponding second real-time apparent viscosity, in mPa·s, is derived from the current valid sample value of the second detection node; The flow transport time, measured in seconds, is a time parameter determined based on the effective flow volume and the real-time volumetric displacement of the main flow path. For example, when the first real-time apparent viscosity is 18 mPa·s, the second real-time apparent viscosity is 26 mPa·s, and the flow transport time is 4 s, the dynamic hydration rate gradient is 2 mPa·s / s. This dynamic hydration rate gradient is incorporated into the process of determining the predicted terminal fully hydrated viscosity and simultaneously into the validity determination process.

[0074] If the dynamic hydration rate gradient is negative, or if multiple consecutive control windows are below the anomaly detection threshold, the main control processing unit will not simply interpret this state as insufficient dosing. The anomaly detection threshold (e.g., -0.5 mPa·s / s, derived from detection noise statistics, viscosity repeatability, and equipment safety strategies) and the continuous anomaly window (e.g., three consecutive effective control cycles, derived from control stability strategies or manual settings) are used to identify abnormal inversions or continuous anomalies. In this case, the dynamic hydration rate gradient is still sent to the effectiveness determination stage, but it will not drive incremental dosing; instead, it serves as the basis for triggering a protection state.

[0075] In Embodiment 2 of the present invention, step S400, which involves determining the predicted terminal fully hydrated viscosity, may include the following steps:

[0076] S410. Determine the second real-time apparent viscosity as the current transition state viscosity;

[0077] S420. Determine the viscosity evolution trend based on the dynamic hydration rate gradient;

[0078] S430. Based on the preset hydration viscosity extrapolation relationship, the current transition state viscosity is corrected to the final state to obtain the predicted terminal fully hydrated viscosity;

[0079] S440. Correct the hydration compensation parameter in the preset hydration viscosity extrapolation relationship according to the fracturing fluid conditions.

[0080] S450. Determine the predicted terminal fully hydrated viscosity based on the corrected hydration compensation parameters, the dynamic hydration rate gradient, and the second real-time apparent viscosity.

[0081] S460. When the viscosity of the predicted terminal after complete hydration exceeds the effective range of the prediction, perform boundary protection processing.

[0082] For example, in Embodiment 2 of the present invention, steps S410 to S460 may further include the following process: Since the second detection node is located downstream of the first detection node, the second real-time apparent viscosity is closer to the transition state of the fracturing fluid before subsequent use than the first real-time apparent viscosity. Therefore, the main control processing unit uses the second real-time apparent viscosity obtained by matching the sampling time as the current transition state viscosity. Subsequently, the main control processing unit judges the current fluid evolution trend based on the dynamic hydration rate gradient; when the dynamic hydration rate gradient is positive and no anomaly judgment is triggered, it indicates that the current transition state viscosity still has a trend of continuing to evolve towards the terminal fully hydrated viscosity; when the dynamic hydration rate gradient is close to zero, it indicates that the viscosity change in the observed pipe section is slowing down; when the dynamic hydration rate gradient is abnormally inverted, normal final state extrapolation update is not performed.

[0083] Under normal update conditions, the main control processing unit determines the predicted final fully hydrated viscosity based on a preset hydration viscosity extrapolation relationship. The input to this extrapolation relationship includes at least the dynamic hydration rate gradient and the second real-time apparent viscosity, and the output is the predicted final fully hydrated viscosity. A hydration compensation parameter (e.g., 0.20 s⁻¹, derived from thickener type, offline calibration curve, manufacturer-published curve, laboratory calibration, or temperature compensation lookup table) characterizes the compensation relationship as the current material system continues to approach the final state from the transition state. This hydration compensation parameter can be modified according to the fracturing fluid conditions. For example, when the temperature decreases from 25°C to 15°C, the hydration compensation parameter can be reduced by 10% based on a temperature compensation lookup table. This reduction percentage is derived from small-scale calibration, manufacturer-published curves, offline calibration results, or manual setting.

