A water cut prediction method based on fracturing parameters

Abstract

The present invention provides a water cut prediction method based on fracturing parameters, and the method comprises the following steps: calculating the distance between the oil testing layer and the effusive diabase; calculating the correlation value between the gas logging parameters and the water cut of the oil testing, and screening the first sensitive parameter; calculating the correlation value between the fracturing parameters of the oil testing layer and the water cut of the oil testing, and screening the second sensitive parameter; establishing a water cut fitting model according to the first sensitive parameter, the second sensitive parameter and the change rate of the transition zone TI; and predicting the water cut by using the water cut fitting model. This method combines the fracturing parameters with the water cut prediction, establishes a more comprehensive and accurate water cut prediction model, and simultaneously realizes the reverse adjustment of the appropriate range of the fracturing parameters through the prediction model.

Description

Technical Field

[0001] The present invention belongs to the field of oil and gas exploration and development, and relates to a water cut prediction method based on fracturing parameters. Background Art

[0002] The Nanpu 280 block is an important block for increasing reserves and production in the Jidong Oilfield in the past five years. Taking the first sub-member of the third member of the Shahejie Formation as the main target layer, it is a typical reservoir with medium-low porosity and low permeability. After entering the large-scale development stage, all well testing methods of large-scale fracturing are adopted. After fracturing, the water cut of more than 80% of the wells is generally high, and the water cut reaches more than 70%, affecting the stable production of the area.

[0003] In order to analyze the reasons for high water cut in the development of this block, the industry has successively applied a number of logging data and tried existing mature methods, but no expected results have been achieved, and it is impossible to effectively identify the water content in the reservoir of the first sub-member of the third member of the Shahejie Formation in this block. The invention patent "A method, device, electronic device and storage medium for determining the water cut of a well testing interval" has been applied. By introducing the element logging technology and starting from the change characteristics of trace elements in the diabase closest to the well testing interval, a water cut prediction model based on the TI change rate of the diabase transition zone has been invented, and a breakthrough has been made. The fitting degree of the functional relationship reaches 0.8966. However, through in-depth analysis, it is found that this method only considers the influence of adjacent diabase on the well testing water production, but does not consider the influence of various parameters related to fracturing on the well testing water production. The prediction accuracy is limited, and it is impossible to provide suggestions for well testing layer selection and optimization of fracturing parameters. Summary of the Invention

[0004] To solve the technical problems existing in the prior art, the present invention provides a water cut prediction method based on fracturing parameters. This method combines fracturing parameters with water cut prediction, establishes a more comprehensive and accurate water cut prediction model, and at the same time realizes the reverse adjustment of the appropriate range of fracturing parameters through the prediction model.

[0005] To achieve the above technical effects, the present invention adopts the following technical solutions:

[0006] The present invention provides a water cut prediction method based on fracturing parameters, and the method includes the following steps:

[0007] Calculate the distance between the well testing layer and the water-producing diabase;

[0008] Calculate the correlation value between the gas logging parameters and the well testing water cut, and screen the first sensitive parameter;

[0009] Calculate the correlation value between the fracturing parameters of the well testing layer and the well testing water cut, and screen the second sensitive parameter;

[0010] Establish a water cut fitting model according to the first sensitive parameter, the second sensitive parameter and the TI change rate of the transition zone;

[0011] Use the water content fitting model to predict the water content.

[0012] As a preferred technical solution of the present invention, the distance D between the oil test layer and the effluent diabase is D = D 出水井段中间深度 - D 试油层中间深度 .

[0013] As a preferred technical solution of the present invention, the method further includes verifying the correlation between the calculated distance between the oil test layer and the effluent diabase and the oil test water production rate.

[0014] Use grey correlation to calculate the correlation value between the gas logging parameters and the water content of the oil test.

[0015] As a preferred technical solution of the present invention, the correlation value between the first sensitive parameter and the water content of the oil test is not less than 0.7000, such as 0.7000, 0.7200, 0.7500, 0.7800 or 0.8000, etc., but is not limited to the listed values, and other unlisted values within this value range are equally applicable.

[0016] As a preferred technical solution of the present invention, the first sensitive parameters include peak-to-base ratio, total hydrocarbon Tg, heavy hydrocarbon Hg, humidity ratio Wh, equilibrium ratio Bh, light-to-heavy ratio Lh, and light-to-medium ratio Lm.

