A method for predicting and evaluating the volume and structural instability of erosion cavities in the annular gravel layer of a gravel-packed well

Abstract

The present application belongs to the technical field of oil and gas development and exploitation engineering in the industry of oil and natural gas development, and particularly relates to a method for predicting and evaluating the volume and structural instability of erosion cavities of a gravel packing annulus in a gravel packing well, which accurately estimates the limit void ratio of the annulus gravel packing layer by constructing a prediction model based on the annulus packing rate and the physical parameters of the packing material; simulates and predicts the void ratio of the gravel layer erosion cavities under a given production time based on the production fluid dynamics characteristics; further deduces the geometric parameters of the erosion cavities according to the predicted void ratio, proposes a gravel layer structural instability evaluation method, determines the instability critical condition and safety factor, and realizes the quantitative analysis of the stability of the annulus gravel layer and the grading determination of the instability risk.

Description

Technical Field

[0001] This invention belongs to the field of oil and gas development and extraction engineering technology in the oil and gas development industry, and specifically relates to a method for predicting and evaluating the volume and structural instability of erosion cavities in the annulus gravel layer of gravel-filled wells. Background Technology

[0002] Sand production is a common problem in the development of loose sandstone oil and gas reservoirs, easily leading to wellbore blockage, equipment wear, and reduced production capacity, severely impacting the stability and economic benefits of oil well production. Gravel packing for sand control, as a primary sand control measure, has been widely applied in emerging energy fields such as hydrate reservoir sand control, gas storage sand control, and deep oil and gas sand control. With extended production cycles, continuous scouring by formation fluids often causes erosion and particle migration in the gravel layer under high flow velocities or local disturbances, forming erosion cavities. Cavity expansion disrupts the integrity of the gravel layer, leading to structural instability, screen erosion, and sand control failure, ultimately resulting in severe sand production and reduced production.

[0003] Current gravel backfilling sand control technology mainly focuses on static parameters such as gravel gradation and backfill density in practical applications, lacking quantitative prediction methods for the impact of gravel layer erosion and voids on structural stability during dynamic production processes. Therefore, accurately predicting the void ratio of the gravel layer and quantitatively analyzing its stability are of significant engineering importance for optimizing sand control process parameters and ensuring safe on-site operation. Summary of the Invention

[0004] To address the technical challenge of erosion, void formation, and structural instability in the annular gravel layer during long-term production after gravel packing sand control in loose sandstone oil and gas reservoirs, this invention constructs a predictive model based on the annular packing ratio and the physical properties of the packing material to accurately estimate the ultimate void ratio of the annular gravel packing layer. Based on the characteristics of production fluid dynamics, it simulates and predicts the void ratio of gravel layer erosion voids under a given production time. Based on the predicted void ratio, it further derives the geometric parameters of the erosion voids, proposes a method for evaluating the structural instability of the gravel layer, determines its critical instability conditions and safety factor, and achieves quantitative analysis of the stability of the annular gravel layer and classification of instability risks.

[0005] A method for predicting and evaluating the volume and structural instability of erosion voids in the annulus of gravel-filled wells includes the following steps:

[0006] S1, based on the annular filling rate Predicting the ultimate void ratio of annular gravel-filled layers based on the physical properties of the filling material R cvmax :

[0007] After applying gravel packing sand control technology to loose sandstone oil and gas wells, the annular gravel layer is prone to erosion and porosity instability. A method based on the filling ratio is proposed. Limiting void ratio of filling material properties R cvmax Prediction method: First, a gravel accumulation correction factor is introduced. To correct for differences in packing porosity; secondly, by adjusting the median particle size of the filling material. d g Compared with reference particle size d ref The ratio and particle sphericity d s The influence factors of particle size and morphology on skeleton stability were constructed; the final overall filling rate was determined. Stacking correction factor The geometric factor of the filling material determines the limiting deficit rate. R cvmax Prediction formula.

