Method and system for analyzing main control factors influencing oil and gas reservoir single well yield and medium

Abstract

The invention provides a main control factor analysis method and system influencing oil and gas reservoir single well yield and a medium, and relates to the technical field of oil yield prediction, and the method specifically comprises the steps: collecting the oil reservoir single well yield and influence factors; processing the yield and each influence factor, calculating a Pearson's correlation coefficient, and determining a main control factor; according to the yield of the ith single well and the initial value of the yield of the ith single well, the sensitivity coefficient of the bth main control factor of the m single wells is obtained; and combining the Pearson's correlation coefficient with the sensitivity coefficient to generate a comprehensive evaluation coefficient, and evaluating the influence of each main control factor on the single well yield. According to the method, the influence degree of each factor on the yield can be quantified, the main control factor of the oil and gas reservoir single well yield can be determined, the comprehensive influence of each main control factor on the single well yield can be comprehensively reflected through the comprehensive evaluation coefficient, related factors can be identified, and the factor is prevented from generating significant influence on the yield under specific conditions.

Description

Technical Field

[0001] The present invention relates to the technical field of oil production prediction, and specifically provides a method, system and medium for analyzing the main controlling factors affecting the single-well production of oil and gas reservoirs. Background Art

[0002] With the progress of oil exploitation in China, most oil reservoirs have entered the middle and late stages of oilfield development, and the reservoirs are characterized by high water production and low oil production. Therefore, in order to optimize oilfield production strategies, cost control, and risk assessment and management, accurately determining the main controlling factors of the single-well production of oil and gas reservoirs has important theoretical and practical significance. Especially in the modern oil industry, it is directly related to the economic benefits of oilfields, production layout, rational utilization of resources, and technological progress. The rational development and utilization of oil reservoirs is not only necessary for China's economy, but also of great significance for ensuring China's energy security, promoting scientific and technological progress, and sustainable economic development.

[0003] In the prior art, a method, system, device and storage medium for analyzing the main controlling factors of oil well productivity, with the publication number of CN114021922A, includes the following steps: respectively cleaning the production dynamic factors and static geological factors in the obtained oil well data; using the method of controlling variables to independently analyze the cleaned production dynamic and static geological data, respectively designing their application methods, and using machine learning algorithms to carry out the ranking of the main controlling factors of oil well productivity, so as to obtain the importance ranking of each production dynamic factor and static geological factor. By efficiently cleaning the production dynamic and static geological data and adopting a data usage method suitable for the characteristics of production dynamic and static geological data, this method can improve the applicability and accuracy of machine learning algorithms in the research field of the main controlling factors of oil well productivity.

[0004] However, there are still the following deficiencies. From the above statements, although the prior art mentions ranking the influencing factors, it does not provide a specific quantitative analysis method. For example, it does not use statistical methods to quantify the contribution degree of different factors to the oil well production, and there is also a lack of sensitivity analysis of the influencing factors in the analysis process, resulting in significant impacts of the influencing factors on the oil well production in specific situations.

[0005] The above information disclosed in the background art section is only used to strengthen the understanding of the background of the present disclosure, so it may include information that does not constitute the prior art known to those of ordinary skill in the art. Summary of the Invention

[0006] The purpose of the present invention is to provide a method, system and medium for analyzing the main controlling factors affecting the single-well production of oil and gas reservoirs, so as to solve the problems raised in the above background art.

[0007] To achieve the above purpose, the present invention provides the following technical solutions:

[0008] A method for analyzing the main controlling factors affecting the single - well production of oil and gas reservoirs, the specific steps include:

[0009] S1. Collect the time - series data of the single - well production of oil and gas reservoirs and the time - series data of production - influencing factors for m single wells within the t - time period before the current moment. The production - influencing factors include reservoir permeability, reservoir porosity, original oil - saturation, original formation pressure, original formation temperature, effective injection volume, crude oil viscosity, effective reservoir thickness, and well depth;

[0010] S2. Normalize the production of m single wells in the oil reservoir and each influencing factor, and calculate the Pearson correlation coefficient between the single - well production of the oil and gas reservoir and each influencing factor through the Pearson correlation coefficient formula. Compare the magnitudes of the Pearson correlation coefficients corresponding to each influencing factor, and determine that the main controlling factors of the single - well production of the oil and gas reservoir are effective injection volume, reservoir permeability, original oil - saturation, effective reservoir thickness, and crude oil viscosity;

[0011] S3. According to the production of the i - th single well at the current moment and the initial value of the production of the i - th single well, obtain the change in the production of the i - th single well. According to the change in the production of the i - th single well, the current value of the b - th main controlling factor in the i - th single well at the current moment, and the initial value of the b - th main controlling factor in the i - th single well, obtain the sensitivity coefficient of the b - th main controlling factor of m single wells;

[0012] S4. Process the Pearson correlation coefficient and the corresponding sensitivity coefficient of the b - th main controlling factor of m single wells to generate a comprehensive evaluation coefficient. According to the comprehensive evaluation coefficient, evaluate the magnitude relationship of the influence of each main controlling factor on the single - well production.