[0017] As a preferred technical solution of the present invention, use grey correlation to calculate the correlation value between the fracturing parameters of the oil test layer and the water content of the oil test.

[0018] As a preferred technical solution of the present invention, the correlation value between the second sensitive parameter and the water content of the oil test is not less than 0.7000, such as 0.7000, 0.7200, 0.7500, 0.7800 or 0.8000, etc., but is not limited to the listed values, and other unlisted values within this value range are equally applicable.

[0019] As a preferred technical solution of the present invention, the second sensitive parameters include total sand volume, total liquid volume, and construction displacement.

[0020] As a preferred technical solution of the present invention, the water content fitting model is as shown in Equation 1:

[0021] Water content = (k1×Lm + k2×Lh + k3×Bh + k4×Wh + k5×Hg / 100% + k6×Total hydrocarbon / 1% + k7×Peak-to-base ratio + k8×Change rate of transition zone TI / 1% / m + k9×Construction displacement / 1L / min + k 10 ×Total liquid volume / 1m 3 + k 11 ×Total sand volume / 1t + k 12 ×D / 1m + b)×100%

[0022] Formula 1

[0023] where k1 to k 12 are the regional regression coefficients of each parameter, and b is the regional adjustment coefficient.

[0024] Compared with the prior art, the present invention has at least the following beneficial effects:

[0025] The present invention provides a water cut prediction method based on fracturing parameters. This method is the first to study from the perspective of the influence of various fracturing parameters on the oil testing results, and establishes a comprehensive oil testing water cut prediction model with fracturing parameters as the core. With the help of this model, by adjusting the values of each parameter, an attempt can be made to minimize the predicted water cut, thereby completing the optimization of oil testing layer selection and fracturing scheme. BRIEF DESCRIPTION OF THE DRAWINGS

[0026] Figure 1 is a comparison chart of the fitted water cut and the actual water cut in Example 1 of the present invention;

[0027] Figure 2 is the comprehensive diagram of Well NP1 in Example 2 of the present invention.

[0028] The following further details the present invention. However, the following examples are only simple examples of the present invention and do not represent or limit the scope of the protection of the present invention. The scope of protection of the present invention is subject to the claims. DETAILED DESCRIPTION OF THE INVENTION

[0029] The following further illustrates the technical solutions of the present application through specific embodiments.

[0030] The specific embodiment of the present invention provides a water cut prediction method based on fracturing parameters, and this method includes the following steps:

[0031] Calculate the distance between the oil testing layer and the effusive diabase.

[0032] Calculate the correlation value between the gas logging parameter and the oil testing water cut, and screen the first sensitive parameter.

[0033] Calculate the correlation value between the fracturing parameter of the oil testing layer and the oil testing water cut, and screen the second sensitive parameter.

[0034] Establish a water cut fitting model according to the first sensitive parameter, the second sensitive parameter and the change rate of the transition zone TI.

[0035] Use the water cut fitting model to predict the water cut.

[0036] In view of the poor physical properties of the reservoir in the first sub-member of the third member of the Shahejie Formation in the Nanpu 280 block, and the high water cut caused by the development with fracturing technology, the existing logging methods cannot effectively predict the water production during well testing. Although a water cut prediction model based on the TI change rate of the diabase transition zone has been established to solve some problems in water-bearing prediction, due to the lack of full consideration of various parameters related to fracturing, it still cannot provide more support for the subsequent well testing layer selection and program parameter optimization.

[0037] Since the first sub-member of the third member of the Shahejie Formation in the Nanpu 280 block has near-source hydrocarbon accumulation, poor physical properties, and strong heterogeneity, it is a typical unconventional oil reservoir. Conventional well testing methods cannot fully communicate more pores and fractures and cannot obtain ideal results. Therefore, fracturing technology is an inevitable means, and the current fracturing programs generally result in water production and a high water production rate after application. In the present invention, by analyzing the fracturing parameters of the first sub-member of the third member of the Shahejie Formation and combining the established water cut prediction method, the fracturing parameters are combined with the water cut prediction to establish a more comprehensive and accurate water cut prediction model. At the same time, the appropriate range of fracturing parameters is adjusted reversely through the prediction model.

[0038] In a specific embodiment of the present invention, a theory of high water cut in fracturing of the target layer in the study area is established.