[0084]

[0085] in, To predict the final fully hydrated viscosity, the unit is mPa·s; The second real-time apparent viscosity, in mPa·s, is derived from the effective sampled value of the second detection node. The dynamic hydration rate gradient, in mPa·s / s, is determined based on the first real-time apparent viscosity, the second real-time apparent viscosity, and the flow transport time. The hydration compensation parameter, in units of 1 / s, is derived from thickener type, offline calibration curve, manufacturer-published curve, laboratory calibration, or temperature compensation lookup table. Continuing with the example above, when the second real-time apparent viscosity is 26 mPa·s, the dynamic hydration rate gradient is 2 mPa·s / s, and the hydration compensation parameter is 0.20 s⁻¹, the predicted final fully hydrated viscosity is 36 mPa·s.

[0086] After the predicted final hydration viscosity is formed, the main control processing unit determines whether it falls within the effective prediction range. The effective prediction range (e.g., 10 mPa·s to 80 mPa·s, derived from the physical boundaries of the material system, equipment safety limits, target process settings, offline calibration results, or manual settings) is used to exclude unreliable predicted values ​​caused by invalid inputs, abnormal inversions, or extrapolation distortions. If the predicted final hydration viscosity exceeds the effective prediction range, the main control processing unit performs boundary protection processing; this boundary protection processing includes at least one of the following: refusing to update the predicted value for the current cycle, using the previous effective predicted value for a short period, limiting the predicted final hydration viscosity, and restricting the output of limited adjustment commands, and then sending this state to the validity determination stage.

[0087] Combination Figure 4As shown, in Embodiment 2 of the present invention, step S500, which generates a restricted adjustment command acting on the upstream material proportioning actuator, may include the following steps:

[0088] S510. Determine the control deviation of the predicted terminal fully hydrated viscosity relative to the target viscosity;

[0089] S520. Generate an adjustment amount based on the control deviation;

[0090] S530. Limit the adjustment amount according to the preset output constraint rules to obtain the restricted adjustment command;

[0091] S540, The restricted adjustment command is output to the upstream material proportioning actuator.

[0092] For example, in Embodiment 2 of the present invention, steps S510 to S540 may further include the following process: The main control processing unit receives the target viscosity, which (e.g., 35 mPa·s, derived from the target viscosity setting terminal, construction process input, or upper computer process parameters) is used as a comparison benchmark for predicting the final fully hydrated viscosity. The main control processing unit does not directly compare the instantaneous apparent viscosity at the second detection node with the target viscosity, but instead compares the predicted final fully hydrated viscosity with the target viscosity and determines the deviation state based on the difference between the two. If the predicted final fully hydrated viscosity is lower than the target viscosity and exceeds the allowable deviation, an adjustment amount to increase the upstream material addition trend can be generated; if the predicted final fully hydrated viscosity is higher than the target viscosity and exceeds the allowable deviation, an adjustment amount to decrease the upstream material addition trend can be generated; if the predicted final fully hydrated viscosity is within the allowable deviation range, the current output is maintained or only a small maintenance adjustment is made.

[0093] To avoid frequent actuator actions caused by minor disturbances, the main control processing unit sets allowable deviations or control dead zones. These allowable deviations or control dead zones (e.g., ±2 mPa·s, derived from apparent viscosity fluctuations, actuator response accuracy, and historical calibration results) are used to determine whether a new adjustment quantity needs to be generated. After the adjustment quantity is generated, it is not directly output to the actuator but first undergoes preset output constraint rules. These preset output constraint rules may include a single-cycle correction limit (e.g., not exceeding 5% of the rated output, derived from actuator safety and anti-oscillation control strategies), a maximum output amplitude range (e.g., 0% to 100% of the rated output, derived from the actuator's rated capacity), an output change rate limit (e.g., not exceeding 3% of the rated output per effective control cycle, derived from actuator response capability and continuous mixing stability requirements), and a safety holding range under protection conditions (e.g., ±3% of the previous effective command, derived from the safety holding strategy).

