Intelligent injection system and method for efficient polymer injection well blocking remover

Abstract

The invention relates to the technical field of polymer injection well blocking removal, in particular to an intelligent injection system and method for efficient polymer injection well blocking remover. According to the method, a pulse type injection mechanism is established, a reference pressure reference curve is determined based on wellhead pressure falling characteristics in the early stage of injection, then the relative reference deviation of the wellhead pressure falling form of each injection round is compared and analyzed to comprehensively evaluate the formation change condition, and the formation flow conductivity is further evaluated in combination with the wellhead pressure falling condition. Therefore, the blocking removal condition is comprehensively judged to control the injection of the blocking remover; according to the method, the blocking removal state can be accurately evaluated, automatic stopping can be achieved after blocking removal is completed, excessive injection is avoided, meanwhile, early warning can be immediately triggered and injection can be stopped when a formation collapse accident occurs, and the injection effect of the efficient polymer injection well blocking remover is improved.

Description

Technical Field

[0001] This invention relates to the field of polymer injection well unblocking technology, specifically to an intelligent injection system and method for a highly efficient polymer injection well unblocking agent. Background Technology

[0002] In polymer flooding operations in petroleum engineering, as the polymer is injected and advanced, it easily cross-links into a gel deep within the formation, blocking pores and significantly reducing formation permeability, thus affecting production efficiency. Therefore, a high-efficiency polymer injection unblocking agent is usually injected into the wellbore to disrupt the gel structure. Accurately determining the unblocking status is crucial during the unblocking process; currently, this is mainly determined by observing the decrease in wellhead pressure, and a pressure decrease is generally considered an indicator of effective unblocking.

[0003] However, unblocking agents can reduce fluid viscosity through chemical reactions (rheological changes) and increase formation permeability by dissolving blockages (structural changes). Both the reduction in fluid viscosity and the increase in formation permeability lead to a decrease in wellhead pressure. The false pressure drop caused by rheological changes can easily mask the true progress of formation pore dissolution and unblocking, potentially leading to premature cessation of unblocking operations and "false unblocking" when the fluid becomes thinner but the formation blockage has not been truly resolved. In addition, when incidents such as formation skeleton fracture or severe crossflow occur, it is difficult to distinguish them from normal and efficient unblocking based on pressure values, resulting in a failure to intervene in time and causing serious formation damage, thus leading to poor unblocking injection results. Summary of the Invention

[0004] To address the technical problem of poor injection effect of high-efficiency polymer injection well unblocking agents, the present invention aims to provide an intelligent injection system and method for high-efficiency polymer injection well unblocking agents. The specific technical solution adopted is as follows: A smart injection method for a highly efficient polymer injection well unblocking agent, the method comprising: During the pulsed unblocking agent injection process, the unblocking agent injection volume during the constant rate injection phase of each injection cycle and the wellhead pressure curve during the pump shutdown and fallback phase are obtained. Based on the wellhead pressure curve during the pump stop and fallback phase of the first preset number of injection cycles after the start of injection, a reference pressure curve is determined; in each injection cycle, the formation heterogeneity change coefficient is determined according to the change deviation of the wellhead pressure curve relative to the reference pressure curve during the pump stop and fallback phase. In each injection cycle, the formation conductivity coefficient is obtained based on the changing trend of the wellhead pressure curve during the pump shutdown and fallback phase, and the amount of unblocking agent injected during the constant-rate injection phase; the structural blockage improvement coefficient for each injection cycle is obtained based on the deviation of the formation conductivity coefficient between adjacent injection cycles, and the formation heterogeneity change coefficient for each injection cycle; the unblocking agent injection is controlled based on the structural blockage improvement coefficient and the formation heterogeneity change coefficient.

[0005] Furthermore, the method for obtaining the reference pressure curve includes: The wellhead pressure curve during the pump stop and fall-back phase of the preset number of injection cycles after the start of injection is selected, and baseline removal and standardization processing are performed. The processed curve is used as the reference pressure curve.

[0006] Furthermore, the method for obtaining the formation heterogeneity change coefficient includes: In each injection cycle, the wellhead pressure curve during the pump shutdown and fallback phase is subjected to baseline removal and standardization to obtain the wellhead pressure curve to be analyzed; the DTW distance between the wellhead pressure curve to be analyzed and the reference pressure curve is used as the formation heterogeneity change coefficient.

[0007] Furthermore, baseline removal and standardization processes include: The wellhead pressure at the last monitoring moment in the wellhead pressure curve is used as the pressure benchmark. The wellhead pressure at each monitoring moment in the wellhead pressure curve is subtracted from the pressure benchmark to remove the baseline. The wellhead pressure at each monitoring moment in the baseline-removed wellhead pressure curve is then subjected to Z-Score standardization.

[0008] Furthermore, the method for obtaining the formation conductivity coefficient includes: In each injection cycle, the pressure change is determined based on the difference in wellhead pressure at the beginning and end of the wellhead pressure curve; the pressure change is then divided by the amount of unblocking agent injected to obtain the formation conductivity coefficient.

