A shale gas well recoverable reserves analysis method considering dynamic capillary effect

Abstract

The application provides a shale gas well recoverable reserves analysis method considering dynamic capillary effect, which utilizes shale gas well original production data to obtain a fitting relationship curve of original production and production time, further obtains effective production data, and obtains reservoir capillary pressure and dynamic capillary effect coefficient of each production time through the effective production data, further obtains initial ideal production considering dynamic capillary effect, fits basic parameters considering dynamic capillary effect, then obtains characteristic time, deduces future ideal production, and obtains future actual production after considering dynamic capillary effect again, and finally calculates recoverable reserves (EUR). The method can consider dynamic capillary effect, adopt a capillary bundle model, and make the analysis and prediction result more accurate.

Description

Technical Field

[0001] This invention belongs to the fields of shale gas development technology and gas production engineering, specifically a method for analyzing the recoverable reserves of shale gas wells that considers dynamic capillary effects. Background Technology

[0002] Shale gas reservoirs are characterized by low porosity and permeability, and high adsorbed gas content, requiring large-scale hydraulic fracturing for effective production. Capillary pressure is the primary obstacle to fracturing fluid flowback. EIA statistics indicate that my country's recoverable shale gas reserves are approximately 36.1 × 10⁻⁶. 12 m 3 China possesses approximately 20% of the world's technically recoverable reserves, making it the country with the richest shale gas resources globally. Estimated Ultimate Recovery (EUR) of shale gas wells is a key indicator for comprehensively evaluating development effectiveness. Shale gas is primarily found within matrix nanopores and natural fractures. Shale gas reservoirs are often developed using a horizontal well + hydraulic fracturing model, involving cross-scale flow issues during the gas flow from the reservoir to the wellbore. During extraction, gas diffuses from the matrix into natural fractures, then converges from natural fractures into artificial fractures, and finally flows into the wellbore. Gas flow traverses nanoscale matrix pores, micrometer-scale natural fractures, and meter-scale artificial fractures, resulting in complex and variable gas flow patterns. Traditional Darcy's law is no longer applicable. Currently, production capacity evaluation mainly relies on calculating the unobstructed flow rate of the gas well through production well testing, but this assessment method is costly and cannot cope with subsequent changes.

[0003] Therefore, relevant research institutions also adopt the method of establishing flow equations coupled with multi-scale flow laws to evaluate EUR. Existing evaluation methods for EUR of shale gas wells include analogy method, flow material balance method, and production decline analysis method. For example, Chinese patent application number 202010130359.6, "A Method for Predicting Permeability of Shale Reservoirs Based on Improved Kozeny-Carman Model", and application number 202011420774.1, "A Method and System for Predicting Production of Fracturing Horizontal Wells in Shale Gas Reservoirs", both provide evaluation and prediction methods based on their respective models.

[0004] Because shale gas reservoirs have extremely low permeability and porosity, and the flow of gas and water in the matrix during gas well production is greatly affected by the dynamic capillary effect, existing EUR evaluation methods for shale gas wells are difficult to fully consider the dynamic capillary effect, resulting in large errors in the evaluation results and making it difficult to accurately simulate the required data. Summary of the Invention

[0005] To overcome the above technical deficiencies, this invention provides a method for analyzing the recoverable reserves of shale gas wells that considers the dynamic capillary effect. This method takes into account the dynamic capillary effect and uses a capillary bundle model, making the analysis and prediction results more accurate.

[0006] The technical solution of the present invention is as follows:

[0007] A method for analyzing recoverable reserves of shale gas wells considering dynamic capillary effects, employing a model for analysis and calculation, includes the following steps:

[0008] S100. Collect raw production data for the shale gas wells to be analyzed, and use the raw production rate q of the shale gas wells. initial Based on the linear flow stage under the initial fixed bottom pressure production conditions, the reciprocal of the production rate and the half power of time have a linear relationship in the coordinate system. The following formula (1) is used to utilize the original production data q of the shale gas well. initial :

[0009]

[0010] Where: q initial —Original yield, m 3 / d;

[0011] t—production time, d;

[0012] w—fitting parameters, d 0.5 / m 3 ;

[0013] b—fitting parameter, d / m 3 ;

[0014] Fitting using formula (1) and The relationship curve is used to determine the value of parameter w by using the slope of the obtained relationship curve, and the value of b is determined by the curve intercept;

[0015] S200. Using formula (1), the yield data is screened and corrected by fitting the relationship curve to obtain effective yield data q.

[0016] S300. Based on the flowback volume of fracturing fluid at the site, the reservoir water saturation is calculated using formula (2). The reservoir capillary pressure at each production time is obtained from the capillary pressure data measured in the experiment.

