Fractured sedimentary reservoir overpressure prediction method and device and computer equipment

Abstract

The invention relates to a fractured sedimentary reservoir overpressure prediction method and device and computer equipment. The method comprises the following steps: obtaining basic physical property parameters of a to-be-predicted sedimentary reservoir; calculating a rock matrix bulk modulus and a fluid bulk modulus; acquiring a crack angle average value and a preliminary crack aspect ratio of the crack; setting a random crack pore aspect ratio; obtaining the bulk modulus of the rock skeleton; calculating rock longitudinal wave velocity; when the ratio of the difference value of the longitudinal wave speed and the actual logging longitudinal wave speed to the actual longitudinal wave speed is smaller than a threshold value, the real skeleton bulk modulus of the rock is obtained; calculating to obtain a combination item; introducing a correction coefficient to obtain an improved sedimentary reservoir pore pressure prediction model based on a porous elastic mechanics theory, and obtaining a correction coefficient gamma; and predicting pore pressure of other typical wells in the same region. The method is a general method for predicting the overpressure of the sedimentary reservoir, which is really suitable for various rock types and takes the fracture anisotropy into consideration.

Description

Technical Field

[0001] The present invention relates to the field of geological exploration, and more specifically, to a method, device and computer equipment for predicting overpressure in fractured sedimentary reservoirs. Background Art

[0002] The accumulation and migration of oil and gas in many sedimentary basins are closely related to the formation pressure system. Abnormal overpressure may cause various engineering safety problems such as blowout, wellbore instability, wellbore erosion, and loss of drilling fluid circulation. At the same time, formation pore pressure, as the natural productivity, has an important impact on the development of conventional and unconventional oil and gas, and is also an important parameter for reservoir modeling, numerical simulation of oil and gas reservoirs, and prediction of sweet spots. The commonly used pore pressure prediction methods in the past include: the equivalent depth method using porosity and acoustic logging data; the Eaton formula method using acoustic and resistivity logging data; the Fillippone formula method using seismic interval velocity; the Eberhart-Phillips model and Bowers model by establishing empirical relationships between parameters such as acoustic velocity-porosity-shale content-Terzaghi effective stress, and some improved methods derived therefrom. The above methods are all for predicting formation pressure in clastic rock formations with specific overpressure causes. For heterogeneous fractured reservoirs such as tight carbonate rocks and tight sandstone formations with strong heterogeneity, it is difficult to find logging and seismic response parameters that reflect the change of Terzaghi effective stress. The prediction of pore pressure in sedimentary reservoirs with complex overpressure causes has become an unsolved problem and a frontier issue at home and abroad. The overpressure causes in most sedimentary reservoirs are often diverse, and there are often superpositions of multiple types of lithologies and overpressure causes. The previous overpressure prediction methods mainly target the same rock type. In addition, for fractured reservoirs, the distribution of pore space is often heterogeneous, and the problem of fracture anisotropy existing is not considered by the existing pore pressure prediction methods, which is an important factor affecting the accuracy of pore pressure prediction. Therefore, there is currently a lack of an overpressure prediction method for sedimentary reservoirs that can adapt to multiple rock types (clastic rocks, carbonates) and consider fracture anisotropy. Summary of the Invention

[0003] Aiming at the difficult problem of predicting pore pressure in current fractured sedimentary reservoirs (multiple rock types), the present invention proposes a method for predicting overpressure in fractured sedimentary reservoirs, which solves the pressure prediction of most fractured sedimentary reservoirs to a certain extent. This method is applicable to a wide range of formation types, and can accurately predict the pore pressure of fractured sedimentary reservoirs by obtaining the key parameters of fracture anisotropy, and has certain industrial application value.

[0004] To solve the above technical problems or achieve the above object, the present invention adopts the following specific technical solutions:

[0005] According to one aspect of the present invention, there is provided an overpressure prediction method for fractured sedimentary reservoirs, comprising the following steps:

[0006] 1) According to the comprehensive logging interpretation model of sedimentary reservoirs, using logging data to interpret the basic physical property parameters of the sedimentary reservoir to be predicted, and obtaining the basic physical property parameters of the sedimentary reservoir to be predicted;

[0007] 2) Based on the basic physical property parameters of the sedimentary reservoir to be predicted, using the Voigt-Reuss-Hill average modulus model to calculate the bulk modulus K of the rock matrix of the sedimentary reservoir to be predicted s , and using the Wood model or the Patchy model to calculate the bulk modulus K of the pore fluid of the sedimentary reservoir to be predicted f ;

[0008] 3) Based on the core observation statistics and the logging interpretation results of rock electrical imaging, obtaining the average fracture angle of the fractures and the initial fracture aspect ratio β0 of the fractures;

[0009] 4) Set a random fracture pore aspect ratio β, and set the initial value of the fracture pore aspect ratio β to be equal to the initial fracture aspect ratio β0;

[0010] 5) Add empty fracture pores with a pore aspect ratio of β based on the fracture Hudson equivalent medium theory to the rock matrix to obtain the bulk modulus K of the sedimentary reservoir rock skeleton d ;

[0011] 6) According to the bulk modulus K of the rock matrix s , the bulk modulus K of the pore fluid f , the bulk modulus K of the rock skeleton d and the basic physical property parameters, using the Gassmann equation to calculate the longitudinal wave velocity V of the sedimentary reservoir p-c ;