[0009] Furthermore, the method for obtaining the structural blockage improvement coefficient includes: In each injection cycle, a historical change reference coefficient is determined based on the distribution characteristics of the formation heterogeneity change coefficients in all its historical injection cycles; and a formation change confidence factor is determined based on the deviation of the formation heterogeneity change coefficients in each injection cycle relative to the historical change reference coefficients. Based on the formation conductivity coefficient of each injection cycle and the deviation of the formation conductivity coefficient from the adjacent previous historical injection cycle, the formation change parameters are determined. The formation change parameters are weighted using the formation change confidence factor to obtain the structural blockage improvement coefficient.

[0010] Furthermore, the method for obtaining the formation change confidence factor includes: The formation heterogeneity change coefficient for each injection cycle is used as the numerator, and the sum of the formation heterogeneity change coefficient for each injection cycle, the historical change reference coefficient, and the preset non-zero positive parameter is used as the denominator. The ratio is used as the formation change confidence factor.

[0011] Further, controlling the injection of the unblocking agent based on the structural blockage improvement coefficient and the formation heterogeneity change coefficient includes: Based on the formation conductivity coefficient of the first preset number of water injection cycles after the injection begins, a reference factor for improving structural blockage is determined; In each injection round, if the structural blockage improvement coefficient of the preceding second-preset number of injection rounds is less than the structural blockage improvement reference factor, the unblocking is deemed to have ended normally, and the unblocking agent injection is stopped; if the formation heterogeneity change coefficient is greater than the preset change coefficient, the formation structure is deemed to have undergone severe distortion, the unblocking agent injection is stopped, and a structural instability risk warning is issued; if the determination result is neither the normal end of unblocking nor severe distortion of the formation structure, the pulsed injection of the unblocking agent continues.

[0012] Furthermore, the pulsed unblocking agent injection process includes: The unblocking agent is injected according to a preset intermittent pulse injection action; in each injection round, the unblocking agent maintains a constant injection rate during the constant injection phase, and after the constant injection phase ends, it enters the pump stop and fall back phase and stops injection.

[0013] A smart injection system for a high-efficiency polymer injection well unblocking agent is disclosed. The system includes a memory, a processor, and a computer program stored in the memory and executable on the processor. When the processor executes the computer program, it implements the steps of the smart injection method for the high-efficiency polymer injection well unblocking agent.

[0014] The present invention has the following beneficial effects: This invention establishes a pulsed injection mechanism and, during the pulsed unblocking agent injection process, acquires the unblocking agent injection volume during the constant-rate injection phase of each injection cycle and the wellhead pressure curve during the pump shutdown and pullback phase. Through an intermittent cyclic monitoring mode, it ensures both the efficiency of the unblocking operation and allows for periodic analysis and evaluation of the unblocking status. Furthermore, based on the wellhead pressure curves during the pump shutdown and pullback phases of the first preset number of injection cycles after the start of injection, a reference pressure curve characterizing the initial structural morphology of the formation before unblocking is determined. Then, in each injection cycle, based on the deviation of the wellhead pressure curve relative to the reference pressure curve during the pump shutdown and pullback phase, a value reflecting the formation's porosity is determined. The invention establishes a pulsed injection mechanism that accurately assesses formation conductivity and formation changes, automatically stops injection after unblocking, avoids over-injection, and can immediately trigger warnings and stop injection in the event of formation collapse, thus improving the injection effect of unblocking agents in high-efficiency polymer injection wells. Furthermore, based on the changing trend of the wellhead pressure curve during the pump shutdown and fallback phase, and the injection volume of unblocking agent during the constant-rate injection phase, a formation conductivity coefficient characterizing formation blockage is obtained. Then, the deviation in the formation conductivity coefficient between adjacent injection cycles is analyzed to determine the improvement in conductivity, and the formation heterogeneity change coefficient for each injection cycle is combined with an analysis of whether the formation structure change is caused by unblocking, indirectly assessing the risk of formation damage, and obtaining the structural blockage improvement coefficient for each injection cycle. Finally, the injection of unblocking agent is controlled based on the structural blockage improvement coefficient and the formation heterogeneity change coefficient. Attached Figure Description

[0015] To more clearly illustrate the technical solutions and advantages in the embodiments of the present invention or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0016] Figure 1 A flowchart illustrating an intelligent injection method for a high-efficiency polymer injection well unblocking agent according to an embodiment of the present invention; Figure 2 This is a flowchart illustrating a method for obtaining a structural blockage improvement coefficient according to an embodiment of the present invention. Detailed Implementation

[0017] To further illustrate the technical means and effects adopted by the present invention to achieve its intended purpose, the following, in conjunction with the accompanying drawings and preferred embodiments, details the specific implementation, structure, features, and effects of an intelligent injection system and method for high-efficiency polymer injection well unblocking agent proposed according to the present invention. In the following description, different "one embodiment" or "another embodiment" do not necessarily refer to the same embodiment. Furthermore, specific features, structures, or characteristics in one or more embodiments can be combined in any suitable form.

