Method for predicting recoverable reserves of horizontal well of multi-parameter coupled thin-layer bottom water reservoir

Abstract

The invention relates to a method for predicting recoverable reserves of a horizontal well of a multi-parameter coupled thin-layer bottom water reservoir. The method comprises the following steps: determining a plurality of factors influencing the recoverable reserves of the horizontal well of the thin-layer bottom water reservoir and a numerical value change range of each factor; establishing a thin-layer bottom water reservoir mechanism model and a horizontal well model, setting a horizontal well working system, and controlling the numerical value change of a single factor and the remaining factors to remain unchanged to obtain recoverable reserves under the influence of the single factor; according to the recoverable reserves under the influence of the single factors, selecting factors with the influence on the recoverable reserves reaching a set quantized value, and establishing a mathematical relationship between the recoverable reserves and each selected single factor; according to the mathematical relationship between the recoverable reserves and each selected single factor, establishing a mathematical relationship between the recoverable reserves and the selected multi-factor coupling by adopting a preset function relationship; and inputting numerical values of the selected multiple factors, and calculating the recoverable reserves according to a mathematical relationship between the recoverable reserves and the selected multiple factors.

Description

Technical Field

[0001] The present invention relates to the technical field of oil and gas exploration and development, and in particular to a multi-parameter coupled method for predicting recoverable reserves of horizontal wells in thin-layer bottom water reservoirs. Background Art

[0002] Thin-layer bottom-water reservoirs are usually developed using horizontal wells, and the recoverable reserves of the wells need to be predicted during the development process.

[0003] Existing techniques use empirical formulas to predict recoverable reserves in wells. Practical research has found that these formulas have a high error rate. For example, the formula proposed by Shu Jie (Shu Jie, Research on Factors Affecting Recovery Efficiency in Edge-Bottom Water Reservoirs, Southwest Petroleum University, 2015) has an error rate of 36%.

[0004] Therefore, it is necessary to provide a new rapid prediction method with higher accuracy. Summary of the Invention

[0005] The present invention provides a multi-parameter coupled method for predicting recoverable reserves of horizontal wells in thin-layer bottom water oil reservoirs, which can predict recoverable reserves of wells and areas more quickly and accurately than existing empirical formulas.

[0006] To achieve the above object, the present invention adopts the following technical solutions:

[0007] In a first aspect, the present application provides a multi-parameter coupled method for predicting recoverable reserves of horizontal wells in thin-layer bottom water reservoirs, comprising:

[0008] S1, determine the multiple factors that affect the recoverable reserves of horizontal wells in thin bottom water reservoirs and the range of each factor;

[0009] S2, establish a thin bottom water reservoir mechanism model and a horizontal well model, set a horizontal well working system, and control the value of a single factor while keeping the other factors unchanged to obtain the recoverable reserves under the influence of a single factor;

[0010] S3, based on the recoverable reserves under the influence of a single factor, select factors whose influence on the recoverable reserves reaches a set quantitative value, and establish a mathematical relationship between the recoverable reserves and each selected single factor;

[0011] S4, based on the mathematical relationship between recoverable reserves and each selected single factor, a preset functional relationship is used to establish a mathematical relationship between recoverable reserves and the selected multiple factors;

[0012] S5, inputting the numerical values of the selected multiple factors, and calculating the recoverable reserves based on the mathematical relationship between the recoverable reserves and the selected multiple factors.

[0013] In one implementation, in S1, the multiple factors include: reservoir environment, structural factors, reservoir factors, fluid properties, reservoir parameters, well parameters, and production control factors.

[0014] In one implementation, the step S2 specifically includes:

[0015] According to the characteristics of the thin bottom water reservoir under study, a reservoir model is established in the numerical simulation software, fluid parameters, reservoir initial conditions, relative permeability curves are set, a horizontal development well model is established, and the well working system is set;

[0016] Control the value change of one factor and simulate the recoverable reserves of horizontal wells under different values of the factor while keeping other factors unchanged; and complete the same operation for each factor.

[0017] In one implementation, the S3 includes:

[0018] The factors that affect the reaching of the set quantitative value are determined based on the variation of recoverable reserves with each influencing factor. The power function is preferably used to express the mathematical relationship between recoverable reserves and each selected factor:

[0019] N R =ax b

[0020] If it is not suitable to be represented by a power function, a polynomial is used. The degree of the polynomial is generally not more than 3:

[0021] N R =a1x k +a2x k-1 +……+a k x 1 +a k+1

[0022] Among them, N R is the recoverable reserves; a and b are unknown coefficients; x is the influencing factor; k is the degree of the polynomial.