[0012] 7) Compare the calculated longitudinal wave velocity V of the sedimentary reservoir p-c with the actual logging longitudinal wave velocity V p-m , and when the absolute value of the difference between the two velocities and the ratio of the actual logging longitudinal wave velocity V p-m is less than the threshold, determine that the compliance standard is met and determine the fracture pore aspect ratio β and the bulk modulus K of the rock skeleton at this time d as the obtained target values, otherwise, repeat steps 4)-6) until the fracture pore aspect ratio β and the bulk modulus K of the rock skeleton of the sedimentary reservoir that meet the compliance standard are obtained d ;

[0013] 8) According to the basic physical property parameters, the bulk modulus K of the rock matrix s , the bulk modulus K of the pore fluid fand the obtained rock frame bulk modulus K that meets the compliance criteria d And based on the modification of the poroelastic mechanics theory of the pressure prediction model, calculate the composite elastic modulus combination term A representing the change in pore pressure magnitude;

[0014] 9) Obtain an improved pore pressure prediction model for sedimentary reservoirs based on poroelastic mechanics theory by introducing a correction coefficient γ, and correct the prediction result based on the measured pore pressure coefficient during drilling to obtain the correction coefficient γ;

[0015] 10) Use the correction coefficient γ and adopt the improved pore pressure prediction model for sedimentary reservoirs based on poroelastic mechanics theory to predict the pore pressure of other wells in the same area.

[0016] In an embodiment of the present invention, in step 1), the basic physical property parameters include the volume content V of each mineral composition of the sedimentary reservoir to be predicted i , the rock pore porosity Φ of the sedimentary reservoir to be predicted b , the rock fracture porosity Φ of the sedimentary reservoir to be predicted f and the volume percentage x of each component of the fluid mixture in the sedimentary reservoir to be predicted j .

[0017] In an embodiment of the present invention, in step 2), according to the volume content V of each mineral composition of the sedimentary reservoir to be predicted i , use the Voigt-Reuss-Hill average modulus model to calculate the rock matrix bulk modulus K of the sedimentary reservoir to be predicted s .

[0018] In an embodiment of the present invention, the calculation formula of K s is as follows:

[0019]

[0020] In the formula, M i is the elastic modulus of the i-th mineral.

[0021] In an embodiment of the present invention, in step 2), according to the volume percentage x of each component of the fluid mixture in the sedimentary reservoir to be predicted j , use the Wood model or the Patchy model to calculate the pore fluid bulk modulus K of the sedimentary reservoir to be predicted f .

[0022] In an embodiment of the present invention, the calculation formula of K f is as follows:

[0023]

[0024] In the formula, Ki is the bulk modulus of each mixed fluid component in the sedimentary reservoir to be predicted.

[0025] In one embodiment of the present invention, in step 4), 0.01 < β < 0.1.

[0026] In one embodiment of the present invention, in step 6), according to the bulk modulus K of the rock matrix s , the bulk modulus K of the pore fluid f , the bulk modulus K of the rock skeleton d and the rock fracture porosity Φ f , the longitudinal wave velocity V of the sedimentary reservoir is calculated using the Gassmann equation p-c .

[0027] In one embodiment of the present invention, in step 7), the threshold is 5%.

[0028] In one embodiment of the present invention, in step 8), according to the rock pore porosity Φ b , the rock fracture porosity Φ f , the bulk modulus K of the rock matrix s , the bulk modulus K of the pore fluid f and the obtained bulk modulus K of the rock skeleton that meets the compliance criteria d and based on the porous elastic mechanics theory correction of the pressure prediction model, the following formula for calculating the composite elastic modulus combination term A is obtained:

[0029]

[0030]

[0031] In the formula, Φ is the total rock porosity, Φ = Φ b + Φ f ; P p is the pore pressure; σ v is the overburden stress; σ T is the regional tectonic stress increment; k and z are empirical parameters of the linear relationship between the pore pressure and the composite elastic modulus combination term.

[0032] In one embodiment of the present invention, σ v is obtained by calculating the logging density, σ v = ρgh, where ρ is the logging density and h is the depth; σ T is obtained from the measured in-situ stress data in the area.

[0033] In one embodiment of the present invention, in step 9), the process of obtaining the correction coefficient γ includes the following steps:

[0034] 9.1) Based on the linear relationship between the pore pressure and the combined term of the complex elastic modulus in Equation (3-2), determine the maximum and minimum pore pressure conditions assumption, that is, satisfying:

[0035]

[0036] In the formula, P pmax and P pmin are the maximum pore pressure and the minimum pore pressure respectively; A max and A min are the maximum combined term of the complex elastic modulus and the minimum combined term of the complex elastic modulus respectively;

[0037] 9.2) Assume that the maximum pore pressure P pmax =σ v +σ T , the minimum pore pressure P pmin =P h , and transform Equation (4) into:

[0038]

[0039] And calculate the formation pore pressure coefficient P g through the following formula:

[0040]

[0041] In the formula, P h is the hydrostatic pressure and is obtained by calculating the formation depth;

[0042] 9.3) Introduce a correction coefficient γ to obtain an improved prediction model of the pore pressure coefficient of the sedimentary reservoir based on the poroelastic mechanics theory:

[0043]

[0044] 9.4) Obtain the measured pore pressure coefficient of the well drilling, the combined term A of the complex elastic modulus at the measured pressure position, and the maximum and minimum values A max and A min of all the data, and substitute them into Equation (7) to obtain the correction coefficient γ.