[0018] Unless otherwise defined, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this invention pertains.

[0019] The following description, in conjunction with the accompanying drawings, details the specific scheme of the intelligent injection system and method for high-efficiency polymer injection well unblocking agent provided by the present invention.

[0020] Please see Figure 1 The diagram illustrates a flowchart of an intelligent injection method for a high-efficiency polymer injection well unblocking agent according to an embodiment of the present invention, specifically including: Step S1: During the pulsed unblocking agent injection process, obtain the unblocking agent injection volume during the constant-rate injection phase of each injection round and the wellhead pressure curve during the pump shutdown and fallback phase.

[0021] During the unblocking operation of polymer injection wells, the high-speed flow of fluid in the wellbore generates severe frictional resistance on the pipe wall. This frictional resistance is greater than and unstable than the formation seepage resistance, and often masks the weak seepage characteristic signals of the formation. In order to obtain state data that can truly reflect the formation seepage resistance for subsequent analysis of formation unblocking, this embodiment of the invention will perform pulsed injection of the unblocking agent.

[0022] In a preferred embodiment of the present invention, considering that when injection stops, the frictional resistance of the pipe wall decreases or disappears, and the wellhead pressure naturally drops, the pressure data at this time can truly reflect the seepage resistance at the formation depth, thereby helping to assess the unblocking situation; therefore, the pulsed unblocking agent injection process includes: The unblocking agent is injected according to a preset intermittent pulse injection action; in each injection round, the unblocking agent maintains a constant injection rate during the constant injection phase, and after the constant injection phase ends, it enters the pump stop and fall back phase and stops injection.

[0023] Specifically, the unblocking agent is pumped into the formation through the injection pump and the pulse injection action is triggered at preset intervals such as 30 minutes. Each triggering enters an injection cycle. Each injection cycle includes a constant-rate injection phase and a pump stop and fall-back phase. The duration of the constant-rate injection phase is 60 seconds, and the duration of the pump stop and fall-back phase is 300 seconds. The implementer can also adjust it according to the actual situation. The process involves using a frequency converter to control the speed of the injection pump, causing it to inject the unblocking agent into the well at a set flow rate. During preset intervals, the unblocking agent is pumped through the injection pump... to m 3 The pumping rate is normal at / s, although slight fluctuations may occur. During the constant-rate injection phase, the unblocking agent is injected at a set constant flow rate. m 3 / s injection; after the constant rate injection phase ends, the pump stops and the unblocking agent is pumped out. The injection process of the pulsed unblocking agent is characterized by a cyclical pumping pattern: 30 minutes of normal pumping - 60 seconds of constant pumping - 300 seconds of pumping stop - 30 minutes of normal pumping - 60 seconds of constant pumping - 300 seconds of pumping stop... The preset 30-minute interval is the main pumping phase, and the 60-second constant pumping - 300-second pumping stop is the pumping monitoring phase. This intermittent cyclical monitoring mode ensures both the efficiency of the unblocking operation and the ability to periodically analyze and evaluate the unblocking situation.

[0024] Further, the injection volume of unblocking agent during the constant-rate injection phase of each injection cycle and the wellhead pressure curve during the pump shutdown and fall-back phase were obtained to provide a data analysis basis for subsequent analysis of the unblocking operation status.

[0025] As an example, during the constant-rate injection phase of each injection cycle, instantaneous flow data is collected at a high frequency, such as 10Hz, using a high-precision flow meter installed at the injection pump outlet; the instantaneous flow data during the constant-rate injection phase is integrated to obtain the amount of unblocking agent injected. When the constant-rate injection phase ends, a pump stop command is triggered, and the high-pressure valve at the wellhead is closed, putting the wellbore in a sealed state. At the same time, the pressure sensor installed at the wellhead begins to collect wellhead pressure data at a sampling frequency of 1Hz until the pump stop and fall-back phase ends. The wellhead pressure data is then sorted in time sequence, and a cubic spline interpolation algorithm is used to fit the wellhead pressure curve. It should be noted that the integral and cubic spline interpolation algorithms are well-known techniques and will not be elaborated further; in other examples, implementers can also adjust the sampling frequency according to the actual situation.

[0026] Step S2: Based on the wellhead pressure curves during the pump stop and fallback phase of the first preset number of injection cycles after the start of injection, determine the reference pressure curve; in each injection cycle, determine the formation heterogeneity change coefficient based on the deviation of the wellhead pressure curve from the reference pressure curve during the pump stop and fallback phase.

[0027] In the initial stage of the unblocking operation, the interaction between the formation and the injected fluid may not have reached a steady state, and the data fluctuates greatly, so no unblocking analysis or judgment is performed. In one embodiment of the present invention, the preset number is set to 3, which can also be adjusted by the implementer. The first 3 injection rounds are the monitoring and accumulation period, during which no formation unblocking analysis or unblocking agent injection control is performed to avoid misjudgment caused by initial data fluctuations. From the 4th injection round onwards, the formal monitoring period begins, and after each injection round, an unblocking analysis and unblocking agent injection control are performed.