[0039] Specifically, taking the first sub-member of the third member of the Shahejie Formation in the Nanpu 280 block as an example, the lithology of the first sub-member of the third member of the Shahejie Formation in the Nanpu 280 block is mainly sandstone and mudstone, showing an interbedded feature, with a sand-to-shale ratio of less than 30%, which is a typical shale reservoir. According to the general understanding of this type of reservoir in the industry, due to the poor physical properties of such oil-bearing reservoirs, there are no large pore throats, so there is no situation of high water cut. Generally, it is mainly low-saturation bound water, so there will be no situation of too high water cut after fracturing. However, the water cut after fracturing of the current well testing layers generally reaches more than 70%. Therefore, it is considered that the target well testing layer is not the main water-producing layer. Considering that the high water-producing well testing layers are generally close to the diabase, and according to the previous research, there is an obvious correlation between the target well testing layer and the TI element change rate, so a new understanding is first proposed: it is considered that the general high water cut in well testing of the first sub-member of the third member of the Shahejie Formation in the Nanpu 280 block is because the fracturing parameters are improperly selected, fracturing the adjacent top water-bearing diabase layer, resulting in a large final water production and a high water cut.

[0040] In a specific embodiment of the present invention, the calculation of the middle depth of the water-producing section of the diabase is carried out.

[0041] Specifically, find the diabase closest to the expected well testing section and determine it as the research target. According to the previous research, it is considered that the lithology transition zone at the top of the diabase is the water-producing section of the well testing, so its middle depth is the middle depth of the lithology transition zone, that is, D 出水井段中间深度 = D 岩性过渡带中间深度 ;

[0042] Taking the characteristic of the standard lithology elements of the first sub-member of the third member of Shahejie Formation as a reference, the middle depth of the lithology transition zone at the top of the diabase is determined, which is the middle depth between the standard lithology above the diabase and the standard diabase, that is where Dx is the depth value of the last point of the standard lithology above the diabase, and Ddiabase is the depth value of the first point of the standard diabase.

[0043] In a specific embodiment of the present invention, the distance between the oil testing layer and the water-producing diabase is calculated. The middle depth of the oil testing layer According to the calculation result of the middle depth of the water-producing well section of the diabase, the distance D between the oil testing layer and the water-producing diabase is D = D 出水井段中间深度 - D 试油层中间深度 .

[0044] In a specific embodiment of the present invention, the Pearson correlation algorithm is applied to calculate the correlation between the distance D between the oil testing layer and the water-producing diabase and the oil testing water cut.

[0045] In a specific embodiment of the present invention, taking the first sub-member of the third member of Shahejie Formation in Nanpu Block 280 as an example, the correlation between D and the oil testing water cut is calculated, and the data correlation reaches 0.83, which proves that the oil production of the oil testing is indeed significantly related to the water content of the adjacent diabase. The high water cut theory of fracturing in the target layer of the above research area is established, and at the same time, it is demonstrated that the distance D between the oil testing layer and the water-producing diabase can be used as one of the sensitive parameters for predicting the oil testing water cut in the first sub-member of the third member of Shahejie Formation in Nanpu Block 280.

[0046] In a specific embodiment of the present invention, taking the first sub-member of the third member of Shahejie Formation in Nanpu Block 280 as an example, through grey relational correlation calculation, the first sensitive parameters between the gas logging parameters and the oil testing water cut are the peak-base ratio, total hydrocarbon Tg, heavy hydrocarbon Hg, humidity ratio Wh, balance ratio Bh, light-heavy ratio Lh and light-medium ratio Lm. It should be noted that for oilfields in different regions, combined with different correlation calculation methods and the limitation of correlation values, different first sensitive parameters may be obtained, which will not be further limited here.

[0047] In a specific embodiment of the present invention, taking the first sub-member of the third member of Shahejie Formation in Nanpu Block 280 as an example, through grey relational correlation calculation, the second sensitive parameters between the oil layer fracturing parameters and the oil testing water cut are the total sand volume, total liquid volume and construction displacement. It should be noted that for oilfields in different regions, combined with different correlation calculation methods and the limitation of correlation values, different second sensitive parameters may be obtained, which will not be further limited here.

