Prediction Method, Device, Equipment and Storage Medium for Annual Production Capacity after Fracturing of Horizontal Wells

Abstract

The present invention relates to the technical field of logging evaluation of complex lithology oil and gas reservoirs, and is a method, device, equipment and storage medium for predicting the annual production capacity after horizontal well fracturing. The former includes selecting a horizontal well, determining the single-well production capacity quality of the horizontal well and the sensitive fracturing parameters of the annual production capacity; using the single-well production capacity quality of the selected horizontal well and the sensitive fracturing parameters of the annual production capacity to construct a prediction model for the annual production capacity of the horizontal well; and predicting the annual production capacity of the horizontal well to be predicted according to the prediction model for the annual production capacity of the horizontal well. The present invention comprehensively considers the reservoir's own characteristic indicators and the fracturing construction process, constructs a production capacity prediction model, so that the constructed production capacity prediction model considers more comprehensive production capacity influencing factors compared with the production capacity prediction models obtained by existing conventional methods, avoids the problem that the production capacity after fracturing reconstruction fails to reach the expected effect in actual production, and makes the production capacity prediction model of the embodiments of the present invention have strong adaptability and greater generality.

Description

Technical Field

[0001] The present invention relates to the technical field of logging evaluation of complex lithology oil and gas reservoirs, and is a method, device, equipment and storage medium for predicting the annual production capacity after horizontal well fracturing. Background Art

[0002] Complex lithology reservoirs generally have characteristics such as ultra-low porosity and permeability, and complex pore structures. More factors need to be considered in the evaluation of oil-bearing properties. Production capacity prediction is an important link in the evaluation of reservoir oil-bearing properties, which is directly related to the increase of oil reserves and production in the oilfield, affects the selection of exploration target areas and the formulation of development plans. Accurately predicting the reservoir production capacity is of great significance for cost reduction and efficient development of the oilfield.

[0003] Before the production of horizontal wells in lithologically tight formations, large-scale volume fracturing is required, which makes the factors affecting the production capacity of the oil reservoir more complex than those of conventional oil reservoirs, and the factors affecting the production capacity of horizontal wells are diversified. At present, the main methods for production capacity analysis and prediction in China are empirical methods, analytical methods, numerical simulation methods, etc. Most of these methods follow the production capacity prediction ideas of conventional oil and gas reservoirs, and do not consider the comprehensive influence of reservoir own characteristic indexes and fracturing construction technology and other factors. The influence of fracturing technology and fracturing scale is not studied deeply, resulting in the production capacity after fracturing transformation in actual production not reaching the expected effect, and the difference between the production capacity of a single well in actual production and the predicted production capacity is large. Therefore, when the reservoir own characteristic indexes and fracturing construction technology and other factors are not clear in the existing methods, the production capacity prediction difference is large, which causes uncertainty for the efficient development of complex lithology reservoirs, so the applicable range is narrow, the generality is not strong, and the prediction is inaccurate. Summary of the Invention

[0004] The present invention provides a method, device, equipment and storage medium for predicting the annual production capacity after horizontal well fracturing, which overcomes the above-mentioned deficiencies of the prior art and can effectively solve the problem that the existing production capacity prediction method does not combine the reservoir own characteristic indexes and fracturing construction technology factors, and is easy to cause a large difference between the predicted single-well production capacity and the actual single-well production capacity.

[0005] One of the technical solutions of the present invention is achieved by the following measures: A method for predicting the annual production capacity after horizontal well fracturing, comprising:

[0006] Select a horizontal well, and determine the single-well production capacity quality and sensitive fracturing parameters of the annual production capacity of the horizontal well, wherein the horizontal well is in the same series as the horizontal well to be predicted and adopts a segmented and clustered fracturing process; the sensitive fracturing parameters include cluster liquid volume, cluster proppant dosage and cluster construction displacement;

[0007] Utilize the single-well production capacity quality and sensitive fracturing parameters of the annual production capacity of the selected horizontal well to construct a prediction model for the annual production capacity of the horizontal well;

[0008] According to the prediction model of the annual production capacity of horizontal wells, the annual production capacity of the horizontal well to be predicted is predicted.