[0013] Furthermore, normalize the production of the single well in the oil reservoir and each influencing factor, and calculate the Pearson correlation coefficient between the single - well production of the oil and gas reservoir and each influencing factor through the Pearson correlation coefficient formula. The formula is as follows:

[0014]

[0015] Among them, is the normalized data of the a - th influencing factor in the i - th single well at the j - th collection moment. j is the index of the collection moment within the t - time period before the current moment, j = {1, 2, …, n}, n is the total number of collection moments within the t - time period before the current moment, i is the index of the single well, i = {1, 2, …, m}, a is the index of the influencing factor, a ∈ {1, 2, …, 9}, corresponding to reservoir permeability, reservoir porosity, original oil - saturation, original formation pressure, original formation temperature, effective injection volume, crude oil viscosity, effective reservoir thickness, and well depth respectively, is the original data of the a - th influencing factor in the i - th single well at the j - th collection moment, is the minimum value of the original data of the ath influencing factor in m single wells, X amax is the maximum value of the original data of the ath influencing factor in a single well, Y i, (j) is the normalized data of the single well production of the i-th well at the j-th acquisition time, Y i (j) is the original data of single well production of the i-th well at the j-th acquisition time, Y min is the minimum value of the original data of single well production of m single wells, Y max is the maximum value of the original data of single well production of m single wells, is the normalized mean value of the ath influencing factor in m single wells, is the normalized mean of the single-well production of m single wells, r a is the Pearson correlation coefficient between the ath influencing factor and the single well production of oil and gas reservoirs, r a ∈{r1,r2,…,r9}, r1, r2, r3, r4, r5, r6, r7, r8, r9 are the Pearson correlation coefficients corresponding to reservoir permeability, reservoir porosity, original oil saturation, original formation pressure, original formation temperature, effective water injection volume, crude oil viscosity, effective reservoir thickness, and well depth, respectively.

[0016] Furthermore, the Pearson correlation coefficients of the single-well production of the oil and gas reservoirs and the various influencing factors are compared to obtain the main controlling factors of the single-well production of the oil and gas reservoirs. The specific process is as follows:

[0017] After calculation, the Pearson correlation coefficients corresponding to reservoir permeability, reservoir porosity, original oil saturation, original formation pressure, original formation temperature, effective water injection volume, crude oil viscosity, effective reservoir thickness, and well depth were obtained. The Pearson correlation coefficients corresponding to each influencing factor were sorted from large to small according to their absolute values, and the top 5 were selected. The main controlling factors of the single well production of the oil and gas reservoir are effective water injection volume, reservoir permeability, original oil saturation, effective reservoir thickness, and crude oil viscosity.

[0018] Furthermore, based on the current production of the ith well and the initial value of the production of the ith well, the change in the production of the ith well is obtained. Based on the change in the production of the ith well, the current value of the bth main controlling factor in the ith well at the current moment and the initial value of the bth main controlling factor in the ith well, the sensitivity coefficient of the bth main controlling factor of the m wells is obtained, according to the following formula:

[0019] ΔY i (T)=Y i (T)-Y i (1)

[0020]

[0021] Among them, S b is the sensitivity coefficient of the b-th main control factor of the m single wells, b is the index of the main control factor, and b ∈ [1, 5], S b ∈ {S1, S2, …, S5}, ΔY i (T) is the change in the production of the i-th single well, Y i (T) is the production of the i-th single well at the current moment, Y i (1) is the initial value of the production of the i-th single well, is the current value of the b-th main control factor in the i-th single well at the current moment, is the initial value of the b-th main control factor in the i-th single well.

[0022] Furthermore, the Pearson correlation coefficient and the corresponding sensitivity coefficient of the b-th main control factor of the m single wells are processed to generate a comprehensive evaluation coefficient. The formula is as follows:

[0023]

[0024] Among them, E b is the comprehensive evaluation coefficient of the b-th main control factor, R b ∈ {R1, R2, …, R5}, E b ∈ {E1, E2, …, E5}, E1, E2, E3, E4, and E5 are the comprehensive evaluation coefficients of the affected injection volume, reservoir permeability, original oil saturation, effective reservoir thickness, and crude oil viscosity respectively. ω1 is the weight coefficient of the sensitivity coefficient of each main control factor, ω2 is the weight coefficient of the Pearson correlation coefficient of each main control factor, 0 < ω1 < ω2 < 1, and ω1 + ω2 = 1.