[0023] In one implementation, in S4, the mathematical relationship between recoverable reserves and the selected multi-factor coupling is:

[0024]

[0025] Among them, x1~x m are factors that have a polynomial relationship with recoverable reserves; k1~k m is the degree of the polynomial; x m+1 ~x n are factors that have a power function relationship with recoverable reserves; a, b 1_1 ~b 1_k1 、b2_1 ~b 2_k2 ,……,b m+1 ~b n is the undetermined coefficient.

[0026] The present invention has the following advantages due to the adoption of the above technical solution:

[0027] 1. The obtained prediction formula can be used to calculate the recoverable reserves of horizontal wells in any thin bottom water reservoir without conducting numerical simulation, which is simple and fast.

[0028] 2. Compared with the previous recoverable reserves prediction formula using similar polynomials, the formula established by the present invention is more reasonable and has higher calculation accuracy. BRIEF DESCRIPTION OF THE DRAWINGS

[0029] Figure 1 Schematic diagram of initial oil saturation of a reservoir mechanism model provided by one embodiment of the present invention;

[0030] Figure 2 This is a schematic diagram of the relationship between crude oil properties and pressure provided by one embodiment of the present invention;

[0031] Figure 3 This is a schematic diagram of the relationship between natural gas properties and pressure provided by one embodiment of the present invention;

[0032] Figure 4 This is a schematic diagram of the relationship between recoverable reserves and various influencing factors provided by one embodiment of the present invention;

[0033] Figure 5 1. It is a schematic diagram comparing the calculation results of the polynomial-like formula provided in one embodiment of the present invention and the formula of the present invention;

[0034] Figure 6 3. It is a schematic diagram comparing the calculation errors of the polynomial-like formula provided in one embodiment of the present invention and the formula of the present invention. DETAILED DESCRIPTION

[0035] To make the objectives, technical solutions, and advantages of the embodiments of the present invention more clear, the technical solutions of the embodiments of the present invention will be clearly and completely described below in conjunction with the accompanying drawings of the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the described embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field are within the scope of protection of the present invention.

[0036] In response to the defects and problems of the existing technology, this application provides a multi-parameter coupled method for predicting recoverable reserves of horizontal wells in thin-layer bottom water reservoirs, including:

[0037] S1, determine the multiple factors that affect the recoverable reserves of horizontal wells in thin bottom water reservoirs and the range of each factor;

[0038] S2, establish a thin bottom water reservoir mechanism model and a horizontal well model, set a horizontal well working system, and control the value of a single factor while keeping the other factors unchanged to obtain the recoverable reserves under the influence of a single factor;

[0039] S3, based on the recoverable reserves under the influence of a single factor, select factors whose influence on the recoverable reserves reaches a set quantitative value, and establish a mathematical relationship between the recoverable reserves and each selected single factor;

[0040] S4, based on the mathematical relationship between recoverable reserves and each selected single factor, a preset functional relationship is used to establish a mathematical relationship between recoverable reserves and the selected multiple factors;

[0041] S5, inputting the numerical values of the selected multiple factors, and calculating the recoverable reserves based on the mathematical relationship between the recoverable reserves and the selected multiple factors.

[0042] The above method is described below in a more detailed embodiment with reference to more drawings.

[0043] based on Figures 1 to 6 In a more detailed embodiment, a method for quickly predicting recoverable reserves of horizontal wells in thin-layer bottom water reservoirs with high accuracy is provided, comprising the following steps:

[0044] Step 1: Determine the factors that may affect recoverable reserves and the range of factors' changes.

[0045] Specifically, in an oilfield, the sand body is thin, the porosity and permeability are high, and edge and bottom water are developed. The viscosity of crude oil in different reservoirs varies greatly, and horizontal wells are usually deployed to rely on bottom water to drive oil production. Based on the characteristics of the oilfield and the development experience of similar oilfields, the factors and their ranges that may have a significant impact on recoverable reserves are determined: oil column height (less than 12m), formation crude oil viscosity (10mPa·s~350mPa·s), reservoir vertical permeability (less than 3000mD), water body multiple (less than 5), horizontal well length (about 300m), target daily oil production (less than 100m 3 / d).

[0046] Step 2: Create Figure 1 The reservoir mechanism model and development well model shown in the figure set the well working system and simulate the recoverable reserves under the change of a single influencing factor by controlling variables.

[0047] The above step 2 specifically includes:

[0048] Establish reservoir models: Numerical simulation software was used to create multiple reservoir models with a plane size of 500m × 500m, a grid size of 10m × 10m × 0.5m, and a bottom elevation of -1200m. The model height was equal to the oil column height. Homogenization parameters were set to a porosity of 0.30, a horizontal permeability of 3000mD, and vertical permeability varied as needed. The initial oil saturation was 0.76, the irreducible water saturation was 0.24, and the residual oil saturation was 0.26.