[0028] Since the wellhead pressure curve during the pump stop and fall-back phase of the initial injection rounds can characterize the initial structural morphology of the formation before unblocking, it can provide a benchmark for subsequent assessment of the changes in formation structure relative to the initial structural morphology. Therefore, in this embodiment of the invention, a reference pressure curve is first determined based on the wellhead pressure curve during the pump stop and fall-back phase of the first preset number of injection cycles after the injection begins; the reference pressure curve provides a comparison benchmark for subsequent operations.

[0029] Considering that the wellhead pressure in the early injection rounds is mainly affected by the wellbore volume effect rather than the actual formation feedback, the data noise is extremely high. After a predetermined number of injection rounds, the fluid properties in the wellbore and the pressure field in the near-wellbore zone have initially established a balance, and the data is more reliable. Therefore, in order to avoid the wellbore storage effect and the instability of the flow establishment period in the early stage of operation, the wellhead pressure curve during the pump stop and fall-back phase of the predetermined number of injection rounds after the start of injection can be selected as the initial reference. Furthermore, considering that during the unblocking injection process, the injection of a large amount of fluid into the formation will cause the formation's basic energy to gradually accumulate, which manifests as an overall baseline drift of the wellhead pressure, that is, the final return pressure of different injection rounds is constantly increasing. For example, the first round may tend to 10 MPa, and the tenth round may tend to 12 MPa. The baseline drift will interfere with the change characteristics of the wellhead pressure curve for subsequent injection rounds. In order to ensure that the data of different injection rounds have a unified basis for comparison, it is necessary to further perform baseline removal and standardization processing on the wellhead pressure curves (not only the preset number of injection rounds, but also all injection rounds). Based on this, in a preferred embodiment of the present invention, the method for obtaining the reference pressure curve includes: Select the wellhead pressure curve during the pump stop and fall-back phase of the preset number of injection cycles after the start of injection, and perform baseline removal and standardization processing. Use the processed curve as the benchmark pressure reference curve.

[0030] As an example, the wellhead pressure curve during the pump shutdown and fallback phase of the third injection cycle after the start of injection is first selected, and then further baseline removal and standardization are performed.

[0031] Since the pressure at the end of the pump stop and fall-off phase represents the formation pressure after that injection cycle, it can be regarded as a pressure benchmark. Subtracting this pressure benchmark from the wellhead pressure at each monitoring moment in the wellhead pressure curve can make the wellhead pressure curves of different injection cycles show a trend of pressure falling back to 0, only retaining the morphological characteristics of pressure fall-off, thereby avoiding baseline interference. Furthermore, as the unblocking agent is continuously injected, the fluid viscosity will change, which may lead to different degrees of distortion in the pressure drop characteristics. Directly analyzing the numerical differences may be misjudged as a significant structural change in the formation. By standardizing the wellhead pressure curves of different injection cycles, the wellhead pressure curves of different amplitudes can be compressed to the same standard scale, which facilitates the subsequent evaluation of the differences in the morphological characteristics of pressure drop and accurately determines the unblocking status. In a preferred embodiment of the present invention, the baseline removal and standardization processes include: The wellhead pressure at the last monitoring moment in the wellhead pressure curve is used as the pressure benchmark. The wellhead pressure at each monitoring moment in the wellhead pressure curve is subtracted from the pressure benchmark to remove the baseline. The wellhead pressure at each monitoring moment in the baseline-removed wellhead pressure curve is then Z-score standardized.

[0032] Specifically, for each wellhead pressure curve, the wellhead pressure at the end of the monitoring time is used as the pressure benchmark, and the wellhead pressure at each monitoring time in the wellhead pressure curve is lowered to the pressure benchmark, thereby obtaining the wellhead pressure curve after baseline removal; further, the wellhead pressure at each monitoring time in the wellhead pressure curve after baseline removal is Z-score standardized, and the standardized values ​​are used as data points to obtain the standardized wellhead pressure curve.

[0033] At this point, baseline removal and standardization of the wellhead pressure curve for each wellhead have been completed. After baseline removal and standardization of the wellhead pressure curve for the third injection cycle, the baseline pressure reference curve is obtained.

[0034] It should be noted that Z-Score standardization is a well-known technique and will not be elaborated further. The standardization of each wellhead pressure curve after baseline removal is carried out separately and is based on its own performance. The wellhead pressure in the wellhead pressure curves cannot be completely consistent. When they are completely consistent, the wellhead pressure curves after baseline removal and standardization are made into a straight line with y=1.

[0035] After obtaining the baseline pressure reference curve characterizing the initial formation state, the changes in formation structure after each injection cycle can be analyzed based on the deviation of the wellhead pressure curve relative to the baseline pressure reference curve during the pump shutdown and fallback phase of each injection cycle. This allows for the determination of the formation heterogeneity change coefficient. The formation heterogeneity change coefficient initially reflects the drastic changes in the formation porosity structure, preparing for subsequent assessment of unblocking.