[0025] Furthermore, according to the comprehensive evaluation coefficient, the magnitude relationship of the influence of each main control factor on the single well production is evaluated. The specific process is as follows:

[0026] Sort the comprehensive evaluation coefficients E1 of the affected injection volume, E2 of the reservoir permeability, E3 of the original oil saturation, E4 of the effective reservoir thickness, and E5 of the crude oil viscosity from large to small. The influence degree of each main control factor on the single well production decreases in turn along the sorting order of the corresponding comprehensive evaluation coefficients.

[0027] To achieve the above object, the present invention also provides the following technical solutions:

[0028] A main control factor analysis system for affecting the single well production of an oil and gas reservoir. The system is used to execute any one of the above-mentioned main control factor analysis methods for affecting the single well production of an oil and gas reservoir, including:

[0029] A data acquisition module, which is used to acquire the time-series data of the single-well production of the oil and gas reservoir of m single wells and the time-series data of the production influencing factors within a time period t before the current moment. The production influencing factors include reservoir permeability, reservoir porosity, original oil saturation, original formation pressure, original formation temperature, affected injection volume, crude oil viscosity, effective reservoir thickness, and well depth.

[0030] A data processing module, which is used to perform normalization processing on the production and various influencing factors of m single wells in the oil reservoir, and calculate the Pearson correlation coefficient between the single-well production of the oil and gas reservoir and various influencing factors through the Pearson correlation coefficient formula, compare the magnitudes of the Pearson correlation coefficients corresponding to various influencing factors, and determine that the main controlling factors for the single-well production of the oil and gas reservoir are the affected injection volume, reservoir permeability, original oil saturation, effective reservoir thickness, and crude oil viscosity.

[0031] A data analysis module, which is used to obtain the change in the production of the i-th single well according to the production of the i-th single well at the current moment and the initial value of the production of the i-th single well, and obtain the sensitivity coefficient of the b-th main controlling factor of m single wells according to the change in the production of the i-th single well, the current value of the b-th main controlling factor in the i-th single well at the current moment, and the initial value of the b-th main controlling factor in the i-th single well.

[0032] A data evaluation module, which is used to perform data processing on the Pearson correlation coefficient and the corresponding sensitivity coefficient of the b-th main controlling factor of m single wells to generate a comprehensive evaluation coefficient, and evaluate the magnitude relationship of the influence of each main controlling factor on the single-well production according to the comprehensive evaluation coefficient.

[0033] A medium for storing a computer program, where the computer program, when executed by a processor, implements any one of the above-mentioned methods for analyzing the main controlling factors affecting the single-well production of an oil and gas reservoir.

[0034] Compared with the prior art, the beneficial effects of the present invention are as follows:

[0035] By introducing the calculation of the Pearson correlation coefficient and calculating the correlation coefficient between the production and various influencing factors, the present invention can quantify the influence degree of each factor on the production, thereby determining the main controlling factors for the single-well production of the oil and gas reservoir; by combining the Pearson correlation coefficient with the mean value of the sensitivity coefficient to generate a comprehensive evaluation coefficient, the present invention can comprehensively reflect the comprehensive influence of each main controlling factor on the single-well production, identify relevant factors, and avoid the significant influence of this factor on the production under specific circumstances. Description of the Drawings

[0036] Figure 1 It is a schematic diagram of the overall method flow of the present invention;

[0037] Figure 2 It is a block diagram of the module composition of the present invention;

[0038] Figure 3 This is a heat map of the correlation relationship between the single-well production of the oil and gas reservoir of the present invention and various influencing factors. Specific Embodiments

[0039] To make the objectives, technical solutions, and advantages of the present invention clearer and more understandable, the present invention will be further described in detail below in conjunction with specific embodiments.

[0040] It should be noted that unless otherwise defined, the technical terms or scientific terms used in the present invention should have the ordinary meanings understood by those with ordinary skills in the field to which the present invention belongs. The "first", "second", and similar terms used in the present invention do not indicate any order, quantity, or importance, but are only used to distinguish different components. The terms such as "including" or "comprising" mean that the elements or objects appearing before this word cover the elements or objects listed after this word and their equivalents, without excluding other elements or objects. The terms such as "connected" or "linked" are not limited to physical or mechanical connections, but may include electrical connections, whether direct or indirect. The terms such as "upper", "lower", "left", and "right" are only used to represent relative position relationships. When the absolute position of the object being described changes, the relative position relationship may also change accordingly.