[0049] Establish a water layer model: add a water body close to the bottom of the entire oil layer model. The thickness of the water body is equal to the oil column height multiplied by the water body multiple. The porosity is 0.3 and the permeability is equal to the vertical permeability of the oil layer.

[0050] Set the fluid parameters and reservoir initial conditions: the properties of crude oil and natural gas at reservoir temperature are as follows: Figure 2 、 Figure 3 As shown, the original formation pressure at an altitude of -1200m is 12MPa.

[0051] Set relative permeability curve and rock compressibility: The relative permeability data of oil-water and gas-water are shown in Table 1 and Table 2. The rock compressibility coefficient is 3.06×10 -2 MPa -1 .

[0052] Table 1 Oil-water relative permeability

[0053] <![CDATA[S w ]]> <![CDATA[K rw ]]> <![CDATA[K ro ]]> 0.24 0 1 0.29 0.0003 0.8097 0.34 0.0021 0.6395 0.39 0.0066 0.4894 0.44 0.0148 0.3594 0.49 0.0278 0.2494 0.54 0.0464 0.1595 0.59 0.0718 0.0896 0.64 0.1047 0.0398 0.69 0.1459 0.0099 0.74 0.1965 0

[0054] Table 2 Gas-water relative permeability

[0055] <![CDATA[S w ]]> <![CDATA[K rw ]]> <![CDATA[K rg ]]> 0.00 0 1 0.04 0.003 0.771 0.07 0.009 0.562 0.11 0.019 0.346 0.12 0.027 0.204 0.20 0.057 0.094 0.31 0.095 0.052 0.35 0.131 0.027 0.38 0.163 0.015 0.42 0.230 0.005 0.68 1 0

[0056] Establish a production well: establish a horizontal well in the center of the top of the oil layer. The well length varies according to needs, and the entire well section is perforated.

[0057] Set up the working system: the target oil production of the production well will change according to the needs, and the maximum liquid production is set to 400m 3 / d, set the shut-in condition to be when the water cut reaches 98% or the oil production drops to 5m 3 / d.

[0058] Select a certain influencing factor and continuously change its value while keeping other factors unchanged. Simulate the recoverable reserves of the production well under different values of this factor. Other influencing factors that remain unchanged are set according to Table 3. Repeat the above operation for each influencing factor.

[0059] Table 3 Values of various influencing factors

[0060] Influencing factors Value when changing Value when unchanged Oil column height / m 4，6，8，10 8 Water body multiples 1，2，3，4 2 Formation crude oil viscosity / (mPa·s) 20，50，100，350 100 Vertical permeability / mD 0.05，0.1，0.2，0.5 0.1 Horizontal well length / m 200，250，300，350 300 <![CDATA[Target daily oil production / (m 3 / d)]]> 20，40，60，80 60

[0061] Step 3: Based on the simulation results, select factors whose impact on recoverable reserves reaches the set quantitative value, and determine the mathematical relationship between recoverable reserves and each selected factor.

[0062] The above step three includes:

[0063] Observe as Figure 4 The graph showing the changes in recoverable reserves with various influencing factors shows that the oil column height, formation crude oil viscosity, vertical permeability, and horizontal well length have significant effects, while the water body multiple and target daily oil production have no significant effects.

[0064] Determine the mathematical relationship between recoverable reserves and each selected factor:

[0065] N R =aH b

[0066] N R =aμ b

[0067]

[0068] N R =aL+b

[0069] Among them, N R is recoverable reserves, 10 4 m 3 ; H is the oil column height, m; μ is the formation crude oil viscosity, mPa·s; K v is the vertical permeability, mD; L is the horizontal well length, m; a and b are unknown coefficients.

[0070] Step 4: Based on the relationship between recoverable reserves and each selected factor, establish a recoverable reserves formula that considers the influence of multiple factors.

[0071] The above step 4 includes:

[0072] The formula for predicting recoverable reserves considering multiple factors is as follows:

[0073]

[0074] The recoverable reserves under different conditions obtained by numerical simulation are fitted with the model, and the undetermined coefficient values are determined to obtain the recoverable reserves prediction formula:

[0075]

[0076] If the prediction formula still uses the commonly used polynomial-like formula, its form is:

[0077]

[0078] The recoverable reserves simulation value is fitted with the model to obtain the recoverable reserves prediction formula:

[0079]

[0080] Comparison of the calculation results and errors of the polynomial formula and the formula of the present invention (such as Figure 5 、 6 As shown in the figure, it can be seen that the difference between the recoverable reserves calculation results using the formula of the present invention and the numerical simulation results is smaller, with an average error of only 4.4% and a maximum of less than 20%. However, the error calculated using the polynomial-like formula is an average of 9.6%, and the error of some data points is very large, with the maximum error exceeding 130%.