[0048] In a specific embodiment of the present invention, taking the first sub-member of the third member of Shahejie Formation in Nanpu Block 280 as an example, the water cut fitting model established is shown in Equation 1:

[0049] Water content = (k1 × Lm + k2 × Lh + k3 × Bh + k4 × Wh + k5 × Hg / 100% + k6 × Total hydrocarbon / 1% + k7 × Peak-base ratio + k8 × Transition zone TI change rate / 1% / m + k9 × Construction displacement / 1L / min + k 10 × Total liquid volume / 1m 3 + k 11 × Total sand volume / 1t + k 12 × D / 1m + b) × 100%

[0050] Equation 1

[0051] Among them, the solution methods of k1 to k 12 and b are the least squares method.

[0052] The obtained k1, k2, k3, k4, k5, k6, k7, k8, k9, k 10 , k 11 , k 12 , k 10 = -0.0438, k 11 = 2.0192, k 12 = 2.8581, b = 323.3908.

[0053] In the present invention, the grey correlation calculation and the Pearson correlation algorithm are both well-known correlation calculation methods in the art, and their specific steps are not specifically limited herein.

[0054] To better illustrate the present invention and facilitate the understanding of the technical solution of the present invention, the typical but non-limiting embodiments of the present invention are as follows:

[0055] Embodiment 1

[0056] This embodiment provides a water content prediction method based on fracturing parameters, and the method includes:

[0057] The research object is the first sub-member of the third member of the Shahejie Formation in the Nanpu 280 block;

[0058] The relationship between the water content of the first sub-member of the third member of the Shahejie Formation in the Nanpu 280 block and the distance from the diabase is shown in Table 1. Applying the Pearson correlation algorithm, the correlation between D and the water content of the oil test is calculated, and the data correlation reaches 0.83, proving that there is an obvious relationship between the oil test water production and the water content of the adjacent diabase. The distance D between the oil test layer and the water-producing diabase can be used as one of the sensitive parameters for predicting the water content of the fracturing oil test in the first sub-member of the third member of the Shahejie Formation in the Nanpu 280 block.

[0059] Table 1

[0060]

[0061] Through grey relational correlation calculation, the correlation values between various gas logging parameters of the oil test layer and the water cut of the oil test are calculated, as shown in Table 2. Through correlation ranking, the peak-base ratio, total hydrocarbon Tg, heavy hydrocarbon Hg, humidity ratio Wh, equilibrium ratio Bh, light-heavy ratio Lh, light-medium ratio Lm have relatively high correlations with the water cut of the oil test, and are selected as the first sensitive parameters.

[0062] Table 2

[0063]

[0064] Through grey relational correlation calculation, the correlation values between various fracturing parameters of the oil test layer and the water cut of the oil test are calculated, as shown in Table 3. Through correlation ranking, the total sand volume, total liquid volume, and construction displacement have relatively high correlations with the water cut of the oil test, and are selected as the second sensitive parameters.

[0065] Table 3

[0066]

[0067] According to the first sensitive parameter, the second sensitive parameter and the change rate of the transition zone TI, a water cut fitting model is established, as shown in Equation 1.

[0068] Water cut = (k1×Lm + k2×Lh + k3×Bh + k4×Wh + k5×Hg / 100% + k6×Total hydrocarbon / 1% + k7×Peak-base ratio + k8×Change rate of transition zone TI / 1% / m + k9×Construction displacement / 1L / min + k 10 ×Total liquid volume / 1m 3 +k 11 ×Total sand volume / 1t + k 12 ×D / 1m + b)×100%

[0069] Equation 1

[0070] The k1, k2, k3, k4, k5, k6, k7, k8, k9, k 10 、k 11 、k 12 、b obtained by solving are such that k1 = 0.2497, k2 = 0.0273, k3 = -32.9457, k4 = -5.2914, k5 = -112.2277, k6 = 16.6072, k7 = 8.9135, k8 = 1231.1648, k9 = -5.4460, k 10 = -0.0438, k 11 = 2.0192, k 12= 2.8581, b = 323.3908.

[0071] The water cut is predicted before the fracturing and oil testing by using the established water cut fitting formula, and the fitting degree reaches above 0.9. As Figure 1 shown, the absolute error is controlled within the range of ±5%, which can guide the selection of the next oil testing layer and the optimization of fracturing parameters.