[0041] Example 1:

[0042] Please refer to Figure 1 , the present invention provides a technical solution:

[0043] A method for analyzing the main control factors affecting the single-well production of an oil and gas reservoir, the specific steps include:

[0044] S1. Collect the time-series data of the single-well production of the oil and gas reservoir and the time-series data of the production influencing factors of m single wells within the t time period before the current moment. The production influencing factors include reservoir permeability, reservoir porosity, original oil saturation, original formation pressure, original formation temperature, affected injection volume, crude oil viscosity, effective reservoir thickness, and well depth;

[0045] S2. Normalize the production of m single wells in the oil reservoir and each influencing factor, and calculate the Pearson correlation coefficient between the single-well production of the oil and gas reservoir and each influencing factor through the Pearson correlation coefficient formula. Compare the magnitudes of the Pearson correlation coefficients corresponding to each influencing factor, and determine that the main control factors for the single-well production of the oil and gas reservoir are the affected injection volume, reservoir permeability, original oil saturation, effective reservoir thickness, and crude oil viscosity;

[0046] S3. Obtain the change in the production of the i-th single well according to the production of the i-th single well at the current moment and the initial value of the production of the i-th single well. According to the change in the production of the i-th single well, the current value of the b-th main control factor in the i-th single well and the initial value of the b-th main control factor in the i-th single well, obtain the sensitivity coefficient of the b-th main control factor of m single wells.

[0047] S4. Process the Pearson correlation coefficient and the corresponding sensitivity coefficient of the b-th main control factor of m single wells to generate a comprehensive evaluation coefficient. According to the comprehensive evaluation coefficient, evaluate the magnitude relationship of the influence of each main control factor on the production of a single well.

[0048] Based on the above embodiments, the equipment and methods for collecting the oil and gas reservoir single well production, reservoir permeability, reservoir porosity, original oil saturation, original formation pressure, original formation temperature, affected injection volume, crude oil viscosity, effective reservoir thickness, and well depth in the research area are as follows:

[0049] Measure the oil production of oil wells. Common ones are electromagnetic flowmeters or ultrasonic flowmeters, and regularly record the production of oil and gas reservoir single wells, usually on a daily, weekly, or monthly basis;

[0050] Use a liquid permeability meter to calculate the reservoir permeability by monitoring the flow rate of the fluid through the rock sample by applying a known pressure difference;

[0051] Obtain the reservoir porosity by taking core samples through a vacuum pump or a liquid saturation device and conducting laboratory analysis;

[0052] Use a flowmeter to measure the amount of fluid injected into the core and the amount of fluid flowing out of the core to calculate the original oil saturation;

[0053] Use a pressure gauge to obtain the original formation pressure through well test analysis;

[0054] Install a temperature sensor downhole to monitor the original formation temperature in real time;

[0055] Use an injection water flowmeter to calculate the affected injection volume by measuring the cumulative flow rate within a time period;

[0056] Use a viscometer to measure the crude oil viscosity;

[0057] Take core samples for direct measurement of the effective reservoir thickness;

[0058] Obtain the well depth according to the depth data recorded during the drilling process.

[0059] Based on the above embodiments, normalize the production of the oil reservoir single well and each influencing factor, and calculate the Pearson correlation coefficient between the production of the oil and gas reservoir single well and each influencing factor through the Pearson correlation coefficient formula. The formula is as follows:

[0060]

[0061] Among them, is the normalized data of the ath influencing factor in the ith single well at the jth acquisition time. j is the index of the acquisition time within the t time period before the current time, j = {1, 2, …, n}, where n is the total number of acquisition times within the t time period before the current time. i is the index of the single well, i = {1, 2, …, m}, and a is the index of the influencing factor, a ∈ {1, 2, …, 9}, corresponding to reservoir permeability, reservoir porosity, original oil saturation, original formation pressure, original formation temperature, affected injection volume, crude oil viscosity, effective reservoir thickness, and well depth respectively. is the original data of the ath influencing factor in the ith single well at the jth acquisition time. is the minimum value of the original data of the ath influencing factor among m single wells. is the maximum value of the original data of the ath influencing factor among single wells, Y i, Y(j) is the normalized data of the single well production of the ith single well at the jth acquisition time. i Y(j) is the original data of the single well production of the ith single well at the jth acquisition time. min is the minimum value of the original data of the single well production among m single wells, Y max is the maximum value of the original data of the single well production among m single wells. is the mean value of the normalized data of the ath influencing factor among m single wells. is the mean value of the normalized data of the single well production among m single wells, r a is the Pearson correlation coefficient between the ath influencing factor and the single well production of the oil and gas reservoir, r a ∈ {r1, r2, …, r9}, where r1, r2, r3, r4, r5, r6, r7, r8, r9 are the Pearson correlation coefficients corresponding to reservoir permeability, reservoir porosity, original oil saturation, original formation pressure, original formation temperature, affected injection volume, crude oil viscosity, effective reservoir thickness, and well depth respectively.