[0036] It should be noted that the methods for unblocking analysis and unblocking agent injection control after each injection cycle (the end of the pump shutdown and fall-off phase) are the same. Here, we will only take any injection cycle as an example for analysis and description, and will not go into detail again.

[0037] Preferably, in one embodiment of the present invention, as the unblocking agent is continuously injected, the fluid viscosity varies in different injection rounds, which may cause different degrees of scaling distortion of the pressure fallback characteristics on the time axis. For example, when the viscosity is high, the fluid flow rate is slow, and the wellhead pressure curve is stretched on the time axis; conversely, when the viscosity is low, the flow rate is fast, and the time axis may be compressed. Simply measuring the difference in pressure fallback characteristics with Euclidean distance may ignore the influence of time axis scaling distortion, resulting in a difference measurement bias, which in turn affects the subsequent unblocking analysis effect. The Dynamic Time Warping (DTW) algorithm can flexibly align two sequences that have scaling, thereby ignoring the overall scaling of the pressure curve caused by fluid thinning, and accurately assessing the curve shape distortion caused by changes in formation structure, i.e., the morphological difference of the wellhead pressure curve relative to the initial baseline. Therefore, the method for obtaining the formation heterogeneity change coefficient includes: In each injection cycle, the wellhead pressure curve during the pump shutdown and fallback phase is subjected to baseline removal and standardization to obtain the wellhead pressure curve to be analyzed; the DTW distance between the wellhead pressure curve to be analyzed and the benchmark pressure reference curve is used as the formation heterogeneity change coefficient.

[0038] It should be noted that the calculation of DTW distance is a well-known technique and will not be elaborated further.

[0039] Step S3: In each injection cycle, based on the changing trend of the wellhead pressure curve during the pump shutdown and fallback phase, and the amount of unblocking agent injected during the constant-rate injection phase, obtain the formation conductivity coefficient; based on the variation deviation of the formation conductivity coefficient between adjacent injection cycles, and the formation heterogeneity change coefficient of each injection cycle, obtain the structural blockage improvement coefficient of each injection cycle; control the unblocking agent injection based on the structural blockage improvement coefficient and the formation heterogeneity change coefficient.

[0040] Considering that when the formation is highly blocked (poor permeability), after the pump is stopped, the fluid is difficult to diffuse to distant locations due to the dense formation, resulting in a relatively low pressure drop; conversely, if the formation is not highly blocked, the pressure may drop rapidly after the pump is stopped; during normal unblocking, the change in the shape of the pressure drop curve caused by effective structural unblocking is usually significantly greater than the change in shape caused by changes in fluid viscosity alone. Therefore, the trend of the wellhead pressure curve during the pump stoppage and drop phase can, to some extent, characterize the formation conductivity. Furthermore, considering that the amount of unblocking agent injected in different injection rounds may be affected by factors such as power grid voltage fluctuations, changes in pump and valve leakage efficiency, and changes in agent viscosity, resulting in slight deviations, in order to eliminate the error caused by the fluctuation of the injection amount, the formation conductivity coefficient is further analyzed in conjunction with the amount of unblocking agent injected in the constant rate injection stage. The formation conductivity coefficient intuitively characterizes the formation blockage by using the pressure drop characteristics after pump shutdown, which prepares for subsequent analysis of formation conductivity changes in different cycles to assess the unblocking situation.

[0041] Preferably, in one embodiment of the present invention, the method for obtaining the formation conductivity coefficient includes: In each injection cycle, the pressure change is determined based on the difference in wellhead pressure at the beginning and end of the monitoring time in the wellhead pressure curve; the pressure change is divided by the amount of unblocking agent injected to obtain the formation conductivity coefficient.

[0042] Specifically, in the wellhead pressure curves after baseline removal and standardization, the difference between the wellhead pressure at the first monitoring time and the wellhead pressure at the last monitoring time is taken as the pressure change, and then divided by the amount of unblocking agent injected to obtain the formation conductivity coefficient.

[0043] It should be noted that when the difference is negative, the negative value is truncated, that is, the pressure change is directly set to 0; before the pump is stopped, the amount of unblocking agent injected cannot be 0, so it is always meaningful as the denominator.

[0044] Considering that the variation deviation of the formation conductivity coefficient between adjacent injection cycles can characterize the improvement of formation conductivity, and the formation heterogeneity change coefficient of the injection cycle can not only characterize the improvement of formation conductivity, but also provide relevant reference value for formation skeleton fragmentation and malignant flow, when the formation heterogeneity change coefficient changes abruptly or deviates greatly, the possibility of formation damage is greater, and thus the formation structure blockage improvement coefficient can be accurately assessed.