[0008] S101. Calculate the packing correction factor based on the gravel packing morphology and the physical properties of the backfill material. Influencing factors of particle size and sphericity F p

[0009] Based on the particle packing theory, and considering the packing porosity... rate Porosity with the theoretical closest packing Based on the comparative relationship, it is proposed to use the positive coefficient of pile repair. A calculation method for characterizing the porosity of gravel-filled layers; for quantitatively describing the median grain size of gravel. d g Compared with reference particle size d ref The ratio and particle sphericity d s The study proposes to calculate the influencing factors of particle size and sphericity by using relative particle size and morphological parameters. F p The calculation method.

[0010] The actual gravel deposits within the annulus are not densely packed; the actual packing porosity is... Typically much higher than the theoretical maximum dense packing porosity. Therefore, a stacking correction factor is introduced. Through actual packing porosity Porosity with the theoretical closest packing The ratio of the two values ​​is used to characterize the density of gravel accumulation; the accumulation correction factor. The larger the value, the denser the gravel particle structure. The particle size and sphericity within the gravel layer significantly affect the stability of the annular gravel layer framework. This invention introduces influencing factors for particle size and sphericity. F pThe relative grain size ratio and morphological parameters are used to characterize the variation trend of gravel layer skeleton stability, which is used to represent the skeleton stability of gravel layers within the annulus. Grain size and sphericity are the influencing factors. F p The larger the value, the more stable the gravel layer.

[0011] (1)

[0012] (2)

[0013] In the formula, This is the stacking correction factor, which is dimensionless. This represents the actual packing porosity. The theoretically closest packing porosity is taken as 0.46; F p is a dimensionless factor influencing particle size and sphericity; d g The median particle size of the filling material is in mm. d ref For reference particle size, in mm, take 0.6; d s The sphericity of the particles is dimensionless.

[0014] S102, Based on the stacking correction factor Influencing factors of particle size and sphericity F p Predicting the maximum deficit ratio R cvmax ：

[0015] To predict the ultimate deficit rate of the hole R cvmax Taking into account the filling rate Stacking correction factor Influencing factors of particle size and sphericity F p Establish the extreme deficit ratio R cvmax The prediction formula.

[0016] Gravel packing correction factor Influence factors on particle size and sphericity F p In summary, the maximum deficit ratio is obtained. R cvmax The prediction formula is:

[0017] (3)

[0018] In the formula, R cvmax The maximum deficit ratio is % The filling rate is %; when the particle size is large or the sphericity is good, the packing is prone to slippage, and the ultimate void ratio is... R cvmax Increase.

[0019] S2. Simulate and predict the deficit rate for a given production time based on production flow conditions. R cv :

[0020] The extreme deficit ratio proposed in step S1 R cvmax Based on the prediction method, this paper addresses the evolution of annular gravel layer erosion voids caused by fluid scouring during the production process of gravel-packed wells, and predicts the dynamic deficit rate of gravel layer erosion evolution during production. This step is based on the ultimate deficit rate. R cvmax By combining the production volume Q and fluid properties, the volume of gravel layer erosion cavities within a certain production cycle is predicted, and a method for predicting the cavity deficit rate based on production flow conditions and production time is constructed.

[0021] To quantitatively represent the relationship between gravel layer erosion and porosity expansion rate, an instability rate index is introduced. S cv Instability rate index S cv It is a velocity characteristic parameter used to describe the evolution of annular gravel-filled layers from a steady state to an unstable state under the action of production fluids, and comprehensively reflects the annular flow velocity. Fluid viscosity Fluid density r f With the density of the filling material r g Factors such as particle migration and erosion accelerate the process; the higher the value, the faster the gravel layer develops from an intact state to instability.

[0022] (4)

[0023] (5)

[0024] In the formula, The annular velocity is in m / s; h s Perforation density, 1 / m; Q For the liquid production rate, m 3 / s; H The filling length is in meters (m). D k Where is the perforation diameter, in meters (m); S cv The instability rate exponent is dimensionless; To calibrate the annular velocity, m 3 / s, take =0.001m / s; d g0 To calibrate the particle size of the filling material, in mm, take... d g0 =0.6mm; S c The epidermal coefficient is dimensionless. S c0 To calibrate the epidermal coefficient, which is dimensionless, take... S c0 =1; To calibrate the fluid viscosity, in mPa·s, take... =0.5587 mPa·s; The viscosity of the fluid is given in mPa·s. r f Fluid density, kg / m³ 3 ; r g The density of the filling material is kg / m³. 3 .