[0062] Based on the above embodiments, compare the magnitudes of the Pearson correlation coefficients between the single well production of the oil and gas reservoir and each influencing factor. The specific process is as follows:

[0063] As Figure 3 shown, the Pearson correlation coefficients between each influencing factor and the single well production of the oil and gas reservoir are as follows:

[0064] The mean Pearson correlation coefficients of reservoir permeability, reservoir porosity, initial oil saturation, initial formation pressure, initial formation temperature, effective water injection volume, crude oil viscosity, effective reservoir thickness, well depth, and single-well production of the oil and gas reservoir are 0.81, 0.27, 0.69, 0.14, -0.17, 0.7, -0.8, 0.77, and 0.19 in sequence. The absolute values of the mean Pearson correlation coefficients of each influencing factor are sorted in descending order, and the top 5 are selected. After screening, the main controlling factors of the single-well production of the oil and gas reservoir are effective water injection volume, reservoir permeability, initial oil saturation, effective reservoir thickness, and crude oil viscosity.

[0065] Based on the above embodiments, according to the current single-well production of the i-th well and the initial value of the single-well production of the i-th well, the change in the single-well production of the i-th well is obtained. According to the change in the single-well production of the i-th well, the current value of the b-th main controlling factor in the i-th well at the current moment and the initial value of the b-th main controlling factor in the i-th well, the sensitivity coefficient of the b-th main controlling factor of m wells is obtained. The formula is as follows:

[0066] ΔY i (T)=Y i (T)-Y i (1)

[0067]

[0068] Among them, S b is the sensitivity coefficient of the b-th main controlling factor of m wells. b is the index of the main controlling factor, and b ∈ [1, 5]. S b ∈{S1, S2, …, S5}. S1, S2, S3, S4, and S5 are the sensitivity coefficients of effective water injection volume, reservoir permeability, initial oil saturation, effective reservoir thickness, and crude oil viscosity respectively. ΔY i (T) is the change in the single-well production of the i-th well. Y i (T) is the current single-well production of the i-th well. Y i (1) is the initial value of the single-well production of the i-th well. is the current value of the b-th main controlling factor in the i-th well at the current moment. is the initial value of the b-th main controlling factor in the i-th well. The initial value of the single-well production and the initial value of the main controlling factor are the single-well production value and the main controlling factor value collected for the first time within the previous t time period before the current moment respectively.

[0069] The reason for using the above functional expression for the sensitivity coefficient of the main controlling factor is as follows:

[0070] It is the ratio of the change amount to the initial production, representing the proportion of the change in the production of the i-th single well relative to its initial production. The larger its value, the sensitivity coefficient S b is larger, indicating that the influence of the main control factor is increasing. represents the relative change of the b-th main control factor, that is, the ratio of the current value to the initial value. The larger its value, the sensitivity coefficient S b is smaller because the drastic change of the main control factor will inhibit the sensitivity of the production change; and the calculation of the sensitivity coefficient exactly considers the relationship between the production change and the change of the main control factor. When the value is larger, it means that there is a significant change in the production relative to the initial production. If the change of the main control factor is small, the sensitivity coefficient S b is larger;

[0071] represents the relationship between the change in the production of a single well and the change in the main control factor when the main control factor changes. If this value is positive, it means that the change in the main control factor and the production change are in the same direction (that is, an increase in the main control factor leads to an increase in production, or a decrease in the main control factor leads to a decrease in production); if it is negative, it means it is an inverse relationship.

[0072] Therefore, it can quantify the influence of the main control factor on the production change, that is, the sensitivity coefficient S of the main control factor b is used to quantify the sensitivity of different main control factors to production. Based on the above embodiments, the Pearson correlation coefficient and the corresponding sensitivity coefficient of the b-th main control factor of m single wells are processed to generate a comprehensive evaluation coefficient. The formula is as follows:

[0073]

[0074] where, E b is the comprehensive evaluation coefficient of the b-th main control factor, R b ∈{R1, R2, …, R5}, R1, R2, R3, R4, R5 are the sensitivity coefficients of the affected injection volume, reservoir permeability, original oil saturation, effective reservoir thickness and crude oil viscosity respectively, E b ={E1, E2, …, E5}, E1, E2, E3, E4, E5 are the comprehensive evaluation coefficients of the affected injection volume, reservoir permeability, original oil saturation, effective reservoir thickness and crude oil viscosity respectively, ω1 is the weight coefficient of the sensitivity coefficient of each main control factor, and ω2 is the weight coefficient of the Pearson correlation coefficient of each main control factor.

[0075] The reason for adopting the above functional form to express the relationship between the Pearson correlation coefficient, sensitivity coefficient and comprehensive evaluation coefficient of the b-th main control factor of m single wells is as follows:

[0076] First, ω1 is a weight coefficient, indicating the importance of S b in production prediction. By multiplying with S b , it can adjust the influence degree of the sensitivity factor on the comprehensive evaluation coefficient. ω2 is another weight coefficient, indicating the importance of r b in the prediction. After multiplying with r b , it can measure the direct impact of the Pearson correlation coefficient on the production.