[0009] The following is a further optimization and / or improvement of the above-mentioned technical solution of the invention:

[0010] The above-mentioned method of constructing a prediction model for the annual production capacity of horizontal wells by using the single-well production capacity quality and sensitive fracturing parameters of the annual production capacity of the selected horizontal wells includes:

[0011] Normalize the single-well production capacity quality and sensitive fracturing parameters of the annual production capacity of the selected horizontal wells;

[0012] Use the normalized sensitive fracturing parameters and single-well production capacity quality to construct a prediction model for the annual production capacity of horizontal wells. The prediction model is as follows:

[0013] M yr = a*I phn + b*I ln + c*I sn + d*I rn + e

[0014] Wherein, M yr is the annual production capacity of the horizontal well; a, b, c, d, and e are constants; I phn is the normalized single-well production capacity quality; I ln , I sn , I rn are the liquid volume intensity, proppant intensity, and construction displacement intensity obtained after normalizing the sensitive fracturing parameters, respectively.

[0015] The above-mentioned method of selecting a horizontal well and determining the single-well production capacity quality and sensitive fracturing parameters of the annual production capacity of the horizontal well includes:

[0016] Select a well testing vertical well and determine the production capacity quality index and its lower limit value of the well testing vertical well, where the well testing vertical well is a well testing vertical well in the same formation as the horizontal well to be predicted and having the same fracturing process;

[0017] Select a horizontal well, determine the sensitive fracturing parameters of the annual production capacity of the horizontal well, and use the production capacity quality index and its lower limit value of the selected well testing vertical well to determine the single-well production capacity quality of the horizontal well, where the horizontal well is in the same formation as the selected well testing vertical well and adopts a segmented and clustered fracturing process; the sensitive fracturing parameters include cluster liquid volume, cluster proppant dosage, and cluster construction displacement.

[0018] The above-mentioned method of selecting a well testing vertical well and determining the production capacity quality index and its lower limit value of the well testing vertical well includes:

[0019] Select a well testing vertical well in the same formation as the horizontal well to be predicted and having the same fracturing process;

[0020] Determine the rice production index corresponding to the oil testing interval in combination with the following formula;

[0021]

[0022] where, I oil is the rice production index of the oil testing interval; m is the daily oil production obtained from oil testing; h is the thickness of the oil testing interval;

[0023] Obtain the sensitive reservoir characteristic parameters of the rice production index, where the sensitive reservoir characteristic parameters include movable oil porosity and brittleness index;

[0024] Utilize the sensitive reservoir characteristic parameters of the rice production index to obtain the productivity quality index of the vertical well and its lower limit value through the following formula;

[0025]

[0026] where, I p is the productivity quality index; a, b, c are constants; is the movable oil porosity; I b is the brittleness index.

[0027] The above-mentioned selection of horizontal wells, determination of the sensitive fracturing parameters of the annual productivity of the horizontal well, and utilization of the productivity quality index and its lower limit value of the selected oil testing vertical well to determine the single-well productivity quality of the horizontal well include:

[0028] Select a horizontal well in the same series as the selected vertical well and using the segmented and clustered fracturing technology;

[0029] Determine the single-well productivity quality of the selected horizontal well using the following formula;

[0030]

[0031] where, I ph is the single-well productivity quality; I pi is the productivity quality index of the i-th fracturing interval where I p is greater than the lower limit value of the productivity quality index of the selected vertical well; h i is the length of the i-th fracturing interval where I p is greater than the lower limit value of the productivity quality index of the selected vertical well;

[0032] Determine the sensitive fracturing parameters of the annual productivity of the selected horizontal well according to the segmented and clustered fracturing construction data of the selected horizontal well, where the sensitive fracturing parameters include cluster fluid volume, cluster proppant dosage, and cluster construction displacement.

[0033] The second technical solution of the present invention is achieved through the following measures: A prediction device for the annual productivity after fracturing of a horizontal well, including a processing unit, a generating unit, and a prediction unit;

[0034] A processing unit selects a horizontal well and determines the sensitive fracturing parameters of the single-well production capacity quality and annual production capacity of the horizontal well. Here, the horizontal well is in the same formation as the horizontal well to be predicted and uses a segmented and clustered fracturing process; the sensitive fracturing parameters include the cluster liquid volume, the cluster proppant dosage, and the cluster construction displacement.

[0035] A generating unit constructs a prediction model for the annual production capacity of the horizontal well by using the single-well production capacity quality and the sensitive fracturing parameters of the annual production capacity of the selected horizontal well.

[0036] A predicting unit predicts the annual production capacity of the horizontal well to be predicted according to the prediction model for the annual production capacity of the horizontal well.