[0025] Based on a given production time t p with instability rate index S cv The deficit ratio can be obtained in the end. R cv Relationship over time:

[0026] (6)

[0027] In the formula, R cv The deficit ratio is % t p Production time, in days (d).

[0028] S3, Based on the deficit ratio R cv Predicting the geometric parameters of erosion cavities and evaluating structural instability:

[0029] The deficit ratio obtained based on S2 R cv To further utilize the deficit ratio R cv Quantitative prediction of the geometric characteristics of pores in gravel layers by establishing void ratios R cv Volume of the annular filling section By establishing the correspondence between its geometric parameters and the time-varying geometric parameters of the pores, the equilibrium relationship of the gravel arch structure is established by combining the limit equilibrium arch theory. Based on this, a stability index based on the safety factor is proposed to judge the safety margin and potential instability risk of the wellbore gravel layer under actual production conditions.

[0030] S301. Predicting dynamic geometric parameters of erosion voids based on the deficit rate:

[0031] For ease of calculation, this invention approximates erosion cavities as rotating ellipsoids, and the dynamic cavity deficit rate is obtained based on S2. R cv To quantitatively predict the dynamic geometric parameters of erosion holes based on production time.

[0032] According to the well diameter D h , sieve tube diameter D s With filling length H Calculate the volume of the annular filling section :

[0033] (7)

[0034] In the formula, The volume of the annular filling section is m. 3 ; H The filling length is in meters (m). D h , D s These are the diameters of the wellbore and the screen pipe, respectively, in meters (m).

[0035] Approximating the erosion cavity as a rotating ellipsoid, based on the known void ratio in S2... R cv Then, the dynamic erosion cavity volume based on production time can be obtained, assuming the cross-section is elliptical and the major axis is... c The minor axis is Let the ratio of the major axis to the minor axis of the cross-section of the eroded cavity be... k Substituting these values ​​into the volume formula yields the relationship between the geometric parameters of the erosion cavity and time.

[0036] (8)

[0037] (9)

[0038] (10)

[0039] In the formula, V e For the volume of the erosion cavity, m 3 ; Let m be the minor axis of the cross-section of the erosion cavity; c Let m be the major axis of the cross-section of the erosion cavity; k Let be the ratio of the major axis to the minor axis of the cross-section of the eroded cavity, dimensionless, and taken as . k =1.63.

[0040] S302. Calculate the risk assessment index for void instability based on the limit equilibrium arch theory and the deficit rate. F s :

[0041] To quantitatively determine the critical condition for void instability, this invention, based on limit equilibrium theory, calculates the ultimate bearing capacity of the natural arched gravel structure at the top of the void and establishes a comparative relationship between the two by combining the effective stress of the overlying gravel layer. Based on this comparative relationship and the void deficit rate, the ability of the gravel structure to resist instability is quantitatively characterized, and an instability evaluation index is constructed. F s The calculation method.

[0042] Assuming the gravel structure at the top of the hole forms a natural arch support structure, the ultimate vertical bearing stress of the arch structure is... s cr That is, the ultimate stress of the top plate of the hole; the effective vertical stress generated by the gravel layer covering the top of the hole is s v According to the limit equilibrium arch theory, they are expressed as follows:

[0043] (11)

[0044] (12)

[0045] In the formula, s cr The ultimate vertical bearing stress of the arch structure is given in Pa. s v The effective vertical stress generated by the gravel layer overlying the cavity, Pa; g The acceleration due to gravity is m / s². 2 Generally take g =9.8m / s 2 To ensure the stability of the hole structure, the following conditions must be met. s v < s cr .

[0046] Introducing instability risk assessment indicators F s Instability risk assessment indicators F sIt refers to the ratio of the ultimate bearing capacity that the top of the gravel layer or the arched structure with holes can withstand to the effective stress it actually bears. It is used to measure the ability of the gravel layer structure to resist instability and is a core indicator for instability risk assessment and engineering design.