[0081] Step 5: Calculate the recoverable reserves of horizontal wells in thin-layer bottom water reservoirs using the established formula for predicting recoverable reserves without conducting numerical simulation.

[0082] In a specific embodiment of the present invention, a thin bottom-water reservoir has an oil column height of 10 m, a crude oil viscosity of 100 mPa·s, a vertical permeability of 300 mD, and a horizontal well length of 400 m. Substituting these parameters into the recoverable reserves prediction model:

[0083]

[0084] Among them, N R is recoverable reserves, 10 4 m 3 ; H is the oil column height, m; μ is the formation crude oil viscosity, mPa·s; K v is the vertical permeability, mD; L is the horizontal well length, m.

[0085] The calculated recoverable reserves of the horizontal well are 3.89×10 4 m 3 .

[0086] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention, rather than to limit it. Although the present invention has been described in detail with reference to the aforementioned embodiments, those skilled in the art should understand that they can still modify the technical solutions described in the aforementioned embodiments, or make equivalent replacements for some of the technical features therein. However, these modifications or replacements do not deviate the essence of the corresponding technical solutions from the spirit and scope of the technical solutions of the various embodiments of the present invention.

Claims

1. A multi-parameter coupled method for predicting recoverable reserves of horizontal wells in thin-layer bottom water reservoirs, characterized in that: include: S1, determine the multiple factors that affect the recoverable reserves of horizontal wells in thin bottom water reservoirs and the range of each factor; S2, establish the thin bottom water reservoir mechanism model and horizontal well model, set the horizontal well working system, and control the value of a single factor while keeping the other factors unchanged, to obtain the recoverable reserves under the influence of each factor; S3, based on the recoverable reserves under the influence of a single factor, select factors whose influence on the recoverable reserves reaches a set quantitative value, and establish a mathematical relationship between the recoverable reserves and each selected single factor; S4, based on the mathematical relationship between recoverable reserves and each selected single factor, a preset functional relationship is used to establish a mathematical relationship between recoverable reserves and the selected multiple factors; S5, inputting the numerical values of the selected multiple factors, and calculating the recoverable reserves based on the mathematical relationship between the recoverable reserves and the selected multiple factors.

2. The multi-parameter coupled method for predicting recoverable reserves of horizontal wells in thin-layer bottom water reservoirs according to claim 1, characterized in that: In S1, the multiple factors include: reservoir environment, structural factors, reservoir factors, fluid properties, reservoir parameters, well parameters, and production control factors.

3. The multi-parameter coupled method for predicting recoverable reserves of horizontal wells in thin-layer bottom water reservoirs according to claim 2, characterized in that: In said S2, it specifically includes: According to the characteristics of the thin bottom water reservoir under study, a reservoir model is established in the numerical simulation software, fluid parameters, reservoir initial conditions, relative permeability curves are set, a horizontal development well model is established, and the well working system is set; Control the value change of one factor and simulate the recoverable reserves of horizontal wells under different values of the factor while keeping other factors unchanged; and complete the same operation for each factor.

4. The multi-parameter coupled method for predicting recoverable reserves of horizontal wells in thin-layer bottom water reservoirs according to claim 3, characterized in that: The S3 includes: The factors that affect the reaching of the set quantitative value are determined based on the variation of recoverable reserves with each influencing factor. The power function is preferably used to express the mathematical relationship between recoverable reserves and each selected factor: N R =ax b If it is not suitable to be represented by a power function, a polynomial is used. The degree of the polynomial is generally not more than 3: N R =a1x k +a2x k-1 +……+a k x 1 +a k+1 Among them, N R is the recoverable reserves; a and b are unknown coefficients; x is the influencing factor; k is the degree of the polynomial.

5. The method for predicting recoverable reserves of horizontal wells in thin-layer bottom water reservoirs using multi-parameter coupling according to claim 4, characterized in that: In S4, the mathematical relationship between recoverable reserves and the selected multi-factor coupling is: Among them, x1~x m are factors that have a polynomial relationship with recoverable reserves; k1~k m is the degree of the polynomial; x m+1 ~x n are factors that have a power function relationship with recoverable reserves; a, b 1_1 ~b 1_k1 、b 2_1 ~b 2_k2 ,……,b m+1 ~b n is the undetermined coefficient.

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