[0094] The constrained adjustment command formed after the above constraints can be applied to the upstream material proportioning actuator. The upstream material proportioning actuator can be an actuator used to change the dosage of thickener or liquid additives, such as a dry powder feed screw, a liquid additive pump, a feed valve, or a frequency converter drive mechanism. The above examples of actuators are only used to illustrate the target of the constrained adjustment command; the essence of the main control processing unit's output is to correct the dosage of materials subsequently entering the pipeline, so that the final hydration viscosity of the fracturing fluid tends to the target viscosity.

[0095] Meanwhile, the feedback end of the upstream material proportioning actuator can transmit the actual execution status, execution status, and deviation between the actual output and the restricted adjustment command back to the main control processing unit. The feedback result enters the validity determination process of the next effective control cycle to determine whether the restricted adjustment command has been executed normally, and triggers subsequent protection control when the execution feedback is abnormal.

[0096] Combination Figure 5 As shown, in Embodiment 2 of the present invention, the effectiveness determination of the control process for generating the restricted adjustment command based on the predicted terminal's fully hydrated viscosity in step S600 may include the following steps:

[0097] S610. Monitor the execution status of the first real-time apparent viscosity, the second real-time apparent viscosity, the dynamic hydration rate gradient, the predicted terminal fully hydrated viscosity, and the restricted adjustment command fed back by the upstream material proportioning actuator to obtain judgment data.

[0098] S620. Based on the determination data, determine whether the control process meets the effective control conditions;

[0099] S630. When the judgment result fails, it is determined that the effective control conditions are not met, and the incremental output of the restricted adjustment command is frozen in the protection state.

[0100] S640. When the judgment result passes within multiple consecutive effective control cycles, the protection state is released and the output of the restricted adjustment command is restored.

[0101] For example, in Embodiment 2 of the present invention, steps S610 to S640 may further include the following process: the main control processing unit synchronously generates determination data within each effective control cycle. The determination data includes the effective state of the first real-time apparent viscosity, the effective state of the second real-time apparent viscosity, the sampling time matching state, the effective state of the main road real-time volumetric displacement, the dynamic hydration rate gradient state, whether the predicted terminal fully hydrated viscosity exceeds the limit, whether the restricted adjustment command has been output, and whether the actuator feedback is consistent with the command. The actuator feedback deviation threshold (e.g., 10% of the rated output, derived from the actuator feedback accuracy, frequency converter drive response error, and safety strategy) is used to determine whether the execution state is abnormal.

[0102] When the first or second real-time apparent viscosity is invalid, sampling time matching fails, the main pipeline real-time volumetric discharge does not meet the effective calculation conditions, the dynamic hydration rate gradient is lower than the anomaly judgment threshold, the predicted terminal fully hydrated viscosity exceeds the predicted effective range, or the actuator feedback is inconsistent with the restricted adjustment command, the main control processing unit determines that the control process does not meet the effective control conditions. At this time, the main control processing unit generates a protection state and freezes the incremental output of the restricted adjustment command in the protection state. The freezing of incremental output means no longer increasing the material dosage based on the current unreliable prediction result; the restriction of output means keeping the output within the safe holding range or limiting it to near the previous effective command. The safe holding range (e.g., ±3% of the previous effective command, derived from equipment safety strategy and continuous mixing stability requirements) is used to prevent the actuator from continuing to expand the adjustment range due to false low viscosity signals.

[0103] Before the protection status is lifted, the main control processing unit continuously monitors and determines the data. The number of consecutive effective control windows (e.g., 5 consecutive effective control cycles, derived from the stability recovery strategy, equipment safety strategy, or manual setting) is used to confirm whether the control process has returned to stability. When, within multiple consecutive effective control windows, the main pipeline real-time volumetric displacement is effective, the sampling at both detection nodes is effective, the sampling time matching is successful, the dynamic hydration rate gradient recovers to a non-abnormal state, the predicted terminal fully hydrated viscosity falls within the predicted effective range, and the execution feedback returns to normal, the main control processing unit lifts the protection status and restores the regulated output in a restricted manner. During restoration, the previous effective restricted regulation command can be used first, and then the output can be gradually restored to normal output according to the output change rate limit to avoid new closed-loop fluctuations occurring the instant the protection is lifted.