[0072] Example 2

[0073] This example provides a water cut prediction method based on fracturing parameters, and the method includes:

[0074] Taking a wildcat well NP1 in the Nanpu 280 area as an example;

[0075] The target oil testing interval is 4053.0 - 4061.0 m, and the middle depth of oil testing is 4057.0 m. According to the achievements obtained in this invention, the adjacent diabase interval is 4062.0 - 4074.0 m, among which the diabase transition zone interval is 4062.0 - 4064.0 m, and the water production interval depth is 4063.0 m. The distance D between the oil testing layer and the water-producing diabase is 6.0 m;

[0076] The change rate of the transition zone TI = 0.048, the peak-to-base ratio = 3.16, the total hydrocarbon = 2.69%, HG = 0.39%, Wh = 17.97, BH = 15.59, LH = 447.91, LM = 14.33. In the original fracturing plan design, the total sand volume = 235.0 t, the total liquid volume = 3400.0 m 3 3, and the construction displacement = 12.0 L / min;

[0077] Applying the water cut fitting model provided in Example 1, the predicted water cut is 96.42%. Based on the prediction model, the fracturing parameters are adjusted. The total sand volume = 230.0 t, the total liquid volume = 3520.0 m 3 3, and the construction displacement is 14.0 L / min. The predicted water cut is 70.17%, and the actual water cut during oil testing is 71.15%. The absolute error is within the range of ±5%, meeting the production requirements (see Figure 2 , Table 4).

[0078] Table 4

[0079]

[0080] Example 3

[0081] This example provides a water cut prediction method based on fracturing parameters, and the method includes:

[0082] Taking the oil testing layer of the first sub-member of the third member of Shahejie Formation in a wildcat well in the Nanpu 280 block of the Bohai Bay Basin as an example;

[0083] Calculate the middle depth of the diabase water-producing interval

[0084] Find the diabase closest to the predicted oil test interval of the Es3 1st sub-member reservoir. The interval is 4150.0 - 4176.0m. Among them, the lithologic transition zone interval at the top of the diabase is 4150.0 - 4156.0m, D 出水井段中间深度 = 4153.0m.

[0085] Calculate the distance between the oil test layer and the water-producing diabase

[0086] The predicted oil test interval is 4126.0 - 4128.0m, and the middle depth D 试油层中间深度 = 4127.0m. The distance D between the predicted oil test interval and the water-producing diabase = D 出水井段中间深度 - D 试油层中间深度 = 26.0m.

[0087] Parameters involved in prediction

[0088] Calculate all parameters involved in water cut prediction. The change rate of TI in the transition zone = 0.031, peak-to-base ratio = 5.84, total hydrocarbon = 16.63%, HG = 2.10%, Wh = 16.55, BH = 14.53, LH = 2.42, LM = 3.52, total sand volume for fracturing = 47.00t, total liquid volume = 320.00m 3 、construction displacement = 2.00 L / min.

[0089] Water cut prediction

[0090] Apply the water cut fitting model provided in Example 1 to predict that the water cut is 32.53%.

[0091] In this example, for the interval 4126.0 - 4128.0m, the predicted oil test water cut is 32.53%, and the actual oil test water cut is 31.50%. The absolute error of the prediction is 1.03%.

[0092] Example 4

[0093] This example provides a water cut prediction method based on fracturing parameters. The method includes:

[0094] Take the oil test layer of the Es3 1st sub-member of a pre-exploration well in the Nanpu 280 block of the Bohai Bay Basin as an example;

[0095] Calculate the middle depth of the diabase water-producing interval

[0096] Find the diabase closest to the predicted oil test interval of the Es3 1st sub-member reservoir. The interval is 4184.0 - 4210.0m. Among them, the lithologic transition zone interval at the top of the diabase is 4184.0 - 4188.0m, D 出水井段中间深度 = 4186.0m.

[0097] Calculate the distance between the test oil layer and the water-producing diabase

[0098] The predicted test oil interval is 4182.0 - 4184.0 m, and the middle depth D 试油层中间深度 = 4183.0 m. The predicted distance D between the test oil interval and the water-producing diabase is D 出水井段中间深度 - D 试油层中间深度 = 3.0 m.