[0045] According to another aspect of the present invention, there is provided an overpressure prediction device for a fractured sedimentary reservoir, including:

[0046] A first module, which is configured to interpret the basic physical property parameters of the sedimentary reservoir to be predicted by using well logging data according to the comprehensive well logging interpretation model of the sedimentary reservoir, so as to obtain the basic physical property parameters of the sedimentary reservoir to be predicted;

[0047] The second module, which is configured to calculate the bulk modulus K of the rock matrix of the sedimentary reservoir to be predicted based on the basic physical properties of the sedimentary reservoir to be predicted, using the Voigt-Reuss-Hill average modulus model s , and calculate the bulk modulus K of the pore fluid of the sedimentary reservoir to be predicted using the Wood model or the Patchy model f ;

[0048] The third module, which is configured to obtain the average fracture angle of the fractures and the initial fracture aspect ratio β0 of the fractures based on the core observation statistics and the rock electrical imaging logging interpretation result data;

[0049] The fourth module, which is configured to set a random fracture pore aspect ratio β, set the initial value of the fracture pore aspect ratio β to be equal to the initial fracture aspect ratio β0, and add empty fracture pores with a pore aspect ratio of β based on the fracture Hudson equivalent medium theory to the rock matrix to obtain the bulk modulus K of the rock skeleton of the sedimentary reservoir d ;

[0050] The fifth module, which is configured to calculate the P-wave velocity V of the sedimentary reservoir using the Gassmann equation based on the bulk modulus K of the rock matrix s , the bulk modulus K of the pore fluid f , the bulk modulus K of the rock skeleton d and the basic physical properties, and compare the calculated P-wave velocity V of the sedimentary reservoir p-c with the actual logging P-wave velocity V p-c , and determine that the compliance standard is met and determine the fracture pore aspect ratio β and the bulk modulus K of the rock skeleton at this time when the ratio of the absolute value of the difference between the two velocities to the actual logging P-wave velocity V p-m is less than the threshold, otherwise, repeat the calculation until the fracture pore aspect ratio β and the bulk modulus K of the rock skeleton of the sedimentary reservoir that meet the compliance standard are obtained p-m ; d ; d ;

[0051] The sixth module, which is configured to calculate the combined composite elastic modulus term A representing the change in pore pressure magnitude based on the basic physical properties, the bulk modulus K of the rock matrix s , the bulk modulus K of the pore fluid f and the obtained bulk modulus K of the rock skeleton that meets the compliance standard d and based on the porous elastic mechanics theory correction of the pressure prediction model

[0052] The seventh module is configured to obtain an improved prediction model for pore pressure of sedimentary reservoirs based on poroelasticity theory by introducing a correction coefficient γ, and correct the prediction result based on the pore pressure coefficient measured in drilling to obtain the correction coefficient γ;

[0053] The eighth module is configured to use the correction coefficient γ and adopt the improved prediction model for pore pressure of sedimentary reservoirs based on poroelasticity theory to predict the pore pressure of other wells in the same area.

[0054] According to another aspect of the present invention, there is provided a computer device, including:

[0055] At least one processor; and

[0056] A memory that stores a computer program executable in the processor, and when the processor executes the computer program, it executes the overpressure prediction method for fractured sedimentary reservoirs as described above.

[0057] By adopting the above technical solutions, the present invention has the following advantages compared with the prior art:

[0058] The present invention proposes an overpressure prediction method for fractured sedimentary reservoirs, which is applicable to almost all sedimentary reservoirs and takes into account the influence of fracture anisotropy. It is a general method for overpressure prediction of sedimentary reservoirs that truly adapts to various rock types (clastic rocks, carbonate rocks) and considers fracture anisotropy. The present invention is expected to be widely applied in the field of pore pressure prediction of various fractured sedimentary reservoirs and has important industrial application value in oil and gas exploration and evaluation. BRIEF DESCRIPTION OF THE DRAWINGS

[0059] In order to more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the following will briefly introduce the drawings required for the description of the embodiments or the prior art. Obviously, the drawings in the following description are only some embodiments of the present invention. For those of ordinary skill in the art, other embodiments can be obtained based on these drawings without creative efforts.

[0060] Figure 1 Shows a flowchart of an overpressure prediction method for fractured sedimentary reservoirs provided by the present invention;

[0061] Figure 2 Shows the predicted pressure map of a fractured reservoir in a well in the Sichuan Basin in an embodiment of the present invention. DETAILED DESCRIPTION OF THE EMBODIMENTS

[0062] It should be understood that the embodiments of the present invention shown in the exemplary embodiments are merely illustrative. Although only a few embodiments of the present invention are described in detail, those skilled in the art can easily understand that various modifications are feasible without substantially departing from the teachings of the subject matter of the present invention. Accordingly, all such modifications should be included within the scope of the present invention. Without departing from the gist of the present invention, other substitutions, modifications, changes, and deletions can be made to the design, operating conditions, parameters, etc. of the following exemplary embodiments.