[0104] Accordingly, this invention establishes a hydration evolution observation section by setting a first and second detection node along the flow direction, converts the effective flow volume into flow transmission time by using the real-time volumetric displacement of the main road, and matches the sampling time to make the first real-time apparent viscosity and the second real-time apparent viscosity correspond to the same or a matching fluid evolution segment. Then, the predicted terminal complete hydration viscosity is determined by the dynamic hydration rate gradient and the preset hydration viscosity extrapolation relationship, so that the restricted regulation command is based on the predicted terminal complete hydration viscosity rather than the single-point instantaneous apparent viscosity. At the same time, the protection judgment is formed by the input validity, prediction validity, gradient abnormal state and execution feedback state, so that the control process freezes and restricts the output when abnormal, and resumes the restricted regulation after stabilization, thus forming a closed-loop implementation process in which acquisition, matching, prediction, regulation and protection backoff are mutually reinforcing.

[0105] The above description is merely a preferred embodiment of the technical solution of the present invention and is not intended to limit the scope of protection of the present invention. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of the present invention should be included within the scope of protection of the present invention.

Claims

1. A method for real-time data acquisition and intelligent feedback adjustment of fracturing fluid hydration process, characterized in that, A main control processing unit applied in a fracturing fluid continuous mixing control system, the method comprising: Based on the flow correspondence between the first detection node and the second detection node, the flow transmission time of the fracturing fluid from the first detection node to the second detection node is determined. The first detection node is the apparent viscosity detection node located upstream along the fracturing fluid flow direction, and the second detection node is the apparent viscosity detection node located downstream along the fracturing fluid flow direction. The first real-time apparent viscosity at the first detection node and the second real-time apparent viscosity at the second detection node are obtained, and the correspondence between the first real-time apparent viscosity and the second real-time apparent viscosity is established by a sampling time matching method based on the flow transport time. Based on the viscosity change between the corresponding first real-time apparent viscosity and the second real-time apparent viscosity, and using the flow transport time as the time scale, the dynamic hydration rate gradient of the fracturing fluid between the first detection node and the second detection node is determined. Based on the preset hydration viscosity extrapolation relationship, the predicted terminal fully hydrated viscosity is determined based on the dynamic hydration rate gradient and the second real-time apparent viscosity. Obtain the target viscosity, and based on the deviation of the predicted terminal fully hydrated viscosity from the target viscosity, generate a restricted adjustment command to act on the upstream material proportioning actuator; The effectiveness of the control process that generates the restricted adjustment command based on the predicted terminal's fully hydrated viscosity is determined. When the determination result is that the effective control conditions are not met, the output of the restricted adjustment command is frozen or limited, and a protection state is generated.

2. The method according to claim 1, characterized in that, The determination of the flow transport time of the fracturing fluid from the first detection node to the second detection node includes: Obtain the effective flow volume between the first detection node and the second detection node, and the real-time volumetric displacement of the main road. When the real-time volumetric displacement of the main road meets the effective calculation conditions, the flow transmission time is determined based on the effective flow volume and the real-time volumetric displacement of the main road. When the real-time volume displacement of the main road does not meet the effective calculation conditions, the update of the flow transmission time is paused and the output of the restricted adjustment command is limited.

3. The method according to claim 1, characterized in that, The step of establishing the correspondence between the first real-time apparent viscosity and the second real-time apparent viscosity by matching sampling times based on the flow transport time includes: Obtain the sampling identification information corresponding to the first real-time apparent viscosity and the second real-time apparent viscosity respectively; Perform data validity preprocessing on the first real-time apparent viscosity and the second real-time apparent viscosity; Based on the flow transport time and the sampling identification information, the sampling time of the preprocessed first real-time apparent viscosity and the second real-time apparent viscosity is matched to obtain two-point viscosity data corresponding to the same fluid evolution segment.