[0037] The following is a further optimization or / and improvement of the above technical solution of the invention:

[0038] The above processing unit includes a first processing module and a second processing module;

[0039] The first processing module selects a well testing vertical well and determines the production capacity quality index and its lower limit value of the well testing vertical well. Here, the well testing vertical well is a well testing vertical well in the same formation as the horizontal well to be predicted and having the same fracturing process;

[0040] The second processing module selects a horizontal well, determines the sensitive fracturing parameters of the annual production capacity of the horizontal well, and determines the single-well production capacity quality of the horizontal well by using the production capacity quality index and its lower limit value of the selected well testing vertical well. Here, the horizontal well is in the same formation as the selected well testing vertical well and uses a segmented and clustered fracturing process; the sensitive fracturing parameters include the cluster liquid volume, the cluster proppant dosage, and the cluster construction displacement.

[0041] The present invention comprehensively considers the reservoir's own characteristic indexes and the fracturing construction process, that is, a horizontal well in the same formation as the horizontal well to be measured and using a segmented and clustered fracturing process, obtains the sensitive fracturing parameters of the single-well production capacity quality and annual production capacity of the horizontal well, and fits a production capacity prediction model by using the single-well production capacity quality and the sensitive fracturing parameters of the annual production capacity related to the horizontal well production capacity. That is, from the two aspects of "reservoir quality" and "engineering quality", a production capacity prediction model is constructed, so that the constructed production capacity prediction model considers more comprehensive production capacity influencing factors compared with the production capacity prediction model obtained by the existing conventional methods, the constructed prediction model is more reasonable, the production capacity prediction is more accurate, avoiding the problem that the production capacity after fracturing transformation in actual production fails to reach the expected effect, and making the production capacity prediction model of the embodiment of the present invention have strong adaptability and greater generality. Description of the Drawings

[0042] Appendix Figure 1 It is a flowchart of the method according to Embodiment 1 of the present invention.

[0043] Appendix Figure 2It is the flowchart of the method in Embodiment 2 of the present invention.

[0044] Appendix Figure 3 It is the flowchart of the method for determining the productivity quality index and its lower limit value of the selected oil test vertical well in Embodiment 3 of the present invention.

[0045] Appendix Figure 4 It is the relationship diagram between the movable oil porosity and the rice production index in Embodiment 3 of the present invention.

[0046] Appendix Figure 5 It is the relationship diagram between the brittleness index and the rice production index in Embodiment 3 of the present invention.

[0047] Appendix Figure 6 It is the method flow for determining the sensitive fracturing parameters of the productivity quality and annual productivity of the selected horizontal well in Embodiment 4 of the present invention.

[0048] Appendix Figure 7 It is the method flow for constructing the prediction model of the annual productivity of the horizontal well in Embodiment 5 of the present invention.

[0049] Appendix Figure 8 It is the relationship diagram between the normalized single-well productivity quality and the annual cumulative oil production in Embodiment 5 of the present invention.

[0050] Appendix Figure 9 It is the relationship diagram between the liquid volume intensity and the annual cumulative oil production in Embodiment 5 of the present invention.

[0051] Appendix Figure 10 It is the relationship diagram between the proppant strength and the annual cumulative oil production in Embodiment 5 of the present invention.

[0052] Appendix Figure 11 It is the relationship diagram between the construction displacement intensity and the annual cumulative oil production in Embodiment 5 of the present invention.

[0053] Appendix Figure 12 It is the relationship diagram between the actual annual cumulative oil production of a single well and the predicted annual cumulative oil production in Embodiment 6 of the present invention.

[0054] Appendix Figure 13 It is the structural block diagram of Embodiments 7 and 8 of the present invention. Detailed implementation manners

[0055] The present invention is not limited by the following embodiments, and the specific implementation manners can be determined according to the technical solution of the present invention and the actual situation.

[0056] The present invention will be further described below in conjunction with the embodiments and the drawings:

[0057] Embodiment 1: As shown in the appendix Figure 1 The embodiment of the present invention discloses a method for predicting the annual productivity after fracturing of a horizontal well, including:

[0058] Step S101: Select a horizontal well, and determine the single-well productivity quality and the sensitive fracturing parameters of the annual productivity of this horizontal well. Here, the horizontal well is in the same formation as the horizontal well to be predicted and uses the segmented and clustered fracturing technology; the sensitive fracturing parameters include the cluster fluid volume, the cluster proppant dosage, and the cluster construction displacement.

[0059] Step S102: Use the single-well productivity quality and the sensitive fracturing parameters of the annual productivity of the selected horizontal well to construct a prediction model for the annual productivity of the horizontal well.

[0060] Step S103: Predict the annual productivity of the horizontal well to be predicted according to the prediction model for the annual productivity of the horizontal well.