[0045] Based on this, the structural blockage improvement coefficient for each injection cycle is obtained by considering the variation deviation of the formation conductivity coefficient between adjacent injection cycles and the formation heterogeneity change coefficient for each injection cycle, thus providing a basis for subsequent assessment of the unblocking status.

[0046] Preferably, in one embodiment of the present invention, please refer to Figure 2 The flowchart illustrates a method for obtaining a structural blockage improvement coefficient according to an embodiment of the present invention, specifically including: Step S301: In each injection cycle, based on the distribution characteristics of the formation heterogeneity change coefficients of all its historical injection cycles, determine the historical change reference coefficient; and based on the deviation of the formation heterogeneity change coefficient of each injection cycle relative to the historical change reference coefficient, determine the formation change confidence factor.

[0047] Considering that in each injection cycle, if there were no significant changes in the formation structure in the past historical injection cycles (including unblocking completion or formation damage risk, i.e., no cessation of unblocking operations), the formation heterogeneity change coefficient of the historical injection cycles can usually be regarded as caused by background noise such as sensor jitter, power grid fluctuations, and small pump vibrations. By statistically analyzing the distribution characteristics of the formation heterogeneity change coefficients of all historical injection cycles, a fluctuation baseline can be determined. This fluctuation baseline can characterize the typical level of morphological differences caused by minor random disturbances in the context of unblocking operations. In turn, it can provide relevant references for subsequent assessment of the possibility that the relative change of the formation heterogeneity change coefficient is caused by real changes in the formation structure, i.e., the formation change confidence factor. It should be noted that when the historical injection cycles initially change significantly due to changes in the formation structure, the abrupt changes may be smoothed out by the statistical characteristics of the historical injection cycles, and will be detected immediately, triggering the risk of formation damage. Based on this, before the unblocking is completed or the risk of formation damage is detected, the historical change parameters can be evaluated based on the distribution characteristics of the formation heterogeneity change coefficient of the historical injection cycles. The historical change parameters provide a reference for historical background noise, providing data preparation for subsequent analysis of the relative abrupt changes in the formation heterogeneity change coefficient to evaluate the confidence factor of formation change.

[0048] As an example, taking any injection cycle as an example, the average value of the formation heterogeneity change coefficient of all previous historical injection cycles (excluding the first 3) is used as the historical change reference coefficient; further, the formation change confidence factor that eliminates noise interference and characterizes the actual formation structure change is obtained.

[0049] In a preferred embodiment of the present invention, considering that the formation heterogeneity change coefficient of the injection round includes the unblocking response (the morphological deviation of the wellhead pressure relative to the reference caused by unblocking) and noise interference, when the formation heterogeneity change coefficient of the injection round is much larger than the historical change reference coefficient, it indicates that the unblocking response is more significant than the noise, and the formation heterogeneity change is more likely to be caused by actual unblocking; conversely, when the formation heterogeneity change coefficient of the injection round is less than or close to the historical change reference coefficient, the unblocking response is weak and the unblocking confidence is low; therefore, the method for obtaining the formation change confidence factor includes: The formation heterogeneity change coefficient of each injection cycle is used as the numerator, and the sum of the formation heterogeneity change coefficient of each injection cycle, the historical change reference coefficient, and the preset non-zero positive parameter is used as the denominator. The ratio is used as the formation change confidence factor.

[0050] It should be noted that, in order to avoid the denominator being zero, a preset non-zero positive parameter is set, such as 0.001. The denominator is the sum of the formation heterogeneity change coefficient of the injection cycle, the historical change reference coefficient, and the preset non-zero positive parameter.

[0051] Step S302: Determine the formation change parameters based on the deviation of the formation conductivity coefficient of each injection cycle from the formation conductivity coefficient of the previous adjacent historical injection cycle.

[0052] As an example, the difference between the formation conductivity coefficient of the injection cycle and the formation conductivity coefficient of the previous historical injection cycle is used as the formation change parameter; when the difference is less than 0, negative values ​​are truncated, that is, the formation change parameter is set to 0.

[0053] Step S303: The formation change parameters are weighted using the formation change confidence factor to obtain the structural blockage improvement coefficient.

[0054] As an example, the formation change confidence factor is multiplied by the formation change parameter to obtain the structural blockage improvement coefficient for the corresponding injection cycle. The structural blockage improvement coefficient quantifies the actual degree of formation structure change, but may also include changes caused by factors such as formation skeleton fragmentation and malignant flow.

[0055] After determining the structural blockage improvement coefficient, the injection of unblocking agent is further controlled by combining the formation heterogeneity change coefficient. This allows the injection of unblocking agent to be stopped when unblocking is completed, and also enables early intervention in the event of formation skeleton fracture, malignant flow, or other accidents, thus avoiding further losses.