[0063] As Figure 1 shown, the present invention provides a method for predicting overpressure in fractured sedimentary reservoirs, including the following steps:

[0064] S101: According to the comprehensive logging interpretation model of sedimentary reservoirs, use logging data to interpret the basic physical property parameters of the sedimentary reservoir to be predicted, and obtain the basic physical property parameters of the sedimentary reservoir to be predicted;

[0065] S102: Based on the basic physical property parameters of the sedimentary reservoir to be predicted, use the Voigt-Reuss-Hill average modulus model to calculate the bulk modulus K of the rock matrix of the sedimentary reservoir to be predicted s , and use the Wood model or the Patchy model to calculate the bulk modulus K of the pore fluid of the sedimentary reservoir to be predicted f ;

[0066] S103: Based on the core observation statistics and the rock electrical imaging logging interpretation result data, obtain the average fracture angle of the fractures and the initial fracture aspect ratio β0 of the fractures;

[0067] S104: Set a random fracture pore aspect ratio β, and set the initial value of the fracture pore aspect ratio β to be equal to the initial fracture aspect ratio β0;

[0068] S105: Add empty fracture pores with a pore aspect ratio of β based on the fracture Hudson equivalent medium theory to the rock matrix to obtain the bulk modulus K of the rock skeleton of the sedimentary reservoir d ;

[0069] S106: According to the bulk modulus K of the rock matrix s , the bulk modulus K of the pore fluid f , the bulk modulus K of the rock skeleton d , and the basic physical property parameters, use the Gassmann equation to calculate the longitudinal wave velocity V of the sedimentary reservoir p-c ;

[0070] S107: Compare the calculated longitudinal wave velocity V of the sedimentary reservoir p-c with the actual logging longitudinal wave velocity V p-mCompare them, and when the ratio of the absolute value of the difference between the two speeds to the actual logging compressional wave velocity V p-m is less than the threshold, determine that the compliance standard is met and determine the fracture porosity aspect ratio β and the rock matrix bulk modulus K d at this time as the obtained target values. Otherwise, repeat steps S104 - S106 until the fracture porosity aspect ratio β and the rock matrix bulk modulus K d of the sedimentary reservoir that meet the compliance standard are obtained;

[0071] S108: According to the basic physical property parameters, the rock matrix bulk modulus K s , the pore fluid bulk modulus K f and the obtained rock matrix bulk modulus K d that meet the compliance standard, and based on the modification of the poroelastic mechanics theory of the pressure prediction model, calculate the combined composite elastic modulus term A representing the change in pore pressure magnitude;

[0072] S109: Obtain an improved sedimentary reservoir pore pressure prediction model based on the poroelastic mechanics theory by introducing a correction coefficient γ, and correct the prediction result based on the measured pore pressure coefficient during drilling to obtain the correction coefficient γ;

[0073] S110: Use the correction coefficient γ and adopt the improved sedimentary reservoir pore pressure prediction model based on the poroelastic mechanics theory to predict the pore pressure of other wells in the same area.

[0074] The present invention proposes a method for predicting overpressure in fractured sedimentary reservoirs, which is applicable to almost all sedimentary reservoirs and takes into account the influence of fracture anisotropy. It is a general method for predicting overpressure in sedimentary reservoirs that truly adapts to various rock types (clastic rocks, carbonate rocks) and considers fracture anisotropy.

[0075] In the above method, in step S101, the basic physical property parameters include the volume content V i of each mineral composition of the sedimentary reservoir to be predicted, the rock pore porosity Φ b of the sedimentary reservoir to be predicted, the fracture porosity Φ f of the sedimentary reservoir to be predicted, and the volume percentages x j of each component of the fluid mixture in the sedimentary reservoir to be predicted.

[0076] In the above method, in step S102, according to the volume content V i of each mineral composition of the sedimentary reservoir to be predicted, use the Voigt - Reuss - Hill average modulus model to calculate the rock matrix bulk modulus K s of the sedimentary reservoir to be predicted.

[0077] In the above method, K sThe calculation formula is as follows:

[0078]

[0079] Wherein, M i is the elastic modulus of the i-th mineral.

[0080] In the above method, in step S102, according to the volume percentage x j of each component of the fluid mixture in the sedimentary reservoir to be predicted, the pore fluid bulk modulus K f of the sedimentary reservoir to be predicted is calculated by using the Wood model or the Patchy model.

[0081] In the above method, the calculation formula of K f is as follows:

[0082]

[0083] Wherein, K i is the bulk modulus of each mixed fluid component in the sedimentary reservoir to be predicted.

[0084] In the above method, in step S104, 0.01 < β < 0.1.

[0085] In the above method, in step S106, according to the rock matrix bulk modulus K s , the pore fluid bulk modulus K f , the rock frame bulk modulus K d and the rock fracture porosity Φ f , the longitudinal wave velocity V p-c of the sedimentary reservoir is calculated by using the Gassmann equation.

[0086] In the above method, in step S107, the threshold is 5%.

[0087] In the above method, in step S108, according to the rock pore porosity Φ b , the rock fracture porosity Φ f , the rock matrix bulk modulus K s , the pore fluid bulk modulus K f and the obtained rock frame bulk modulus K d meeting the compliance standard conditions, and based on the modification of the poroelastic mechanics theory of the pressure prediction model, the following formula for calculating the composite elastic modulus combination term A is obtained:

[0088]

[0089]

[0090] Wherein, Φ is the total rock porosity, Φ = Φb +Φ f ; P p is the pore pressure; σ v is the overburden stress; σ T is the regional tectonic stress increment; k and z are empirical parameters of the linear relationship between the pore pressure and the combined term of the composite elastic modulus.

[0091] In the above method, σ v is obtained by calculating the logging density, and σ v =ρgh, where ρ is the logging density and h is the depth; σ T is obtained from the measured in-situ stress data of the area.