[0061] The embodiment of the present invention discloses a method for predicting the annual productivity after fracturing of a horizontal well, which comprehensively considers the reservoir's own characteristic indexes and the fracturing construction technology, that is, a horizontal well in the same formation as the horizontal well to be measured and using the segmented and clustered fracturing technology, obtains the sensitive fracturing parameters of the single-well productivity quality and the annual productivity of this horizontal well, and uses the single-well productivity quality and the sensitive fracturing parameters of the annual productivity related to the horizontal well productivity to fit the productivity prediction model, that is, constructs the productivity prediction model from two aspects of "reservoir quality" and "engineering quality", making the constructed productivity prediction model consider more comprehensive productivity influencing factors compared with the productivity prediction model obtained by the existing conventional methods, the constructed prediction model is more reasonable, the productivity prediction is more accurate, avoiding the problem that the productivity after fracturing transformation in actual production fails to reach the expected effect, making the productivity prediction model of the embodiment of the present invention have strong adaptability and greater generality.

[0062] Example 2: As shown in the appendix Figure 2 The embodiment of the present invention discloses a method for predicting the annual productivity after fracturing of a horizontal well, including:

[0063] Step S201: Select a well testing vertical well, and determine the productivity quality index and its lower limit value of this well testing vertical well. Here, the well testing vertical well is a well testing vertical well in the same formation as the horizontal well to be predicted and having the same fracturing technology.

[0064] Step S202: Select a horizontal well, determine the sensitive fracturing parameters of the annual productivity of this horizontal well, and use the productivity quality index and its lower limit value of the selected well testing vertical well to determine the single-well productivity quality of this horizontal well. Here, the horizontal well is in the same formation as the selected well testing vertical well and uses the segmented and clustered fracturing technology; the sensitive fracturing parameters include the cluster fluid volume, the cluster proppant dosage, and the cluster construction displacement.

[0065] Step S203: Use the single-well productivity quality and the sensitive fracturing parameters of the annual productivity of the selected horizontal well to construct a prediction model for the annual productivity of the horizontal well.

[0066] Step S204: Predict the annual production capacity of the horizontal well to be predicted according to the prediction model of the annual production capacity of the horizontal well.

[0067] In the embodiment of the present invention, a well testing vertical well in the same formation as the horizontal well to be predicted and with the same fracturing process, and a horizontal well in the same formation as the selected vertical well and using the staged and clustered fracturing process are sequentially selected to obtain the single-well production capacity quality and the sensitive fracturing parameters of the annual production capacity of the horizontal well, and the production capacity prediction model is fitted by using the single-well production capacity quality related to the horizontal well production capacity and the sensitive fracturing parameters of the annual production capacity.

[0068] Example 3: As shown in the appendix Figure 3 The embodiment of the present invention discloses a method for predicting the annual production capacity after fracturing of a horizontal well. When selecting a well testing vertical well, determining the production capacity quality index of the well testing vertical well and its lower limit value, further including:

[0069] Step S301: Select a well testing vertical well in the same formation as the horizontal well to be predicted and with the same fracturing process;

[0070] Here, selecting a well testing vertical well in the same formation as the horizontal well to be predicted and with the same fracturing process is to reduce the interference of fracturing factors and facilitate comparing the production volume of the reservoir under the same background.

[0071] Step S302: Determine the rice production index of the corresponding well testing interval in combination with the following formula;

[0072]

[0073] where I oil is the rice production index of the well testing interval; m is the daily oil production obtained from well testing; h is the thickness of the well testing interval.

[0074] Step S303: Obtain the sensitive reservoir characteristic parameters of the rice production index, where the sensitive reservoir characteristic parameters include movable oil porosity and brittleness index;

[0075] The process of obtaining the sensitive reservoir characteristic parameters of the rice production index here includes: performing a correlation analysis on the reservoir characteristic parameters affecting the rice production index; obtaining the sensitive reservoir characteristic parameters required for the rice production index according to the magnitude of the correlation coefficient. Here, after the correlation analysis, it is found that only the movable oil porosity and the brittleness index are both positively correlated with the rice production index. As shown in the appendix Figure 4 and 5 shown, thus obtaining the sensitive reservoir characteristic parameters of the rice production index, which are the movable oil porosity and the brittleness index.

[0076] Step S304: Use the sensitive reservoir characteristic parameters of the rice production index to obtain the production capacity quality index and its lower limit value of the vertical well through the following formula;

[0077]

[0078] Among them, I p is the production capacity quality index; a, b, and c are constants that can be obtained by parameter fitting; is the movable oil porosity, in %, obtained from the nuclear magnetic resonance logging T2 spectrum; I b is the brittleness index, calculated by the regional empirical formula.