[0099] Parameters involved in prediction

[0100] Calculate all the parameters involved in the water cut prediction. The change rate of the transition zone TI = 0.168, the peak-to-base ratio = 2.97, the total hydrocarbon = 0.60%, HG = 0.10%, Wh = 17.76, BH = 11.89, LH = 433.25, LM = 83.71, the total sand volume of fracturing = 8.0 t, the total liquid volume = 305.0 m 3 、The construction displacement = 5.0 L / min.

[0101] Water cut prediction

[0102] Apply the water cut fitting model provided in Embodiment 1 to predict that the water cut is 86.67%.

[0103] In this embodiment, the predicted water cut of the test oil in the interval 4182.0 - 4184.0 m is 86.67%, and the actual water cut of the test oil is 86.20%. The absolute error of the prediction is 0.47%.

[0104] The applicant declares that the present invention uses the above embodiments to illustrate the detailed structural features of the present invention, but the present invention is not limited to the above detailed structural features, that is, it does not mean that the present invention must rely on the above detailed structural features to be implemented. Those skilled in the art should understand that any improvement to the present invention, the equivalent replacement of the components selected by the present invention, and the addition of auxiliary components, the selection of specific methods, etc., all fall within the protection scope and the disclosure scope of the present invention.

[0105] The preferred embodiments of the present invention have been described in detail above. However, the present invention is not limited to the specific details in the above embodiments. Within the scope of the technical concept of the present invention, various simple modifications can be made to the technical solution of the present invention, and these simple modifications all belong to the protection scope of the present invention.

[0106] In addition, it should be noted that in the various specific technical features described in the above specific embodiments, they can be combined in any appropriate manner without contradiction. To avoid unnecessary repetition, the present invention will not separately describe various possible combination methods.

[0107] In addition, any combination can be made among various different embodiments of the present invention, as long as it does not violate the idea of the present invention, and it should equally be regarded as the content disclosed by the present invention.

Claims

1. A water cut prediction method based on fracturing parameters, characterized in that, The method includes the following steps: Calculate the distance D between the oil testing layer and the water-producing diabase; Calculate the correlation value between the gas logging parameters and the water cut of the oil testing, and screen the first sensitive parameter; Calculate the correlation value between the fracturing parameters of the oil testing layer and the water cut of the oil testing, and screen the second sensitive parameter; Establish a water cut fitting model according to the first sensitive parameter, the second sensitive parameter, the change rate of the transition zone TI, and the distance D between the oil testing layer and the water-producing diabase; Use the water cut fitting model for water cut prediction.

2. The method according to claim 1, wherein The distance D between the oil testing layer and the water-producing diabase is D = D 出水井段中间深度 - D 试油层中间深度 .

3. The method according to claim 1 or 2, characterized in that, The method further includes verifying the correlation between the calculated distance between the oil testing layer and the water-producing diabase and the oil production water rate of the oil testing.

4. The method according to claim 1, wherein Use grey relational correlation to calculate the correlation value between the gas logging parameters and the water cut of the oil testing.

5. The method according to claim 1, characterized in that, The correlation value between the first sensitive parameter and the water cut of the oil testing is not less than 0.7000.

6. The method according to claim 1, wherein The first sensitive parameters include peak-base ratio, total hydrocarbon Tg, heavy hydrocarbon Hg, humidity ratio Wh, balance ratio Bh, light-heavy ratio Lh, and light-medium ratio Lm.

7. The method according to claim 1, wherein Use grey relational correlation to calculate the correlation value between the fracturing parameters of the oil testing layer and the water cut of the oil testing.

8. The method according to claim 1, wherein The correlation value between the second sensitive parameter and the water cut of the oil testing is not less than 0.7000.

9. The method according to claim 1, wherein The second sensitive parameters include total sand volume, total liquid volume, and construction displacement.

10. The method according to claim 6, characterized in that, The water cut fitting model is shown in Equation 1: Water content = (k1×Lm + k2×Lh + k3×Bh + k4×Wh + k5×Hg / 100% + k6×Total hydrocarbon / 1% + k7×Peak base ratio + k8×Transition zone TI change rate / 1% / m + k9×Construction displacement / 1L / min + k 10 ×Total liquid volume / 1m 3 +k 11 ×Total sand volume / 1t + k 12 ×D / 1m + b)×100% Equation 1 Among them, k1~k 12 are the regional regression coefficients of each parameter, and b is the regional adjustment coefficient.

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