[0092] In the above method, in step S109, the process of obtaining the correction coefficient γ includes the following steps:

[0093] (1) Based on the linear relationship between the pore pressure and the combined term of the composite elastic modulus in formula (3-2), determine the maximum and minimum pore pressure condition assumptions, that is, satisfy:

[0094]

[0095] where P pmax and P pmin are the maximum pore pressure and the minimum pore pressure respectively; A max and A min are the maximum combined term of the composite elastic modulus and the minimum combined term of the composite elastic modulus respectively;

[0096] (2) Assume that the maximum pore pressure P pmax =σ v +σ T , the minimum pore pressure P pmin =P h , and transform formula (4) into:

[0097]

[0098] and calculate the formation pore pressure coefficient P g through the following formula:

[0099]

[0100] where P h is the hydrostatic pressure and is obtained by calculating the formation depth;

[0101] (3) Introduce the correction coefficient γ to obtain an improved prediction model of the pore pressure coefficient of sedimentary reservoirs based on the poroelastic mechanics theory:

[0102]

[0103] (4) Obtain the measured pore pressure coefficient of the well drilling, the combined elastic modulus term A at the measured pressure position, and the maximum and minimum values A of all the data max and A min , and substitute them into formula (7) to obtain the correction coefficient γ.

[0104] In addition, the present invention also provides an overpressure prediction device for fractured sedimentary reservoirs, including:

[0105] A first module configured to interpret the basic physical property parameters of the sedimentary reservoir to be predicted by using well logging data according to the integrated well logging interpretation model of the sedimentary reservoir, so as to obtain the basic physical property parameters of the sedimentary reservoir to be predicted;

[0106] A second module configured to calculate the bulk modulus K of the rock matrix of the sedimentary reservoir to be predicted by using the Voigt-Reuss-Hill average modulus model based on the basic physical property parameters of the sedimentary reservoir to be predicted s , and calculate the bulk modulus K of the pore fluid of the sedimentary reservoir to be predicted by using the Wood model or the Patchy model f ;

[0107] A third module configured to obtain the average fracture angle of the fractures and the initial fracture aspect ratio β0 of the fractures based on the core observation statistics and the interpretation result data of the rock electrical imaging logging;

[0108] A fourth module configured to set a random fracture pore aspect ratio β, set the initial value of the fracture pore aspect ratio β to be equal to the initial fracture aspect ratio β0, and add the empty fracture pores with the pore aspect ratio β based on the fracture Hudson equivalent medium theory to the rock matrix to obtain the bulk modulus K of the sedimentary reservoir rock skeleton d ;

[0109] A fifth module configured to calculate the longitudinal wave velocity V of the sedimentary reservoir according to the bulk modulus K of the rock matrix s , the bulk modulus K of the pore fluid f , the bulk modulus K of the sedimentary reservoir rock skeleton d and the basic physical property parameters by using the Gassmann equation p-c , and compare the calculated longitudinal wave velocity V of the sedimentary reservoir p-c with the actual longitudinal wave velocity V of the well logging p-m , and determine that the compliance standard is met and determine the fracture pore aspect ratio β and the bulk modulus K of the sedimentary reservoir rock skeleton at this time when the ratio of the absolute value of the difference between the two velocities to the actual longitudinal wave velocity V of the well logging p-m is less than the threshold value dThe obtained target value; otherwise, repeat the calculation until the aspect ratio β of the fracture pores in the sedimentary reservoir and the bulk modulus K of the rock skeleton that meet the compliance conditions are obtained d ;

[0110] The sixth module, which is configured to calculate the combined term A of the composite elastic modulus representing the change in pore pressure magnitude based on the basic physical properties parameters, the bulk modulus K of the rock matrix s , the bulk modulus K of the pore fluid f and the obtained bulk modulus K of the rock skeleton that meets the compliance conditions, and based on the porous elastic mechanics theory correction of the pressure prediction model d ;

[0111] The seventh module, which is configured to obtain an improved pore pressure prediction model for sedimentary reservoirs based on porous elastic mechanics theory by introducing a correction coefficient γ, and correct the prediction result based on the measured pore pressure coefficient during drilling to obtain the correction coefficient γ

[0112] The eighth module, which is configured to use the correction coefficient γ to predict the pore pressure of other wells in the same area by using the improved pore pressure prediction model for sedimentary reservoirs based on porous elastic mechanics theory

[0113] In addition, the present invention also provides a computer device, including:

[0114] At least one processor; and

[0115] A memory that stores a computer program that can run in the processor, and when the processor executes the computer program, it executes the overpressure prediction method for fractured sedimentary reservoirs as described above

[0116] The above technical solutions of the present invention will be described in detail below through specific embodiments

[0117] In an embodiment of the present invention, an overpressure prediction method for fractured sedimentary reservoirs, the specific steps are as follows:

[0118] (1) According to the comprehensive logging interpretation model of the sedimentary reservoir, use logging data to interpret the basic physical properties parameters of the sedimentary reservoir to be predicted, and obtain the basic physical properties parameters of the sedimentary reservoir to be predicted, where the basic physical properties parameters include the volume content V of each mineral composition of the sedimentary reservoir to be predicted i , the rock pore porosity Φ of the sedimentary reservoir to be predicted b , the rock fracture porosity Φ of the sedimentary reservoir to be predicted f and the volume percentage x of each component of the fluid mixture in the sedimentary reservoir to be predicted j .

[0119] (2) According to the volume content V of each mineral composition of the sedimentary reservoir to be predicted i, the Voigt-Reuss-Hill average modulus model is adopted to calculate the rock matrix bulk modulus \(K\) of the sedimentary reservoir to be predicted. s , \(K\) s is calculated according to the following formula:

[0120]

[0121] According to the volume percentages \(x\) of the components of the fluid mixture in the sedimentary reservoir to be predicted j , the Wood model or the Patchy model is used to calculate the pore fluid bulk modulus \(K\) of the sedimentary reservoir to be predicted. f , \(K\) f is calculated according to the following formula:

[0122]

[0123] In the formula, \(K\) i is the bulk modulus of each mixed fluid component in the sedimentary reservoir to be predicted, which is a prior value.

