Non-vertical well section shale formation pore pressure prediction method, system, device and medium

Abstract

The application discloses a non-vertical well section shale formation pore pressure prediction method, system, device and medium, relates to the prediction of shale formation pore pressure, and aims to solve the problem that there is great difficulty in predicting the non-vertical well formation pore pressure by using acoustic logging data in the prior art. The non-vertical well section predicted acoustic interval transit time under the logging condition of the non-vertical well section is predicted, the predicted acoustic interval transit time is compared with the logging data, the anisotropic stiffness coefficient of the non-vertical well section is selectively output according to the comparison result, the verticalized acoustic interval transit time of the non-vertical well section is calculated based on the anisotropic stiffness coefficient of the non-vertical well section, and the vertical in-situ stress calculated by using the density logging data, so that the non-vertical well section shale formation pore pressure can be effectively predicted. The scheme effectively solves the problem that the acoustic interval transit time of the non-vertical well section cannot be directly used for formation pore pressure prediction, and the prediction accuracy of the shale formation pore pressure is relatively high.

Description

TECHNICAL FIELD

[0001] The present application belongs to the field of unconventional oil and gas development, and relates to the prediction of shale formation pore pressure, in particular to the prediction of shale formation pore pressure in non-vertical well sections. BACKGROUND

[0002] Formation pore pressure refers to the pressure possessed by fluid in formation pores or fractures, and it is the basis for reasonably determining casing programs and the key to reasonably selecting mud density and realizing safe and efficient drilling. Meanwhile, formation pore pressure is one of the main controlling factors of oil and gas accumulation and distribution, and is the basis for the study of oil and gas accumulation fluid dynamics.

[0003] The existing formation pore pressure logging prediction methods can be divided into three categories: formation pore pressure prediction methods based on the undercompaction theory, represented by the equivalent depth method and Eaton method; formation pore pressure prediction methods based on the effective stress theory, represented by the Bowers method; and empirical relationship methods constructed by using acoustic logging data, density logging data, etc. Among them, the method of predicting formation pore pressure by using logging data is widely used due to its low cost, good continuity and high precision, and is mostly used in straight wellbore trajectory formations.

[0004] There is very little research on the prediction of formation pore pressure in the current non-vertical well section, which is due to the great difference in rock properties between straight well section and non-vertical well section. Shale shows strong transverse isotropic characteristics due to the presence of clay, kerogen and other minerals in shale and the development of horizontal fractures in shale formations. Due to the strong anisotropy of shale, there is a great difference in rock properties parallel to the bedding plane and perpendicular to the bedding plane, which leads to a large difference in acoustic wave velocity between the non-vertical well section and the straight well section. In transversely isotropic shale formations, the acoustic travel time will change with the change of propagation direction. In non-vertical wellbore trajectory formations, due to the angle between the wellbore trajectory direction and the normal of the shale formation bedding plane, the compressional and shear wave travel times are very different from those of the straight wellbore trajectory in the same formation, which makes it difficult to predict the formation pore pressure in the non-vertical well section. Based on this, the current formation pore pressure prediction methods rarely consider the change of acoustic wave velocity caused by the anisotropy of the formation, and accurate determination of the acoustic wave velocity perpendicular to the formation is crucial regardless of which type of formation pore pressure prediction method is used.

[0005] To accurately determine the acoustic wave velocity of the non-vertical well section formation, current researches are made on the acoustic wave of the non-vertical well section formation in the aspect of acoustic wave inversion to the corresponding straight well. For example, Donald et al. combine the seismic wave velocity and the core database prior elastic anisotropy relationship to solve the inverted acoustic travel time. Ferla et al. establish the relationship between the shale physical parameters and the Thomsen anisotropy coefficient based on the Bayesian theory, and then use the relationship between the Thomsen anisotropy coefficient and the vertical propagation acoustic wave velocity and the acoustic wave velocity under the corresponding inclined well condition to invert the inverted acoustic wave velocity. Hornby et al. combine the acoustic travel time of the inclined well and the adjacent straight well to obtain five independent elastic stiffness coefficients, and then use the relationship between the Thomsen coefficient and the wave velocity under the inclined well and the corresponding straight well condition to correct the acoustic travel time under the inclined well condition to the straight well condition.

[0006] Although the above-mentioned research methods use different methods to invert the acoustic travel time of the non-vertical well section formation, these methods have the shortcomings of poor seismic wave velocity accuracy, difficult acquisition of prior information of the core database, and Thomsen coefficient only applicable to weak anisotropic shale formation.