[0079] Here, using the sensitive reservoir characteristic parameters of the rice production index (i.e., movable oil porosity and brittleness index), substitute them into the above formula to obtain the production capacity quality index I of the vertical well p ; the lower limit value I of the production capacity quality index p_cutoff Then substitute the movable oil porosity and brittleness index of the test oil interval corresponding to this vertical well into the above formula for calculation, that is, I p_cutoff is the boundary between dry layers and oil layers.

[0080] Example 4: As shown in the appendix Figure 6 This invention example discloses a prediction method for the annual production capacity after horizontal well fracturing. Among them, select a horizontal well, determine the sensitive fracturing parameters of the annual production capacity of this horizontal well, and use the production capacity quality index and its lower limit value of the selected test oil vertical well to determine the single-well production capacity quality of this horizontal well, including:

[0081] Step S401, select a horizontal well in the same formation as the selected vertical well and using the segmented and clustered fracturing process.

[0082] Step S402, use the following formula to determine the single-well production capacity quality of the selected horizontal well;

[0083]

[0084] Among them, I ph is the single-well production capacity quality, reflecting the quality of the sweet spot itself; n is the length of the horizontal well; i is each meter in the length of the horizontal well; I pi is the production capacity quality index of the fracturing interval greater than the lower limit value I of the production capacity quality index p_cutoff , dimensionless; h i is the length of the fracturing interval when the production capacity quality index is greater than the lower limit value I of the production capacity quality index p_cutoff , in m.

[0085] Here, find the production capacity quality index of each meter of the length of the selected horizontal well, compare it with the lower limit value I of the production capacity quality index p_cutoff , retain the production capacity quality index greater than the lower limit value I of the production capacity quality index p_cutoff , and multiply it by the length of the corresponding fracturing interval, and then sum them up to obtain the single-well production capacity quality of the selected horizontal well.

[0086] Step S403: Determine the sensitive fracturing parameters of the annual production capacity of the selected horizontal well based on the staged and clustered fracturing construction data of the selected horizontal well, where the sensitive fracturing parameters include the cluster fluid volume, the cluster proppant dosage, and the cluster construction displacement.

[0087] Here, the sensitive fracturing parameters include the cluster fluid volume, the cluster proppant dosage, and the cluster construction displacement. The three parameters are closely related to the number, morphology, and spatial distribution of the fractures formed in the reservoir after volumetric fracturing, and show a positive correlation. Among them, the cluster quantity number is the average value of all cluster quantity numbers in the fracturing section, and the cluster proppant dosage considers whether the proppant is quartz sand or ceramsite. Example 5: As shown in the appendix Figure 7 As shown, the embodiment of the present invention discloses a method for predicting the annual production capacity after fracturing of a horizontal well, in which a prediction model of the annual production capacity of the horizontal well is constructed by using the single-well production capacity quality and the sensitive fracturing parameters of the annual production capacity of the selected horizontal well, and further includes:

[0088] Step S501: Normalize the single-well production capacity quality and the sensitive fracturing parameters of the annual production capacity of the selected horizontal well. Here, in order to eliminate the influence of different dimensions of each parameter, the sensitive fracturing parameters of the annual production capacity of the selected horizontal well and the single-well production capacity quality are normalized so that the numerical values are between 0 and 1. The influence mechanisms of different parameters on the reservoir production capacity are different,

[0089] The normalization methods are also different. The specific normalization process includes:

[0090] A. Normalize the single-well production capacity quality I ph of the selected horizontal well by using the following formula to obtain the normalized single-well production

[0091] capacity quality I phn ;

[0092]

[0093] where, I ph_i is the single-well production capacity quality of the i-th well, dimensionless; I ph_max is the maximum value in the single-well production capacity quality, dimensionless.

[0094] B. After normalizing the cluster fluid volume, the cluster proppant dosage, and the cluster construction displacement, the fluid volume intensity I ln , the proppant intensity I sn , and the construction displacement intensity I rn are obtained respectively. The normalization formula is:

[0095]

[0096] where, x i , x max are the cluster fluid volume and the maximum cluster fluid volume of the i-th well respectively, with the unit of m 3 / cluster; proppant consumption per cluster, maximum proppant consumption per cluster, unit: m3 / cluster; pumping rate for cluster treatment, maximum pumping rate for cluster treatment, unit: m 3 / min; p i and p xmax are the closure stress of the i-th well and the closure stress corresponding to x max respectively, unit: MPa; c is the correlation coefficient, and its value depends on whether it is related to the type of proppant; that is, the liquid volume intensity I ln and the pumping rate intensity I rn are not affected by the type of proppant, and c takes the value of 1; the proppant strength I sn is related to the type of proppant. Therefore, when all the proppant is quartz sand, c takes the value of 1; when the proppant is quartz sand followed by ceramsite, c takes the value of 1.2; when all the proppant is ceramsite, c takes the value of 1.3.