[0124] (3) Based on the core observation statistics and the data of the rock electrical imaging logging interpretation results, obtain the average fracture angle of the fractures and the initial fracture aspect ratio \(\beta_0\) of the fractures.

[0125] (4) Set a random fracture pore aspect ratio \(\beta\), with the initial \(\beta=\beta_0\), and \(0.01 < \beta < 0.1\).

[0126] (5) Add the empty fracture pores with a pore aspect ratio of \(\beta\) (initial \(\beta=\beta_0\)) based on the fracture Hudson equivalent medium theory to the rock matrix to obtain the bulk modulus \(K\) of the sedimentary reservoir rock skeleton. d . (For the specific method, see the literature: Dvorkin J., Nur A. Dynamic poroelasticity: A unified model with the squirt and the Biot mechanisms [J]. Geophysics, 1993, 58(4): 524 - 533. and Mavko G., Mukerji T., Dvorkin J. The rock physics handbook: tools for seismic analysis of porous media [M]. New York: Cambridge University Press, 2009.)

[0127] (6) According to the rock matrix bulk modulus \(K\) s , the pore fluid bulk modulus \(K\) f , and the bulk modulus \(K\) of the rock skeleton dand the porosity Φ of rock fractures f , the P-wave velocity V of sedimentary reservoirs is calculated using the Gassmann equation p-c . (For the specific method, see the literature: De-hua Han, Michael L. Batzle; Gassmann's equation and fluid-saturation effects on seismic velocities[J]. Geophysics, 2004; 69(2): 398-405.)

[0128] (7) Compare the calculated P-wave velocity V of sedimentary reservoirs p-c with the actual well-logging P-wave velocity V p-m , and determine that the compliance standard is met when the absolute value of the difference between the two velocities and the ratio of the actual well-logging P-wave velocity V p-m is less than 5%, and determine the aspect ratio β of fracture porosity and the bulk modulus K of the rock skeleton d at this time as the target values obtained. Otherwise, repeat steps (4)-(6) until the aspect ratio β of fracture porosity and the bulk modulus K of the rock skeleton that meet the compliance standard are obtained d .

[0129] (8) According to the porosity Φ of rock pores b , the porosity Φ of rock fractures f , the bulk modulus K of the rock matrix s , the bulk modulus K of pore fluid f and the obtained bulk modulus K of the rock skeleton that meets the compliance standard d and based on the modified poroelastic mechanics theory of the pressure prediction model, calculate the combined term A of the composite elastic modulus representing the change in pore pressure magnitude. The formula is:

[0130]

[0131]

[0132] where Φ is the total porosity of the rock, Φ = Φ b +Φ f ; P p is the pore pressure; σ v is the overburden stress (which can be obtained by calculating the well-logging density, σ v =ρgh, ρ is the well-logging density, h is the depth); σ T is the regional tectonic stress increment (which can be obtained from the measured in-situ stress data in the area and is a prior value); k and z are the empirical parameters of the linear relationship between pore pressure and the combined term of composite elastic modulus (not required to be obtained).

[0133] (9) An improved pore pressure prediction model of sedimentary reservoirs based on the poroelasticity theory is obtained through the proposed correction method, and a new correction coefficient γ is obtained by correcting the prediction results based on the measured pore pressure of one well.

[0134] Since the above various rock elastic parameters are estimated by the rock physics model and their accurate values cannot be obtained, it is necessary to correct the model with actual data in order to accurately predict the pore pressure of sedimentary reservoirs that can reflect the changes in the vertical and horizontal planes. The process of obtaining the model correction coefficient γ is as follows:

[0135] (9.1) Since the combination term of pore pressure and composite elastic modulus in formula (3-1) is a linear relationship, it must conform to the maximum and minimum pore pressure condition assumptions, that is:

[0136]

[0137] In the formula, P pmax and P pmin are the maximum pore pressure and the minimum pore pressure respectively; A max and A min are the maximum composite elastic modulus combination term and the minimum composite elastic modulus combination term respectively;

[0138] (9.2) If it is assumed that the maximum pore pressure P pmax =σ v +σ T , the minimum pore pressure P pmin =P h (P h is the hydrostatic pressure and can be calculated from the formation depth), then formula (4) is transformed into:

[0139]

[0140] The calculation formula of the formation pore pressure coefficient P g :

[0141]

[0142] (9.3) Since the maximum value of the pore pressure cannot reach σ v +σ T , an improved pore pressure coefficient prediction model of sedimentary reservoirs based on the poroelasticity theory is obtained by introducing the correction coefficient γ:

[0143]

[0144] (9.4) According to the measured pore pressure coefficient value of the typical well, σ v is the overburden stress, σ Tis the regional tectonic stress increment; the combined item A of the composite elastic modulus at the measured pressure position n , as well as the maximum and minimum values of all data A max and A min , substitute them into formula (7) to obtain the correction coefficient γ.

[0145] (10) Using the correction coefficient γ, adopt an improved pore pressure prediction model for sedimentary reservoirs based on poroelastic mechanics theory to predict the pore pressure of other typical wells in the same area.