[0077] Second, the interaction term S b ·r b represents the interaction between the sensitivity coefficient and the correlation coefficient. This setting allows the model to capture the non - linear relationship or mutual influence between the two factors. For example, a certain sensitivity may have a greater impact on production under high permeability conditions and a smaller impact under low permeability conditions.

[0078] Third, each value of E b is between (0, 1). The closer the value is to 1, the greater the positive impact of the factor on the production of a single well. The closer the value is to 0, the smaller the impact of the factor on the production of a single well.

[0079] Therefore, using the above - mentioned functional form can not only effectively capture the complex relationships of various influencing factors, but also has good interpretability and applicability.

[0080] Because the Pearson correlation coefficients between the main control factors are generally high, which indicates that there is a significant linear relationship between these factors. This strong correlation directly affects the production performance of the reservoir, resulting in a relatively large weight coefficient ω2; the Pearson correlation coefficient can more effectively reflect the relationship between the main control factors, and this relationship has a more direct and significant impact on the reservoir production. In contrast, the influence of the sensitivity coefficient is smaller or relatively stable, so a lower weight ω1 is assigned in the model.

[0081] Therefore, the weight coefficient of the Pearson correlation coefficient of each main control factor is set to be greater than the weight coefficient of the sensitivity coefficient of each main control factor, that is, 0 < ω1 < ω2 < 1. Without the influence of other factors, ω1 + ω2 = 1 is set.

[0082] Based on the above - mentioned embodiments, according to the comprehensive evaluation coefficient, the magnitude relationship of the influence of each main control factor on the production of a single well is evaluated. The specific process is as follows:

[0083] Sort the comprehensive evaluation coefficients E1 of the affected injection volume, E2 of the reservoir permeability, E3 of the original oil saturation, E4 of the effective reservoir thickness, and E5 of the crude oil viscosity from large to small. The influence degree of each main control factor on the production of a single well decreases in turn along the sorting order of the corresponding comprehensive evaluation coefficients.

[0084] Please refer to Figure 2 , the present invention also provides a technical solution:

[0085] A main control factor analysis system for affecting the single - well production of an oil and gas reservoir, the system is used to execute any one of the above - mentioned main control factor analysis methods for affecting the single - well production of an oil and gas reservoir, including:

[0086] A data acquisition module, which is used to acquire the time - series data of the single - well production of an oil and gas reservoir and the time - series data of production - influencing factors of m single wells within a t - time period before the current moment. The production - influencing factors include reservoir permeability, reservoir porosity, original oil - in - place saturation, original formation pressure, original formation temperature, effective injection volume, crude oil viscosity, effective reservoir thickness, and well depth;

[0087] A data processing module, which is used to perform normalization processing on the production and various influencing factors of m oil reservoir single wells, and calculate the Pearson correlation coefficients between the single - well production of the oil and gas reservoir and various influencing factors through the Pearson correlation coefficient formula, compare the magnitudes of the Pearson correlation coefficients corresponding to various influencing factors, and determine that the main control factors for the single - well production of the oil and gas reservoir are effective injection volume, reservoir permeability, original oil - in - place saturation, effective reservoir thickness, and crude oil viscosity;

[0088] A data analysis module, which is used to obtain the change amount of the production of the i - th single well according to the production of the i - th single well at the current moment and the initial value of the production of the i - th single well, and obtain the sensitivity coefficient of the b - th main control factor of m single wells according to the change amount of the production of the i - th single well, the current value of the b - th main control factor in the i - th single well at the current moment, and the initial value of the b - th main control factor in the i - th single well;

[0089] A data evaluation module, which is used to perform data processing on the Pearson correlation coefficients and the corresponding sensitivity coefficients of the b - th main control factor of m single wells to generate a comprehensive evaluation coefficient, and evaluate the magnitude relationship of the influence of each main control factor on the single - well production according to the comprehensive evaluation coefficient.

[0090] A medium for storing a computer program, which when executed by a processor implements any one of the above - mentioned main control factor analysis methods for affecting the single - well production of an oil and gas reservoir.

[0091] The above formulas are all dimensionless and take their numerical values for calculation. The formula is obtained by software simulation of a large amount of collected data to get a formula closest to the actual situation. The preset parameters in the formula are set by those skilled in the art according to the actual situation.

[0092] The above embodiments can be implemented in whole or in part by software, hardware, firmware, or any combination thereof. When implemented using software, the above embodiments can be implemented in whole or in part in the form of a computer program product. Those skilled in the art will realize that the units and algorithm steps of the examples described in connection with the embodiments disclosed herein can be implemented by electronic hardware, or a combination of computer software and electronic hardware. Whether these functions are executed by hardware or software methods depends on the specific application and design constraints of the technical solution.

[0093] The units described as separate components may or may not be physically separated, and the components shown as units may or may not be physical units. They may be located in one place or distributed over multiple network units. Some or all of the units can be selected according to actual needs to achieve the purpose of the solution of this embodiment.