[0056] Considering that the formation conductivity coefficient of the initial water injection cycle can help assess the blockage situation, and thus determine the structural blockage improvement target, i.e., the structural blockage improvement reference factor, to help determine whether the blockage has been cleared to the expected target, thereby regulating the injection of unblocking agent; and considering that when the formation heterogeneity change coefficient undergoes a huge abrupt change, it may lead to significant changes in formation structure, such as formation skeleton fragmentation and malignant flow, etc., in which case the injection of unblocking agent needs to be stopped immediately to prevent further formation damage, and risk warnings can be issued for timely intervention; and outside of the case where the blockage is cleared and the risk warning is issued, the pulse injection of unblocking agent can continue. Based on this, in a preferred embodiment of the present invention, controlling the injection of the unblocking agent according to the structural blockage improvement coefficient and the formation heterogeneity change coefficient includes: Based on the formation conductivity coefficient of the pre-set number of water injection cycles after the injection begins, a reference factor for improving structural blockage is determined. In each injection cycle, if the structural blockage improvement coefficient of the previous second consecutive preset number of injection cycles is less than the structural blockage improvement reference factor, the unblocking is judged to have ended normally, and the unblocking agent injection is stopped; if the formation heterogeneity change coefficient is greater than the preset change coefficient, the formation structure is judged to have drastic distortion, the unblocking agent injection is stopped, and a structural instability risk warning is issued; if the judgment result is not the normal end of unblocking and drastic distortion of formation structure, the pulse injection of the unblocking agent continues.

[0057] As an example, the pre-set quantity is set to 1, and the formation conductivity coefficient of the first injection cycle after the injection begins is multiplied by a preset ratio, such as 3%, to obtain the improvement target, i.e., the structural blockage improvement reference factor. When the unblocking improvement reaches 97% of the initial level, the expected unblocking target can be considered to have been achieved. Implementers can also adjust the pre-set quantity and preset ratio themselves, such as setting the preset ratio to a preset value based on experience analysis.

[0058] For any injection round k, the preset second quantity is set to 2. When the structural blockage improvement coefficients of the k-th, k-1-th and k-2-th injection rounds are all less than the structural blockage improvement reference factor, it is determined that the structural unblocking improvement has reached the expected goal and tends to be stable. Then it can be determined that the unblocking is normally completed. At this time, the frequency converter will be controlled to stop the injection pump from continuing to inject the unblocking agent. The implementer can also adjust the preset second quantity himself.

[0059] The preset change coefficient is set to 3 times the historical change reference coefficient, and the implementer can also adjust it according to the actual situation. When the formation heterogeneity change coefficient of injection round k is greater than the preset change coefficient, it indicates that the wellhead pressure drop pattern may have undergone unexpected and severe distortion, and the formation may have experienced skeleton collapse or malignant flow. At this time, it is determined that the formation structure is severely distorted, the unblocking agent injection is stopped immediately, and a structural instability risk warning is issued.

[0060] If neither of the above two results (normal completion of unblocking and severe distortion of formation structure) is determined, the pulse injection of unblocking agent will continue, that is, the cyclical pumping process of 30min normal pumping-60s constant pumping-300s pump stop-30min normal pumping-60s constant pumping-300s pump stop... will be performed.

[0061] Based on the same inventive concept, this invention also proposes an intelligent injection system for a high-efficiency polymer injection well unblocking agent. The system includes a memory, a processor, and a computer program stored in the memory and executable on the processor. When the processor executes the computer program, it implements the steps of the intelligent injection method for a high-efficiency polymer injection well unblocking agent described in steps S1-S3.

[0062] In summary, this invention establishes a pulsed injection mechanism and determines a reference pressure curve based on the wellhead pressure drop characteristics in the early stage of injection. Then, it compares and analyzes the relative reference deviation of the wellhead pressure drop pattern in each injection cycle to comprehensively assess the formation change. Furthermore, it combines the wellhead pressure drop situation to assess the formation conductivity, thereby comprehensively judging the unblocking status and controlling the injection of unblocking agent. This invention can accurately assess the unblocking status and automatically stop after unblocking, avoiding over-injection. At the same time, it can also immediately trigger early warning and stop injection in the event of formation collapse, improving the injection effect of unblocking agent in high-efficiency polymer injection wells.

[0063] It should be noted that the order of the above embodiments of the present invention is merely for descriptive purposes and does not represent the superiority or inferiority of the embodiments. The processes depicted in the accompanying drawings do not necessarily require a specific or sequential order to achieve the desired result. In some embodiments, multitasking and parallel processing are also possible or may be advantageous.

[0064] The various embodiments in this specification are described in a progressive manner. The same or similar parts between the various embodiments can be referred to each other. Each embodiment focuses on describing the differences from other embodiments.