[0017] S wj =(VS) wi +V w -G w ) / V (2)

[0018] Wherein: S wj —Reservoir water saturation on day j, dimensionless;

[0019] S wi —The original water saturation of the reservoir is dimensionless;

[0020] V—Reservoir volume reached by fracturing fluid, in meters. 3 ;

[0021] V w —Fracturing fluid usage, m 3 ;

[0022] G w —Cumulative water production, m 3 ;

[0023] S400. Using the effective output q data, the ideal output qideal after considering the dynamic capillary effect is calculated according to formula (3):

[0024] q ideal =q(1+τ*(S) w(j+1) +S wj ) / P c (3)

[0025] Where: q—effective output, m 3 / d;

[0026] q ideal m 3 / d;

[0027] P c —Capillary pressure, MPa;

[0028] τ—Dynamic capillary effect coefficient, MPa;

[0029] S500, using ideal output q ideal The cumulative output G is calculated using formula (4). p Then make ln(q) ideal / G p The relationship curve between ) and lnt is used to determine the value of parameter m in formula (5) by the slope of the curve:

[0030] G p =∑q ideal (4)

[0031]

[0032] Among them: G p —Cumulative gas production, m 3 ;

[0033] a—fitting parameters, d -1 ;

[0034] m — Fitting parameters, dimensionless;

[0035] The value of parameter a is determined by the curve intercept;

[0036] S600, Calculate the characteristic time t according to formula (6). am :

[0037]

[0038] Where: t am —Characteristic time, dimensionless;

[0039] S700, Predict the ideal output q according to formula (7) ideal :

[0040] q ideal =q1t am (7)

[0041] Where: q1 is the output on the first day, m 3 / d;

[0042] The predicted output is reduced from formula (3) to the actual output q after considering the dynamic capillary effect;

[0043] S800. Based on the predicted actual output q, the parameters β and n in formula (8) are obtained by fitting:

[0044]

[0045] Where: β—fitting parameter, d;

[0046] n—fitting parameters, dimensionless;

[0047] q0—Maximum production rate when wellhead pressure drops to 0, m 3 / d;

[0048] S900, Calculate the recoverable reserves EUR using formula (9);

[0049]

[0050] Where: Γ—gamma function;

[0051] EUR—Recoverable reserves, m 3 .

[0052] Furthermore, in step S300, the capillary pressure data includes the capillary pressure P experimentally measured in step S100. c And the dynamic capillary effect coefficient τ.

[0053] Furthermore, the initial data collection includes: q initial G w S wj P c 、τ.

[0054] The advantages of this invention are:

[0055] 1. The method proposed in this invention takes into account dynamic capillary pressure and introduces an original method for calculation in the model calculation. The gas production data obtained can fit well with the actual production data, and the predicted EUR is more accurate.

[0056] 2. The method provided by this invention can provide good predictions for data throughout the entire production cycle. In particular, it can avoid interference caused by various factors in the initial production data, so that the unstable initial production data has a smaller impact on EUR prediction. Attached Figure Description

[0057] Figure 1 In the example, 1 / q and A schematic diagram of the fitting relationship;

[0058] Figure 2 1n(q / G) p A schematic diagram showing the fitting relationship between ) and lnt;

[0059] Figure 3 For t am A schematic diagram of the fitting relationship between q and q;

[0060] Figure 4 Fit actual production data to the LYSD model;

[0061] Figure 5 The results are predictions from the LYSD model. Detailed Implementation

[0062] The present invention will be further described below with reference to embodiments. It should be noted that, in this document, terms such as "upper" and "lower" are used merely for the convenience of describing the drawings and are not intended to limit the direction in actual use, nor do they necessarily require or imply any such actual relationship or order between these entities or operations. Moreover, the terms "comprising," "including," or any other variations thereof are intended to cover non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements includes not only those elements but also other elements not expressly listed, or elements inherent to such a process, method, article, or apparatus.

[0063] According to the method for calculating gas production data using the LYSD model provided by this invention, a shale gas well in the Weiyuan block with a production time of 300 days was selected, and the known production data are shown in Table 1.

[0064] Table 1 Shale Gas Well Production Data

[0065]

[0066]

[0067] Using the field production data provided in Table 1, especially the raw production data q initial ,get and Relationship curves as follows Figure 1 The formula can be obtained. In the given condition, w = 0.076 and b = 0.0114. The value of parameter w is determined by the curve slope, and the value of b is determined by the curve intercept. Then, the relationship curve obtained by fitting is... Figure 1 (The black solid line in the middle) Corrects points with large deviations in the production data onto the curve, resulting in effective production data as shown in Table 2.

[0068] Table 2. Valid data on shale gas well production.

[0069]

[0070]

[0071] (3) The amount of fracturing fluid used on site is V w =4.723*10 4 m 3 The reservoir volume reached by the fracturing fluid is approximately 3*10. 5 m 3 The original water saturation of the reservoir was 0.15, and the formula S was used. wj =(V*S wi +V w -G w ) / V(2) Calculate the reservoir water saturation. From the experimentally measured capillary pressure data and dynamic capillary effect coefficient, obtain the capillary pressure P at each production time. c The dynamic capillary effect coefficient τ is shown in Table 3.