[0094] The above is only the specific implementation manner of this application, but the protection scope of this application is not limited thereto. Any person skilled in the art can easily think of changes or substitutions within the technical scope disclosed in this application, and all should be covered by the protection scope of this application.

[0095] The units described as separate components may or may not be physically separated, and the components shown as units may or may not be physical units. They may be located in one place or distributed over multiple network units. Some or all of the units can be selected according to actual needs to achieve the purpose of the solution of this embodiment.

[0096] The above is only the specific implementation manner of this application, but the protection scope of this application is not limited thereto. Any person skilled in the art can easily think of changes or substitutions within the technical scope disclosed in this application, and all should be covered by the protection scope of this application.

Claims

1. A method for analyzing the main controlling factors affecting the single-well production of an oil and gas reservoir, characterized in that, The specific steps include: S1. Collect the time-series data of the oil and gas reservoir single-well production and the time-series data of production influencing factors of m single wells within the t time period before the current moment. The production influencing factors include reservoir permeability, reservoir porosity, original oil saturation, original formation pressure, original formation temperature, affected injection volume, crude oil viscosity, effective reservoir thickness, and well depth; S2. Normalize the production and each influencing factor of the m oil reservoir single wells, and calculate the Pearson correlation coefficient between the oil and gas reservoir single-well production and each influencing factor through the Pearson correlation coefficient formula. Compare the magnitudes of the Pearson correlation coefficients corresponding to each influencing factor to determine that the main controlling factors of the oil and gas reservoir single-well production are the affected injection volume, reservoir permeability, original oil saturation, effective reservoir thickness, and crude oil viscosity; S3. Obtain the change in the production of the i-th single well according to the production of the i-th single well at the current moment and the initial value of the production of the i-th single well. Obtain the sensitivity coefficient of the b-th main controlling factor of the m single wells according to the change in the production of the i-th single well, the current value of the b-th main controlling factor in the i-th single well at the current moment, and the initial value of the b-th main controlling factor in the i-th single well; S4. Process the Pearson correlation coefficient and the corresponding sensitivity coefficient of the b-th main controlling factor of the m single wells to generate a comprehensive evaluation coefficient. Evaluate the magnitude relationship of the influence of each main controlling factor on the single-well production according to the comprehensive evaluation coefficient.

2. The analysis method for the main controlling factors affecting the single-well production of an oil and gas reservoir according to claim 1, wherein: Normalize the production and each influencing factor of the oil reservoir single well, and calculate the Pearson correlation coefficient between the oil and gas reservoir single-well production and each influencing factor through the Pearson correlation coefficient formula. The formula is as follows: Among them, is the normalized data of the ath influencing factor in the ith single well at the jth acquisition time. j is the index of the acquisition time within the t time period before the current time, j = {1, 2, …, n}, where n is the total number of acquisition times within the t time period before the current time. i is the index of the single well, i = {1, 2, …, m}, and a is the index of the influencing factor, a ∈ {1, 2, …, 9}, corresponding to reservoir permeability, reservoir porosity, original oil saturation, original formation pressure, original formation temperature, affected injection volume, crude oil viscosity, effective reservoir thickness, and well depth respectively. is the original data of the ath influencing factor in the ith single well at the jth acquisition time. is the minimum value of the original data of the ath influencing factor in m single wells. is the maximum value of the original data of the ath influencing factor in m single wells, Y i, Y(j) is the normalized data of the single well production of the ith single well at the jth acquisition time. i Y(j) is the original data of the single well production of the ith single well at the jth acquisition time. min is the minimum value of the original data of the single well production of m single wells, Y max is the maximum value of the original data of the single well production of m single wells. is the mean value of the normalized data of the ath influencing factor in m single wells. is the mean value of the normalized data of the single well production of m single wells, r a is the Pearson correlation coefficient between the ath influencing factor and the single well production of the oil and gas reservoir, r a ∈ {r i , r2, …, r9}, and r1, r2, r3, r4, r5, r6, r7, r8, r9 are the Pearson correlation coefficients corresponding to reservoir permeability, reservoir porosity, original oil saturation, original formation pressure, original formation temperature, affected injection volume, crude oil viscosity, effective reservoir thickness, and well depth respectively.

3. The main controlling factor analysis method for the single well production of an oil and gas reservoir according to claim 2, characterized in that: Compare the magnitudes of the Pearson correlation coefficients between the oil and gas reservoir single-well production and each influencing factor to obtain the main controlling factors of the oil and gas reservoir single-well production. The specific process is as follows: After calculation, obtain the Pearson correlation coefficients corresponding to reservoir permeability, reservoir porosity, original oil saturation, original formation pressure, original formation temperature, affected injection volume, crude oil viscosity, effective reservoir thickness, and well depth. Sort the Pearson correlation coefficients corresponding to each influencing factor from largest to smallest according to the absolute value, and select the top 5. Then the main controlling factors of the oil and gas reservoir single-well production are the affected injection volume, reservoir permeability, original oil saturation, effective reservoir thickness, and crude oil viscosity.