[0097] Since the number, shape, and spatial distribution of the fractures formed by volume fracturing in the reservoir are not only affected by the liquid volume, proppant consumption, etc. in the fracturing parameters but also closely related to the closure stress. Generally, the closure stress has a negative effect on fracturing. When the closure stress is greater, a larger fracturing scale is required to achieve the same fracture creation effect. Therefore, the normalization of the above sensitive fracturing parameters should consider the influence of the closure stress. The closure stress P can be calculated by the regional empirical formula, and its value is the average value of the fracturing section of the horizontal well.

[0098] The number, shape, and spatial distribution of the fractures formed by volume fracturing in the reservoir are not only affected by the liquid volume, proppant consumption, etc. in the fracturing parameters but also closely related to the closure stress. Generally, the closure stress has a negative effect on fracturing. When the closure stress is greater, a larger fracturing scale is required to achieve the same fracture creation effect. Therefore, the normalization of the fracturing construction parameters should consider the influence of the closure stress.

[0099] Step S502: Using the normalized sensitive fracturing parameters and the single-well production quality, construct a prediction model for the annual production capacity of the horizontal well. The prediction model is as follows:

[0100] M yr = a * I phn + b * I ln + c * I sn + d * I rn + e

[0101] where M yr is the annual production capacity of the horizontal well; a, b, c, d, and e are constants; I phn is the normalized single-well production quality; I ln , I sn , I rnThey are the liquid volume strength, proppant strength, and construction displacement strength obtained after normalizing the sensitive fracturing parameters respectively.

[0102] When performing a correlation analysis on the normalized sensitive fracturing parameters and the single-well production capacity quality, as shown in Appendices Figure 8 , 9 , 10, and 11, it can be seen that the normalized sensitive fracturing parameters and the single-well production capacity quality have varying degrees of positive correlation with the annual production capacity of the horizontal well. Therefore, the present invention uses the normalized sensitive fracturing parameters and the single-well production capacity quality to construct a prediction model for the annual production capacity of the horizontal well, and the construction process can be achieved by using the method of multiple regression.

[0103] Example 6: In this example of the present invention, the prediction model formed in Example 7 is used to predict the production capacity of the horizontal well to be measured. At the same time, by parameter fitting, it is determined that a, b, c, d, and e are 0.656, 0.033, 1.256, 0.402, and -0.633 respectively. Substituting these values into the prediction model formed in Example 7, the predicted annual cumulative oil production is obtained, and it is compared with the actual annual cumulative oil production of the single well to obtain the relationship diagram as shown in Appendix Figure 12 . It can be seen from the attached figure that the predicted annual cumulative oil production of the present invention has a good degree of coincidence with the actual annual cumulative oil production of the single well.

[0104] Example 7: As shown in Appendix Figure 13 , this example of the present invention discloses a prediction device for the annual production capacity after horizontal well fracturing, including a processing unit, a generating unit, and a predicting unit;

[0105] The processing unit selects a horizontal well and determines the single-well production capacity quality and the sensitive fracturing parameters of the annual production capacity of this horizontal well. Among them, the horizontal well is a horizontal well in the same formation as the horizontal well to be predicted and using the segmented and cluster fracturing technology; the sensitive fracturing parameters include the cluster liquid volume, the cluster proppant dosage, and the cluster construction displacement;

[0106] The generating unit uses the single-well production capacity quality and the sensitive fracturing parameters of the annual production capacity of the selected horizontal well to construct a prediction model for the annual production capacity of the horizontal well;

[0107] The predicting unit predicts the annual production capacity of the horizontal well to be predicted according to the prediction model of the annual production capacity of the horizontal well.

[0108] Example 8: As shown in Appendix Figure 13 , this example of the present invention discloses a prediction device for the annual production capacity after horizontal well fracturing, where the processing unit further includes a first processing module and a second processing module;

[0109] The first processing module selects a well testing vertical well and determines the production capacity quality index and its lower limit value of this well testing vertical well. Among them, this well testing vertical well is a well testing vertical well in the same formation as the horizontal well to be predicted and having the same fracturing technology;

[0110] The second processing module selects a horizontal well, determines the sensitive fracturing parameters of the annual production capacity of the horizontal well, and determines the single-well production quality of the horizontal well by using the production capacity quality index of the selected well test vertical well and its lower limit value, where the horizontal well is in the same series as the selected well test vertical well and adopts a segmented and clustered fracturing process; the sensitive fracturing parameters include cluster liquid volume, cluster proppant dosage, and cluster construction displacement.