[0047] (13)

[0048] In the formula, F s It is a dimensionless indicator for assessing instability risk.

[0049] According to the instability risk assessment indicators F s A standard for classifying instability risk levels is established, as detailed in the table below. The instability risk assessment indicators are... F s Reflecting the ability of the gravel structure to resist instability, if F s If the value is less than 1, it indicates that the gravel arch structure at the top of the hole cannot stably bear its own overlying stress, and there is a significant risk of structural instability. 1 ≤ F s <1.2 indicates that the porous structure is in a critical state of instability. F s ≥1.2, the porous structure has no risk of instability.

[0050] Table 1. Classification Criteria for Instability Risk Levels

[0051]

[0052] The filling material is gravel.

[0053] Compared with the prior art, the present invention has the following beneficial effects:

[0054] 1. The method for predicting and evaluating the volume and structural instability of erosion cavities in the gravel layer of the annulus of gravel-filled wells provided by this invention introduces gravel physical property parameters and wellbore geometric parameters to establish a quantitative evaluation model. This model can accurately reflect the influence of the compactness and pore structure characteristics of the gravel filling layer on the ultimate void rate of the gravel layer, and achieve a more accurate prediction of the ultimate void rate of the gravel layer, providing technical support for sand control design and construction parameter optimization.

[0055] 2. This invention proposes for the first time a method for predicting the volume of erosion cavities based on the coupling of production flow conditions and production time. It can dynamically simulate the formation and expansion process of erosion cavities under different production stages, quantitatively predict the evolution law of cavity volume and deficit rate, and realize the whole-process prediction and analysis of instability risk.

[0056] 3. The method for predicting and evaluating the volume and structural instability of erosion cavities in the annular gravel layer of gravel-filled wells provided by this invention introduces the geometric parameters of erosion cavities and the theory of ultimate arch structure stability to establish a criterion for the structural instability of the gravel layer. This method can quantitatively analyze the stability of the annular sand control layer and achieve graded judgment of instability risk.

[0057] 4. The method for predicting and evaluating the volume and structural instability of erosion cavities in the annular gravel layer of gravel-filled wells provided by this invention can be used as a means of dynamic monitoring and risk warning of gravel layers throughout the entire production process of oil and gas wells. It enables real-time assessment and optimized management of sand control systems, reduces maintenance and repair costs, and enhances the long-term stable production capacity of oil wells, thus having outstanding engineering application value and economic benefits. Attached Figure Description

[0058] Figure 1 The erosion morphology of the gravel layer after the physical simulation experiment of the annular gravel layer erosion in Example 1;

[0059] Figure 2 The image shows the erosion morphology of the gravel layer after the physical simulation experiment of the annular gravel layer erosion in Example 2. Detailed Implementation

[0060] Example 1

[0061] A method for predicting and evaluating the volume and structural instability of erosion cavities in the annular gravel layer of gravel-filled wells is proposed. For typical sandstone oil and gas reservoir sand control wellbore structures, quantitative predictions of the void ratio of the annular gravel layer and the geometric morphology of erosion cavities are carried out, and the stability of the gravel structure at the top of the cavities is systematically analyzed based on the ultimate arch structure theory.

[0062] 1) Prepare basic data

[0063] The basic data used for simulation and prediction of erosion instability of gravel-filled annulus in typical gravel-filled wells are shown in Table 1.

[0064] Table 2. Basic data used for predicting erosion voids in typical gravel-filled wells.

[0065]

[0066] 2) Calculation Results

[0067] a. Calculate the stacking correction factor Influence factors on particle size and sphericity F p ,have to =0.54, F p =0.95; and according to and F p Calculate the limit deficit ratio Rcvmax ,have to R cvmax =20.16%.

[0068] b. Calculate the volume of the annular filling section based on the diameter of the wellbore and screen pipe and the length of the filling section. have to =5.49m 3 ; Calculate the annular velocity have to =0.00424m / s, substitute into the calculation of the instability rate exponent S cv have to S cv =1.34; Based on the known production time, the current deficit rate of this well can be calculated as follows: R cv =20.05%.