4. The analysis method for the main controlling factors affecting the single-well production of oil and gas reservoirs according to claim 3, wherein: Obtain the change in the production of the i-th single well according to the production of the i-th single well at the current moment and the initial value of the production of the i-th single well. Obtain the sensitivity coefficient of the b-th main controlling factor of the m single wells according to the change in the production of the i-th single well, the current value of the b-th main controlling factor in the i-th single well at the current moment, and the initial value of the b-th main controlling factor in the i-th single well. The formula is as follows: ΔY i (T) = Y i (T) - Y i (1) Among them, S b is the sensitivity coefficient of the b-th main control factor of the m-th single well, where b is the index of the main control factor and b ∈ [1, 5], and S b ∈ {S1, S2, …, S5}, ΔY i (T) is the change in the production of the i-th single well, Y i (T) is the production of the i-th single well at the current moment, and Y i (1) is the initial value of the production of the i-th single well, is the current value of the b-th main control factor in the i-th single well at the current moment, is the initial value of the b-th main control factor in the i-th single well.

5. The main control factor analysis method for the single well production of oil and gas reservoirs according to claim 4, characterized in that: Process the Pearson correlation coefficient and the corresponding sensitivity coefficient of the b-th main controlling factor of the m single wells to generate a comprehensive evaluation coefficient. The formula is as follows: Among them, E b is the comprehensive evaluation coefficient of the b-th main control factor, R b ∈ {R1, R2, …, E5}, E b ∈ {E1, E2, …, R5}, where E1, E2, E3, E4, and E5 are the comprehensive evaluation coefficients of the effective injection volume, reservoir permeability, original oil saturation, effective reservoir thickness, and crude oil viscosity respectively. ω1 is the weight coefficient of the sensitivity coefficient of each main control factor, and ω2 is the weight coefficient of the Pearson correlation coefficient of each main control factor. 0 < ω1 < ω2 < 1, and ω1 + ω2 = 1.

6. The analysis method for the main controlling factors affecting the single-well production of an oil and gas reservoir according to claim 5, characterized in that: Evaluate the magnitude relationship of the influence of each main controlling factor on the single-well production according to the comprehensive evaluation coefficient. The specific process is as follows: Rank the comprehensive evaluation coefficient E1 of the effective injection volume, the comprehensive evaluation coefficient E2 of the reservoir permeability, the original oil saturation E3, the comprehensive evaluation coefficient E4 of the effective reservoir thickness, and the comprehensive evaluation coefficient E5 of the crude oil viscosity from largest to smallest. The influence degree of each main control factor on the single-well production decreases in turn along the sorting order of the corresponding comprehensive evaluation coefficient.

7. A main control factor analysis system for the single-well production of an oil and gas reservoir, the system being used to execute a main control factor analysis method for the single-well production of an oil and gas reservoir according to any one of claims 1-6, characterized in that: Including: A data acquisition module for acquiring the time-series data of the single-well production of the oil and gas reservoir and the time-series data of the production influencing factors of m single wells within a time period t before the current moment. The production influencing factors include reservoir permeability, reservoir porosity, original oil saturation, original formation pressure, original formation temperature, effective injection volume, crude oil viscosity, effective reservoir thickness, and well depth. A data processing module for normalizing the production and each influencing factor of m single wells in the oil reservoir, calculating the Pearson correlation coefficient between the single-well production of the oil and gas reservoir and each influencing factor through the Pearson correlation coefficient formula, comparing the magnitudes of the Pearson correlation coefficients corresponding to each influencing factor, and determining that the main control factors for the single-well production of the oil and gas reservoir are the effective injection volume, reservoir permeability, original oil saturation, effective reservoir thickness, and crude oil viscosity. A data analysis module for obtaining the change in the production of the i-th single well according to the production of the i-th single well at the current moment and the initial value of the production of the i-th single well, and obtaining the sensitivity coefficient of the b-th main control factor of m single wells according to the change in the production of the i-th single well, the current value of the b-th main control factor in the i-th single well at the current moment, and the initial value of the b-th main control factor in the i-th single well. A data evaluation module for processing the Pearson correlation coefficient and the corresponding sensitivity coefficient of the b-th main control factor of m single wells to generate a comprehensive evaluation coefficient, and evaluating the magnitude relationship of the influence of each main control factor on the single-well production according to the comprehensive evaluation coefficient.

8. A medium, characterized in that: For saving a computer program, which when executed by a processor implements the method for analyzing the main control factors affecting the single-well production of an oil and gas reservoir according to any one of claims 1-6.

Images