[0146] In the application research of the embodiment of the present invention, a typical well in a fractured reservoir in the Sichuan Basin of China is selected. Using the method of the above embodiment of the present invention, as Figure 2 shown, the calculated pore pressure coefficient (pore pressure coefficient = pore pressure / hydrostatic pressure, Figure 2 the curve line in) is highly consistent with the measured pore pressure coefficient value (measured pore pressure coefficient = measured pore pressure / hydrostatic pressure, Figure 2 the triangular data points in), and the curve trend is basically the same as that of the pressure coefficient converted from mud density ( Figure 2 the dotted line in). Therefore, this method can accurately calculate the pore pressure value of fractured sedimentary reservoirs, has stronger applicability and practicability than previous methods, and has certain industrial application value.

[0147] The above are only the preferred embodiments of the present invention and are not used to limit the scope of implementation of the present invention; if the present invention is modified or equivalently replaced without departing from the spirit and scope of the present invention, it should be covered by the protection scope of the claims of the present invention.

Claims

1. A method for predicting overpressure in fractured sedimentary reservoirs, characterized in that, It includes the following steps: 1) According to the comprehensive logging interpretation model of sedimentary reservoirs, use logging data to interpret the basic physical property parameters of the sedimentary reservoir to be predicted, and obtain the basic physical property parameters of the sedimentary reservoir to be predicted; 2) Based on the basic physical property parameters of the sedimentary reservoir to be predicted, the Voigt-Reuss-Hill average modulus model is used to calculate the bulk modulus K of the rock matrix of the sedimentary reservoir to be predicted s , and the Wood model or the Patchy model is used to calculate the bulk modulus K of the pore fluid of the sedimentary reservoir to be predicted f ; 3) Based on the core observation statistics and the interpretation result data of the rock electrical imaging logging, obtain the average fracture angle of the fractures and the preliminary fracture aspect ratio β0 of the fractures; 4) Set a random fracture pore aspect ratio β, and set the initial value of the fracture pore aspect ratio β to be equal to the preliminary fracture aspect ratio β0; 5) Add empty fractured pores with an aspect ratio of β based on the Hudson equivalent medium theory of fractures to the rock matrix to obtain the bulk modulus K of the sedimentary reservoir rock skeleton d ; 6) According to the bulk modulus K of the rock matrix s , the bulk modulus K of the pore fluid f , the bulk modulus K of the rock skeleton d and the basic physical property parameters, the P-wave velocity V of the sedimentary reservoir is calculated by using the Gassmann equation p-c ; 7) Compare the calculated longitudinal wave velocity V of the sedimentary reservoir p-c with the actual longitudinal wave velocity V measured by logging p-m and, when the ratio of the absolute value of the difference between the two velocities to the actual longitudinal wave velocity V measured by logging p-m is less than the threshold, determine that the compliance criteria are met and determine the fracture porosity aspect ratio β and the rock frame bulk modulus K at this time d as the target values obtained. Otherwise, repeat steps 4)-6) until the fracture porosity aspect ratio β and the rock frame bulk modulus K of the sedimentary reservoir that meet the compliance criteria are obtained d ; 8) According to the basic physical properties parameters, the bulk modulus of the rock matrix K s , the bulk modulus of the pore fluid K f and the bulk modulus of the rock skeleton K d that meet the compliance criteria, and based on the modification of the poroelastic mechanics theory of the pressure prediction model, the combined composite elastic modulus term A representing the change in the magnitude of the pore pressure is calculated; 9) Obtain an improved sedimentary reservoir pore pressure prediction model based on the poroelastic mechanics theory by introducing a correction coefficient γ, and correct the prediction result based on the measured pore pressure coefficient of the drilling to obtain the correction coefficient γ; 10) Use the correction coefficient γ and adopt the improved sedimentary reservoir pore pressure prediction model based on the poroelastic mechanics theory to predict the pore pressure of other drillings in the same area.

2. The overpressure prediction method for fractured sedimentary reservoirs according to claim 1, wherein In step 1), the basic physical property parameters include the volume content V of each mineral composition of the sedimentary reservoir to be predicted i , the rock pore porosity Φ of the sedimentary reservoir to be predicted b , the rock fracture porosity Φ of the sedimentary reservoir to be predicted f and the volume percentage x of each component of the fluid mixture in the sedimentary reservoir to be predicted j .

3. The overpressure prediction method for fractured sedimentary reservoirs according to claim 2, characterized in that, In step 2), according to the volume content V of each mineral component of the sedimentary reservoir to be predicted i , the Voigt-Reuss-Hill average modulus model is used to calculate the bulk modulus K of the rock matrix of the sedimentary reservoir to be predicted s .

4. The overpressure prediction method for fractured sedimentary reservoirs according to claim 3, wherein K s The calculation formula is as follows: where M i is the elastic modulus of the i-th mineral.

5. The overpressure prediction method for fractured sedimentary reservoirs according to claim 2, characterized in that In step 2), according to the volume percentage x of each component of the fluid mixture in the sedimentary reservoir to be predicted j , the pore fluid bulk modulus K of the sedimentary reservoir to be predicted is calculated using the Wood model or the Patchy model f .

6. The overpressure prediction method for fractured sedimentary reservoirs according to claim 5, characterized in that, K f The calculation formula is as follows: Where K j is the bulk modulus of each mixed fluid component in the sedimentary reservoir to be predicted.

7. The overpressure prediction method for fractured sedimentary reservoirs according to claim 1, wherein In step 4), 0.01 < β < 0.

1.

8. The overpressure prediction method for fractured sedimentary reservoirs according to claim 2, wherein In step 6), according to the rock matrix bulk modulus K s , the pore fluid bulk modulus K f , the rock skeleton bulk modulus K d , and the rock fracture porosity Φ f , the longitudinal wave velocity V p-c of the sedimentary reservoir is calculated using the Gassmann equation.