[0072] Table 3. Capillary pressure and dynamic capillary effect coefficient at various production times.

[0073]

[0074]

[0075]

[0076]

[0077]

[0078] Based on the data in Tables 2 and 3, take the formula q. ideal =q(1+τ*(S) w(j+1) +S wj ) / P c(3) The ideal yield (qideal(m)) after considering the dynamic capillary effect is calculated. 3 / d), through formula G p =∑q ideal (4) Calculate the cumulative output G p Make ln(q / G) p )and Relationship curves, such as Figure 2 As shown, the formula for determining the slope of a curve is... The value of parameter m is 1.0803, and the value of parameter a, determined by the curve intercept, is 0.9267.

[0079] According to the formula Calculate t am and make q and t am Relationship curves as follows Figure 3 As shown in Table 1, q1 = 26.9708 is determined from Table 1, and then the formula q... ideal =q1t am (7) and formula q ideal =q(1+τ*(S) w(j+1) +S wj ) / P c (3) Fit the actual yield, the results are as follows Figure 4 As shown; the predicted future output, the results are as follows. Figure 5 As shown, the gas production data calculated using the LYSD model fits the actual production data very well.

[0080] According to the formula The fitting parameters yielded n = 0.5447 and β = 123. And from the formula q... ideal =q(1+τ*(S) w(j+1) +S wj ) / P c (3) The calculated EUR is 172,543,700 m³. 3 .

[0081] The above description is merely a preferred embodiment of the present invention and is not intended to limit the present invention in any way. Although the present invention has been disclosed above with reference to preferred embodiments, it is not intended to limit the present invention. Any person skilled in the art can make some modifications or alterations to the above-disclosed technical content to create equivalent embodiments without departing from the scope of the present invention. Any simple modifications, equivalent changes, and alterations made to the above embodiments based on the technical essence of the present invention without departing from the scope of the present invention shall still be considered improvements to the technical solution of the present invention.

Claims

1. A method for analyzing recoverable reserves of a shale gas well considering dynamic capillary effect, characterized in that, Comprising the following steps: S100. Collect raw production data for the shale gas wells to be analyzed, and use the raw production rate q of the shale gas wells. initial Based on the linear flow stage under the initial constant bottom pressure production conditions, the reciprocal of the production rate and the half power of time have a linear relationship in the coordinate system, using the following formula (1): wherein: q initial — raw yield, m 3 / d; t - production time, d; w - fitting parameter, d 0.5 / m 3 ; b - fitted parameter, d / m 3 ; The relationship curve of formula (1) is fitted with the relationship curve, the slope of which is the value of the parameter w and the intercept of which is the value of the parameter b; S200, the relationship curve obtained by formula (1) is used to correct the points in the production data that deviate greatly from the curve to the relationship curve to obtain effective production data q; S300, according to the field fracturing fluid flowback volume, the reservoir water saturation is calculated by formula (2): S wj = (V * S wi + V w - G w ) / V (2) where: S wj - Reservoir water saturation on day j, dimensionless. S wi —reservoir original water saturation, dimensionless; V - Reservoir volume reached by the fracturing fluid, m 3 ; V w - Fracturing fluid amount, m 3 ; G w cumulative water production, m 3 ; S400, using the data of the effective yield q, the ideal yield q considering the dynamic capillary effect is calculated according to formula (3) ideal : q ideal = q(1 + τ*(S w(j+1) + S wj ) / P c ) (3) where: q - effective production, m 3 / d; q ideal —m 3 / d; P c - capillary pressure, MPa; τ - dynamic capillary effect coefficient, MPa; S500, using ideal output q ideal The cumulative output G is calculated using formula (4). p Then make ln(q) ideal / G p The relationship curve between ) and lnt is used to determine the value of parameter m in formula (5) by the slope of the curve, and the value of parameter a is determined by the intercept of the curve: G p =∑q ideal (4) wherein: G p cumulative gas production, m 3 ; a - fitting parameter, d -1 ; m - fitting parameter, dimensionless; S600, calculate the characteristic time t according to formula (6) am : where: t am — Characteristic time, dimensionless e - natural constant; S700, predict the ideal yield q based on the late data-free stage according to formula (7) ideal : q ideal = q1t am (7) wherein q1 is the yield of the first day, m 3 / d; The predicted production is reduced to the actual production q considering the dynamic capillary effect by formula (3); S800, according to the predicted actual production q, the parameters β and n in formula (8) are fitted: Where: β - fitting parameter, d; n - fitting parameter, dimensionless; q0 - maximum production rate at zero wellhead pressure drop, m3 / d 3 / d; S900, the recoverable reserves EUR are calculated by formula (9); Where: Γ - gamma function; EUR - recoverable reserves, m 3 .

2. The method of claim 1, wherein, The capillary pressure data in the step S300 include the capillary pressure P measured in the step S100 c and the dynamic capillary effect coefficient τ.

3. The method of claim 2, wherein, The contents of the preliminary data collection in step S100 include: q initial , G w , S wj , P c , τ.

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