[0111] Example 9. An embodiment of the present invention discloses a storage medium on which a computer program readable by a computer is stored, and the computer program is configured to execute a method for predicting the annual production capacity after horizontal well fracturing when running.

[0112] The above storage medium may include, but is not limited to: various media such as USB flash drives, read-only memories, mobile hard disks, magnetic disks, or optical discs that can store computer programs.

[0113] Example 10. An embodiment of the present invention discloses an electronic device, including a processor and a memory, where a computer program is stored in the memory, and the computer program is loaded and executed by the processor to implement a method for predicting the annual production capacity after horizontal well fracturing.

[0114] The above electronic device further includes a transmission device and an input / output device, where the transmission device and the input / output device are both connected to the processor.

[0115] The above technical features constitute the best embodiment of the present invention, which has strong adaptability and the best implementation effect. Non-essential technical features can be added or subtracted according to actual needs to meet the requirements of different situations.

Claims

1. A prediction method for the annual production capacity after hydraulic fracturing of horizontal wells, characterized in that, Including: Select a horizontal well, and determine the sensitive fracturing parameters of the single-well production capacity quality and annual production capacity of this horizontal well. Among them, the horizontal well is in the same formation as the horizontal well to be predicted and adopts the segmented and clustered fracturing technology; the sensitive fracturing parameters include the cluster fluid volume, the cluster proppant dosage, and the cluster construction displacement; Utilize the sensitive fracturing parameters of the single-well production capacity quality and annual production capacity of the selected horizontal well to construct a prediction model for the annual production capacity of the horizontal well; Predict the annual production capacity of the horizontal well to be predicted according to the prediction model of the annual production capacity of the horizontal well; Among them, determining the sensitive fracturing parameters of the single-well production capacity quality and annual production capacity of this horizontal well includes: Select a well test vertical well, and determine the production capacity quality index and its lower limit value of this well test vertical well. Among them, this well test vertical well is a well test vertical well in the same formation as the horizontal well to be predicted and with the same fracturing technology; Select a horizontal well, determine the sensitive fracturing parameters of the annual production capacity of this horizontal well, and utilize the production capacity quality index and its lower limit value of the selected well test vertical well to determine the single-well production capacity quality of this horizontal well. Among them, this horizontal well is in the same formation as the selected well test vertical well and adopts the segmented and clustered fracturing technology; the sensitive fracturing parameters include the cluster fluid volume, the cluster proppant dosage, and the cluster construction displacement; Among them, selecting a well test vertical well and determining the production capacity quality index and its lower limit value of this well test vertical well includes: Select a well test vertical well in the same formation as the horizontal well to be predicted and with the same fracturing technology; Determine the meter production index of the corresponding well test interval in combination with the following formula; Among them, I oil is the meter production index of the interval being tested for oil; m is the daily oil production obtained from the oil testing; h is the thickness of the interval being tested for oil; Obtain the sensitive reservoir characteristic parameters of the meter production index, where the sensitive reservoir characteristic parameters include movable oil porosity and brittleness index; Utilize the sensitive reservoir characteristic parameters of the meter production index to obtain the production capacity quality index and its lower limit value of the vertical well through the following formula; Among them, I p is the production capacity quality index; a, b, and c are constants; is the movable oil porosity; I b is the brittleness index; Among them, selecting a horizontal well, selecting a horizontal well, determining the sensitive fracturing parameters of the annual production capacity of this horizontal well, and utilizing the production capacity quality index and its lower limit value of the selected well test vertical well to determine the single-well production capacity quality of this horizontal well includes: Select a horizontal well in the same formation as the selected vertical well and adopting the segmented and clustered fracturing technology; Determine the single-well production capacity quality of the selected horizontal well by using the following formula; Among them, I ph is the single-well production capacity quality; I pi is the production capacity quality index of the i-th p fracture interval whose production capacity quality index is greater than the lower limit value of the selected vertical well production capacity quality index; h i is the length of the i-th p fracture interval whose production capacity quality index is greater than the lower limit value of the selected vertical well production capacity quality index; Determine the sensitive fracturing parameters of the annual production capacity of the selected horizontal well according to the segmented and clustered fracturing construction data of the selected horizontal well, where the sensitive fracturing parameters include the cluster fluid volume, the cluster proppant dosage, and the cluster construction displacement.