[0069] c. Calculate the volume of erosion voids based on the void ratio. V e Geometry parameters of erosion holes c V e =1.1m 3 , =0.54m, c=0.88m; and calculate the ultimate vertical bearing capacity based on the ultimate equilibrium arch theory and the void ratio. s cr The effective vertical stress generated by the gravel layer covering the top of the hole is s v have to s cr =2750Pa s v =755Pa; finally, based on the deficit ratio and s cr and s v Calculate instability risk assessment indicators F s have to F s =3.13.

[0070] The results obtained using this invention are shown in Table 3.

[0071] Table 3. Calculation results of predicted erosion voids in typical gravel-filled wells

[0072]

[0073] According to the dynamic curve of the calculation results, the ultimate void ratio of the gravel backfill layer under this working condition is 20.16%, indicating that the backfill layer structure suffers a certain degree of stability loss under long-term scouring. The corresponding production time is 30.00 days, and the void ratio of the backfill layer is 20.05%, indicating a high degree of scouring damage to the pore structure. The instability risk assessment index is 3.13, which meets the requirements of the engineering design, indicating no risk of instability.

[0074] To verify the accuracy of the above prediction results, a simulation experiment was conducted. The experimental steps are as follows: To verify the accuracy of the method for predicting the dynamic geometric parameters of erosion holes based on the void ratio, a physical simulation experiment of annular gravel layer erosion was carried out. The experimental steps are as follows:

[0075] (1) Using a radial flow displacement experimental device, the annulus was filled with gravel material consistent with the field and pre-compacted to ensure the stability of the initial annulus gravel layer structure.

[0076] (2) Simulate the process of formation fluid entering the wellbore through a flow control system.

[0077] (3) A continuous flushing experiment was conducted under constant flow rate (consistent with the liquid production Q in the basic data). The flushing time was set to 30 days, during which the flow rate, pressure difference and sand production were recorded.

[0078] (4) After the experiment, the morphology of the erosion cavities inside the annular gravel layer was obtained by layer-by-layer cutting, and the volume and geometric parameters of the erosion cavities were calculated.

[0079] After 30 days of scouring, the volume of the eroded holes V e It is 0.876m 3 The major axis c of the erosion cavity is 0.815m; the minor axis of the erosion cavity... It is 0.50m; the eroded annular gravel layer is as follows: Figure 1 As shown in the figure, the erosion holes are mainly concentrated in the local area of ​​the screen tube. The holes are distributed in an ellipsoidal shape. The overall bearing structure of the gravel layer is intact, and there is no collapse or instability.

[0080] Example 2

[0081] The basic data for this embodiment is shown in Table 4.

[0082] Table 4. Basic data used for predicting erosion voids in typical gravel-filled wells.

[0083]

[0084] The calculation results are shown in Table 5.

[0085] Table 5. Calculation results of predicted erosion voids in typical gravel-filled wells

[0086]

[0087] To verify the accuracy of the above prediction results, a simulation experiment was conducted, and the experimental procedure was the same as in Example 1.

[0088] After 60 days of scouring, the volume of the eroded cavity V e It is 0.381m 3 The major axis c of the cross-section of the erosion cavity is 0.62m; the minor axis c of the cross-section of the erosion cavity is... It is 0.38m; the eroded annular gravel layer is as follows: Figure 2 As shown in the figure, the erosion holes are mainly concentrated in the local area of ​​the screen tube. The holes are distributed in an ellipsoidal shape. The overall bearing structure of the gravel layer is intact, and there is no collapse or instability.