4. The method according to claim 3, characterized in that, The step of matching the sampling times of the preprocessed first real-time apparent viscosity and the second real-time apparent viscosity according to the flow transport time and the sampling identification information to obtain two-point viscosity data corresponding to the same fluid evolution segment includes: Establish a sampling buffer queue on the side of the first detection node; Based on the flow transmission time, the corresponding first real-time apparent viscosity is retrieved from the sampling buffer queue and matched with the second real-time apparent viscosity; When the data from the detected node does not meet the valid matching conditions, historical valid sampled values ​​are used for short-term retention. When the short-term hold cannot meet the matching conditions, the output of the restricted adjustment command is limited.

5. The method according to claim 1, characterized in that, Determining the dynamic hydration rate gradient of the fracturing fluid between the first detection node and the second detection node includes: The viscosity change is determined by using the corresponding first real-time apparent viscosity as the upstream viscosity value and the corresponding second real-time apparent viscosity as the downstream viscosity value. The apparent viscosity evolution state is determined based on the direction of the viscosity change. When the flow transport time meets the effective time scale condition, the dynamic hydration rate gradient is determined based on the viscosity change and the flow transport time.

6. The method according to claim 5, characterized in that, Determining the apparent viscosity evolution state based on the direction of the viscosity change includes: Based on the relationship between the first real-time apparent viscosity and the second real-time apparent viscosity characterized by the viscosity change, the apparent viscosity evolution state is determined, and the apparent viscosity evolution state and the dynamic hydration rate gradient are used to determine the predicted terminal fully hydrated viscosity and the validity determination.

7. The method according to claim 1, characterized in that, The determination of the predicted terminal fully hydrated viscosity includes: The second real-time apparent viscosity is determined as the current transition state viscosity; The viscosity evolution trend is determined based on the dynamic hydration rate gradient. Based on the preset hydration viscosity extrapolation relationship, the current transition state viscosity is corrected to the final state to obtain the predicted terminal fully hydrated viscosity.

8. The method according to claim 7, characterized in that, The step of performing final-state correction on the current transition state viscosity based on the preset hydration viscosity extrapolation relationship to obtain the predicted final fully hydrated viscosity includes: The hydration compensation parameters in the preset hydration viscosity extrapolation relationship are adjusted according to the fracturing fluid conditions. The predicted terminal fully hydrated viscosity is determined based on the corrected hydration compensation parameters, the dynamic hydration rate gradient, and the second real-time apparent viscosity. When the viscosity of the predicted terminal after complete hydration exceeds the effective range of the prediction, boundary protection processing is performed.

9. The method according to claim 1, characterized in that, The generation of restricted adjustment commands acting on the upstream material proportioning actuator includes: Determine the control deviation of the predicted terminal fully hydrated viscosity relative to the target viscosity; An adjustment amount is generated based on the control deviation; The adjustment amount is restricted according to the preset output constraint rules to obtain the restricted adjustment command.

10. The method according to claim 1, characterized in that, The determination of the effectiveness of the control process for generating the restricted adjustment command based on the predicted terminal's fully hydrated viscosity includes: The execution status of the first real-time apparent viscosity, the second real-time apparent viscosity, the dynamic hydration rate gradient, the predicted terminal fully hydrated viscosity, and the restricted adjustment command fed back by the upstream material proportioning actuator are monitored to obtain judgment data. Based on the determination data, it is determined whether the control process meets the effective control conditions; If the judgment result fails, it is determined that the effective control conditions are not met, and the incremental output of the restricted adjustment command is frozen in the protection state; When the judgment results pass within multiple consecutive effective control cycles, the protection state is released and the output of the restricted adjustment command is restored.

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