9. The overpressure prediction method for fractured sedimentary reservoirs according to claim 1, wherein In step 7), the threshold value is 5%.

10. The overpressure prediction method for fractured sedimentary reservoirs according to claim 2, characterized in that In step 8), according to the rock pore porosity Φ b , the rock fracture porosity Φ f , the rock matrix bulk modulus K s , the pore fluid bulk modulus K f and the obtained rock skeleton bulk modulus K d that meets the compliance criteria, and based on the porous elastic mechanics theory correction of the pressure prediction model, the following formula for calculating the composite elastic modulus combination term A is obtained: where Φ is the total porosity of the rock, Φ = Φ b + Φ f ; P p is the pore pressure; σ v is the overburden stress; σ T is the regional tectonic stress increment; k and z are empirical parameters of the linear relationship between the pore pressure and the combined elastic modulus term.

11. The overpressure prediction method for fractured sedimentary reservoirs according to claim 10, characterized in that, σ v Obtained by calculating well logging density, σ v = ρgh, where ρ is the well logging density and h is the depth; σ T Obtained from the measured in-situ stress data of the area.

12. The overpressure prediction method for fractured sedimentary reservoirs according to claim 11, wherein In step 9), the process of obtaining the correction coefficient γ includes the following steps: 9.1) Based on the linear relationship between the pore pressure and the combined term of the complex elastic modulus in formula (3-2), determine the maximum and minimum pore pressure condition assumptions, that is, satisfy: where P pmax and P pmin are the maximum pore pressure and the minimum pore pressure respectively; A max and A min are the maximum combined composite elastic modulus term and the minimum combined composite elastic modulus term respectively; 9.2) Assume the maximum pore pressure P pmax = σ v+ σ T , and the minimum pore pressure P pmin = P h . Then transform Equation (4) into: And calculate the formation pore pressure coefficient P through the following formula g :[[]]END]] where P h is the hydrostatic pressure and is obtained by calculating the formation depth; 9.3) Introduce the correction coefficient γ to obtain an improved sedimentary reservoir pore pressure coefficient prediction model based on the poroelastic mechanics theory: 9.4) Obtain the measured pore pressure coefficient during drilling, the combined elastic modulus term A at the measured pressure position, and the maximum and minimum values A of all the data max and A min , and substitute them into Equation (7) to obtain the correction coefficient γ.

13. An overpressure prediction device for fractured sedimentary reservoirs, characterized in that, It includes: The first module, which is configured to interpret the basic physical property parameters of the sedimentary reservoir to be predicted according to the comprehensive logging interpretation model of the sedimentary reservoir, and use logging data to obtain the basic physical property parameters of the sedimentary reservoir to be predicted; The second module, configured to calculate the bulk modulus K of the rock matrix of the sedimentary reservoir to be predicted based on the basic physical property parameters of the sedimentary reservoir to be predicted, using the Voigt-Reuss-Hill average modulus model s , and calculate the bulk modulus K of the pore fluid of the sedimentary reservoir to be predicted using the Wood model or the Patchy model f ; The third module, which is configured to obtain the average fracture angle of the fractures and the preliminary fracture aspect ratio β0 of the fractures based on the core observation statistics and the interpretation result data of the rock electrical imaging logging; The fourth module is configured to set a random crack porosity aspect ratio β, set the initial value of the crack porosity aspect ratio β to be equal to the preliminary crack aspect ratio β0, and add empty crack pores with a porosity aspect ratio of β based on the crack Hudson equivalent medium theory to the rock matrix to obtain the bulk modulus K of the sedimentary reservoir rock skeleton d ; The fifth module, where the fifth module is configured to calculate the P-wave velocity V of the sedimentary reservoir using the Gassmann equation based on the bulk modulus K of the rock matrix s , the bulk modulus K of the pore fluid f , the bulk modulus K of the rock skeleton d and the basic physical property parameters p-c , and compare the calculated P-wave velocity V of the sedimentary reservoir p-c with the actual P-wave velocity V measured by logging p-m . When the ratio of the absolute value of the difference between the two velocities to the actual P-wave velocity V measured by logging p-m is less than the threshold, it is determined that the compliance standard is met, and the fracture porosity aspect ratio β and the bulk modulus K of the rock skeleton at this time d are determined as the target values. Otherwise, the calculation is repeated until the fracture porosity aspect ratio β and the bulk modulus K of the rock skeleton of the sedimentary reservoir that meet the compliance standard are obtained d ; The sixth module, which is configured to calculate, based on basic physical property parameters, the bulk modulus K s of the rock matrix, the bulk modulus K f of the pore fluid, and the obtained bulk modulus K d of the rock skeleton that meets the compliance criteria, and based on the porous elastic mechanics theory correction of the pressure prediction model, calculate the combined composite elastic modulus term A representing the change in pore pressure magnitude; The seventh module, which is configured to obtain an improved sedimentary reservoir pore pressure prediction model based on the poroelastic mechanics theory by introducing a correction coefficient γ, and correct the prediction result based on the measured pore pressure coefficient of the drilling to obtain the correction coefficient γ; The eighth module, which is configured to use the correction coefficient γ and adopt the improved sedimentary reservoir pore pressure prediction model based on the poroelastic mechanics theory to predict the pore pressure of other drillings in the same area.

14. A computer device, characterized in that, It includes: At least one processor; And A memory, the memory stores a computer program that can run in the processor, and when the processor executes the computer program, it executes the overpressure prediction method for fractured sedimentary reservoirs described in any one of claims 1-12.

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