Claims

1. A smart injection method for a high-efficiency polymer injection well unblocking agent, characterized in that, The method includes: During the pulsed unblocking agent injection process, the unblocking agent injection volume during the constant rate injection phase of each injection cycle and the wellhead pressure curve during the pump shutdown and fallback phase are obtained. Based on the wellhead pressure curve during the pump stop and fallback phase of the first preset number of injection cycles after the start of injection, a reference pressure curve is determined; in each injection cycle, the formation heterogeneity change coefficient is determined according to the change deviation of the wellhead pressure curve relative to the reference pressure curve during the pump stop and fallback phase. In each injection cycle, the formation conductivity coefficient is obtained based on the changing trend of the wellhead pressure curve during the pump shutdown and fallback phase, and the amount of unblocking agent injected during the constant-rate injection phase; the structural blockage improvement coefficient for each injection cycle is obtained based on the deviation of the formation conductivity coefficient between adjacent injection cycles, and the formation heterogeneity change coefficient for each injection cycle; the unblocking agent injection is controlled based on the structural blockage improvement coefficient and the formation heterogeneity change coefficient.

2. The intelligent injection method for a high-efficiency polymer injection well unblocking agent according to claim 1, characterized in that, The method for obtaining the reference pressure curve includes: The wellhead pressure curve during the pump stop and fall-back phase of the preset number of injection cycles after the start of injection is selected, and baseline removal and standardization processing are performed. The processed curve is used as the reference pressure curve.

3. The intelligent injection method for a high-efficiency polymer injection well unblocking agent according to claim 1, characterized in that, The method for obtaining the formation heterogeneity change coefficient includes: In each injection cycle, the wellhead pressure curve during the pump shutdown and fallback phase is subjected to baseline removal and standardization to obtain the wellhead pressure curve to be analyzed; the DTW distance between the wellhead pressure curve to be analyzed and the reference pressure curve is used as the formation heterogeneity change coefficient.

4. The intelligent injection method for a high-efficiency polymer injection well unblocking agent according to claim 2 or 3, characterized in that, Baseline removal and standardization processes include: The wellhead pressure at the last monitoring moment in the wellhead pressure curve is used as the pressure benchmark. The wellhead pressure at each monitoring moment in the wellhead pressure curve is subtracted from the pressure benchmark to remove the baseline. The wellhead pressure at each monitoring moment in the baseline-removed wellhead pressure curve is then subjected to Z-Score standardization.

5. The intelligent injection method for a high-efficiency polymer injection well unblocking agent according to claim 1, characterized in that, The method for obtaining the formation conductivity coefficient includes: In each injection cycle, the pressure change is determined based on the difference in wellhead pressure at the beginning and end of the wellhead pressure curve; the pressure change is then divided by the amount of unblocking agent injected to obtain the formation conductivity coefficient.

6. The intelligent injection method for a high-efficiency polymer injection well unblocking agent according to claim 1, characterized in that, The method for obtaining the structural blockage improvement coefficient includes: In each injection cycle, a historical change reference coefficient is determined based on the distribution characteristics of the formation heterogeneity change coefficients in all its historical injection cycles; and a formation change confidence factor is determined based on the deviation of the formation heterogeneity change coefficients in each injection cycle relative to the historical change reference coefficients. Based on the formation conductivity coefficient of each injection cycle and the deviation of the formation conductivity coefficient from the previous adjacent historical injection cycle, the formation change parameters are determined. The formation change parameters are weighted using the formation change confidence factor to obtain the structural blockage improvement coefficient.

7. The intelligent injection method for a high-efficiency polymer injection well unblocking agent according to claim 6, characterized in that, The method for obtaining the formation change confidence factor includes: The formation heterogeneity change coefficient for each injection cycle is used as the numerator, and the sum of the formation heterogeneity change coefficient for each injection cycle, the historical change reference coefficient, and the preset non-zero positive parameter is used as the denominator. The ratio is used as the formation change confidence factor.

8. The intelligent injection method for a high-efficiency polymer injection well unblocking agent according to claim 1, characterized in that, The injection of the unblocking agent is controlled based on the structural blockage improvement coefficient and the formation heterogeneity alteration coefficient, including: Based on the formation conductivity coefficient of the first preset number of water injection cycles after the injection begins, a reference factor for improving structural blockage is determined; In each injection round, if the structural blockage improvement coefficient of the preceding second-preset number of injection rounds is less than the structural blockage improvement reference factor, the unblocking is deemed to have ended normally, and the unblocking agent injection is stopped; if the formation heterogeneity change coefficient is greater than the preset change coefficient, the formation structure is deemed to have undergone severe distortion, the unblocking agent injection is stopped, and a structural instability risk warning is issued; if the determination result is neither the normal end of unblocking nor severe distortion of the formation structure, the pulsed injection of the unblocking agent continues.

9. The intelligent injection method for a high-efficiency polymer injection well unblocking agent according to claim 1, characterized in that, The pulsed unblocking agent injection process includes: The unblocking agent is injected according to a preset intermittent pulse injection action; in each injection round, the unblocking agent maintains a constant injection rate during the constant injection phase, and after the constant injection phase ends, it enters the pump stop and fall back phase and stops injection.

10. A smart injection system for a high-efficiency polymer injection well unblocking agent, the system comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, characterized in that, When the processor executes the computer program, it implements the steps of the intelligent injection method for a high-efficiency polymer injection well unblocking agent as described in any one of claims 1 to 9.

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