2. The prediction method for annual production capacity after horizontal well fracturing according to claim 1, wherein The constructing a prediction model for the annual production capacity of the horizontal well by using the single-well production capacity quality and the sensitive fracturing parameters of the annual production capacity of the selected horizontal well includes: Normalize the single-well production capacity quality and the sensitive fracturing parameters of the annual production capacity of the selected horizontal well; Utilize the normalized sensitive fracturing parameters and single-well production capacity quality to construct a prediction model for the annual production capacity of the horizontal well. The prediction model is as follows: M yr = a*I phn + b*I ln + c*I sn + d*I rn + e Among them, M yr is the annual production capacity of the horizontal well; a, b, c, d, and e are constants; I phn is the productivity quality of a single well after normalization; I ln , I sn , and I rn are the liquid volume intensity, proppant intensity, and construction displacement intensity obtained after normalizing the sensitive fracturing parameters, respectively.

3. A prediction device for the annual production capacity after horizontal well fracturing using the method according to claim 1 or 2, characterized in that, Including a processing unit, a generating unit, and a predicting unit; The processing unit selects a horizontal well and determines the sensitive fracturing parameters of the single-well production capacity quality and annual production capacity of this horizontal well. Among them, the horizontal well is in the same formation as the horizontal well to be predicted and adopts the segmented and clustered fracturing technology; the sensitive fracturing parameters include the cluster fluid volume, the cluster proppant dosage, and the cluster construction displacement; A generating unit, which constructs a prediction model for the annual production capacity of a horizontal well by using the single-well production capacity quality and the sensitive fracturing parameters of the annual production capacity of the selected horizontal well; A prediction unit, which predicts the annual production capacity of the horizontal well to be predicted according to the prediction model for the annual production capacity of the horizontal well; Among them, the processing unit includes a first processing module and a second processing module; The first processing module selects a well test vertical well, determines the production capacity quality index and its lower limit value of the well test vertical well, where the well test vertical well is a well test vertical well in the same formation series as the horizontal well to be predicted and with the same fracturing process; The second processing module selects a horizontal well, determines the sensitive fracturing parameters of the annual production capacity of the horizontal well, and determines the single-well production capacity quality of the horizontal well by using the production capacity quality index and its lower limit value of the selected well test vertical well, where the horizontal well is in the same formation series as the selected well test vertical well and adopts a segmented and clustered fracturing process; the sensitive fracturing parameters include the cluster liquid volume, the cluster proppant dosage, and the cluster construction displacement; Among them, selecting a well test vertical well and determining the production capacity quality index and its lower limit value of the well test vertical well includes: Selecting a well test vertical well in the same formation series as the horizontal well to be predicted and with the same fracturing process; Determining the rice production index of the corresponding well test interval in combination with the following formula; Among them, I oil is the meter production index of the oil testing interval; m is the daily oil production obtained from the oil testing; h is the thickness of the oil testing interval; Obtaining the sensitive reservoir characteristic parameters of the rice production index, where the sensitive reservoir characteristic parameters include the movable oil porosity and the brittleness index; Using the sensitive reservoir characteristic parameters of the rice production index to obtain the production capacity quality index and its lower limit value of the vertical well through the following formula; Among them, I p is the production capacity quality index; a, b, and c are constants; is the movable oil porosity; I b is the brittleness index; Among them, selecting a horizontal well, selecting a horizontal well, determining the sensitive fracturing parameters of the annual production capacity of the horizontal well, and determining the single-well production capacity quality of the horizontal well by using the production capacity quality index and its lower limit value of the selected well test vertical well includes: Selecting a horizontal well in the same formation series as the selected vertical well and adopting a segmented and clustered fracturing process; Determining the single-well production capacity quality of the selected horizontal well by using the following formula; Among them, I ph is the productivity quality of a single well; I pi is the productivity quality index of the i-th p frac interval with a productivity quality index greater than the lower limit value of the productivity quality index of the selected vertical well; h i is the length of the i-th p frac interval with a productivity quality index greater than the lower limit value of the productivity quality index of the selected vertical well; Determining the sensitive fracturing parameters of the annual production capacity of the selected horizontal well according to the segmented and clustered fracturing construction data of the selected horizontal well, where the sensitive fracturing parameters include the cluster liquid volume, the cluster proppant dosage, and the cluster construction displacement.

4. A storage medium, characterized in that, The storage medium stores a computer program readable by a computer, and the computer program is set to execute the prediction device for the annual production capacity after horizontal well fracturing as described in claim 1 or 2 when running.

5. An electronic device, characterized in that, It includes a processor and a memory, and a computer program is stored in the memory. The computer program is loaded and executed by the processor to implement the prediction device for the annual production capacity after horizontal well fracturing as described in claim 1 or 2.

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