Claims

1. A method for predicting and evaluating the volume and structural instability of erosion voids in the annulus of gravel-filled wells, characterized in that, Includes the following steps: S1, based on the annular filling rate Predicting the ultimate void ratio of annular gravel-filled layers based on the physical properties of the filling material R cvmax : S101. Calculate the packing correction factor based on the gravel packing morphology and the physical properties of the backfill material. Influencing factors of particle size and sphericity F p : (1) (2) In the formula, The packing correction factor is dimensionless. This represents the actual packing porosity. This represents the theoretically closest packing porosity. F p is a dimensionless factor influencing particle size and sphericity; d g The median particle size of the filling material is in mm. d ref Reference particle size, mm; d s The sphericity of the particles is dimensionless. S102, Based on the stacking correction factor Influencing factors of particle size and sphericity F p Predicting the maximum deficit ratio R cvmax ： (3) In the formula, R cvmax The maximum deficit ratio is % The filling rate is %; S2. Simulate and predict the deficit rate for a given production time based on production flow conditions. R cv : （4） （5） In the formula, The annular velocity is in m / s; h s Perforation density, 1 / m; Q For the liquid production rate, m 3 / s; H The filling length is in meters (m). D k Where is the perforation diameter, in meters (m); S cv The instability rate exponent is dimensionless; To calibrate the annular velocity, m 3 / s; d g0 To calibrate the particle size of the filling material, in mm; S c The epidermal coefficient is dimensionless. S c0 The epidermal coefficient is dimensionless; To calibrate the fluid viscosity, in mPa·s; Where is the fluid viscosity, mPa·s; ρ f Fluid density, kg / m³ 3 ; ρ g The density of the filling material is kg / m³. 3 ; Based on production time t p with instability rate index S cv The deficit ratio can be obtained in the end. R cv Relationship over time: （6） In the formula, R cv The deficit ratio is % t p Production time, in days; S3, Based on the deficit ratio R cv Predicting the geometric parameters of erosion cavities and evaluating structural instability: S301. Predicting dynamic geometric parameters of erosion voids based on the deficit rate: （7） In the formula, The volume of the annular filling section is m. 3 ; H The filling length is in meters (m). D h , D s These are the diameters of the wellbore and the screen pipe, respectively, in meters; (8) （9） （10） In the formula, V e For the volume of the erosion cavity, m 3 ; Let m be the minor axis of the cross-section of the erosion cavity; c Let m be the major axis of the cross-section of the erosion cavity; k is the ratio coefficient between the major and minor axes of the cross-section of the erosion cavity, which is dimensionless; S302. Calculate the risk assessment index for void instability based on the limit equilibrium arch theory and the deficit rate. F s : （11） （12） In the formula, σ cr The ultimate vertical bearing stress of the arch structure is given in Pa. σ v The effective vertical stress generated by the gravel layer overlying the cavity, Pa; g The acceleration due to gravity is m / s². 2 ; （13） In the formula, F s It is a dimensionless indicator for assessing instability risk. According to the instability risk assessment indicators F s Establish standards for classifying instability risk levels: F s <1 indicates a significant risk of structural instability; 1≤ F s <1.2 indicates that the porous structure is in a critical state of instability; F s ≥1.2, the porous structure has no risk of instability.

2. The method for predicting and evaluating the volume and structural instability of erosion voids in the annulus gravel layer of gravel-filled wells according to claim 1, characterized in that, Take 0.

46.

3. The method for predicting and evaluating the volume and structural instability of erosion voids in the annular gravel layer of gravel-filled wells according to claim 1, characterized in that, d ref Take 0.

6.

4. The method for predicting and evaluating the volume and structural instability of erosion voids in the annular gravel layer of gravel-filled wells according to claim 1, characterized in that, Take 0.001 m / s.

5. The method for predicting and evaluating the volume and structural instability of erosion voids in the annular gravel layer of gravel-filled wells according to claim 1, characterized in that, d g0 Take 0.6mm.

6. The method for predicting and evaluating the volume and structural instability of erosion voids in the annular gravel layer of gravel-filled wells according to claim 1, characterized in that, S c0 Take 1.

7. The method for predicting and evaluating the volume and structural instability of erosion voids in the annular gravel layer of gravel-filled wells according to claim 1, characterized in that, Take 0.5587 mPa·s.

8. The method for predicting and evaluating the volume and structural instability of erosion voids in the annular gravel layer of gravel-filled wells according to claim 1, characterized in that, k Take 1.

63.

9. The method for predicting and evaluating the volume and structural instability of erosion voids in the annular gravel layer of gravel-filled wells according to claim 1, characterized in that, g Take 9.8 m / s 2 .

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