[0007] Therefore, it is urgent to establish a prediction method for the pore pressure of the shale non-vertical well section formation with strong anisotropy characteristics, which will help to improve the prediction accuracy of the pore pressure of the shale formation and provide basic data and guidance for the subsequent stress prediction, mud density window determination and wellbore stability analysis. SUMMARY

[0008] To solve the problem in the prior art that the acoustic travel time along the non-vertical well trajectory and the acoustic travel time along the straight well trajectory have large differences due to the strong anisotropy of the shale, and thus it is difficult to predict the pore pressure of the non-vertical well formation by using acoustic logging data, a shale non-vertical well section pore pressure prediction method is provided.

[0009] To solve the above technical problems, the technical scheme adopted by the present application is as follows:

[0010] A shale non-vertical well section pore pressure prediction method, comprising the following steps:

[0011] Step 1: acquiring logging data;

[0012] Step 2: constructing a transversely isotropic shale rock physics model;

[0013] Step 3: inputting the non-vertical well section shale physical parameters in the logging data obtained in step 1 into the transversely isotropic shale rock physics model to calculate the anisotropic stiffness coefficient of the non-vertical well section;

[0014] Step four, predicting the non-vertical well section predicted acoustic interval transit time in the non-vertical well section logging condition by using the non-vertical well section anisotropic stiffness coefficient obtained in step three; if the difference between the predicted non-vertical well section predicted acoustic interval transit time and the non-vertical well section acoustic interval transit time in the logging data is less than a preset threshold, outputting the non-vertical well section anisotropic stiffness coefficient, and entering step five; if the difference between the predicted non-vertical well section predicted acoustic interval transit time and the non-vertical well section acoustic interval transit time in the logging data is greater than the preset threshold, returning to step two to reconstruct the transversely isotropic shale rock physical model;

[0015] Step five, calculating the non-vertical well section acoustic interval transit time after verticalization of the non-vertical well section formation by using the non-vertical well section anisotropic stiffness coefficient output in step four;

[0016] Step six, predicting the non-vertical well section shale formation pore pressure based on the non-vertical well section acoustic interval transit time obtained in step five and the vertical ground stress calculated by using the density logging data.

[0017] As preferred, the non-vertical well section shale physical parameters include mineral components and content of each component, formation fluid components and content of each component, formation porosity, and fluid saturation.

[0018] As preferred, the transversely isotropic shale rock physical model in step two includes:

[0019] A Hashin-Shtrikman limit module, configured to calculate the upper limit value and the lower limit value of the bulk modulus and the shear modulus of the brittle mineral mixture by using the Hashin-Shtrikman limit according to the non-vertical well section shale physical parameters in the logging data obtained in step one, and taking the average value of the upper limit value and the lower limit value as the bulk modulus and the shear modulus of the brittle mineral mixture;

[0020] A dry brittle rock physical model, configured to add inorganic pores to the brittle mineral mixture to obtain a brittle mineral equivalent mixture by using the isotropic SCA model and the isotropic DEM model, and establish a rock physical model of the dry brittle rock; taking the bulk modulus and the shear modulus output by the HS limit module as the input of the dry brittle rock physical model;

[0021] An anisotropic SCA module, configured to simulate the equivalent elastic properties of clay-dry kerogen by using the anisotropic SCA model, and calculate the corresponding equivalent elastic stiffness matrix;

[0022] A dry clay-dry kerogen mixture physical module, configured to add inorganic pores to the clay-dry kerogen mixture to establish a rock physical model of the dry clay-dry kerogen mixture by using the anisotropic DEM model; taking the equivalent elastic stiffness matrix output by the anisotropic SCA module as the input of the dry clay-dry kerogen mixture physical module;

[0023] The dry shale rock physics module is configured to mix the dry clay-dry kerogen mixture and the dry brittle rock by using the Backus averaging theory to establish a dry shale rock physics model; the outputs of the dry brittle rock physics model and the dry clay-dry kerogen mixture physics module are both taken as the inputs of the dry shale rock physics module, and the elastic tensor of the dry shale is outputted;

[0024] The saturated fluid transversely isotropic shale rock physics model is configured to calculate the bulk modulus of the gas-water mixture in the pore according to the gas saturation and the water saturation by using the Wood formula, and convert the bulk modulus into the stiffness tensor; the Brown-Korringa model is used to add the mixed fluid to the dry shale to obtain the saturated fluid shale, and the saturated fluid transversely isotropic shale rock physics model is established; the elastic tensor of the dry shale outputted by the dry shale rock physics module is taken as the input of the saturated fluid transversely isotropic shale rock physics model, and the anisotropic stiffness coefficient of the non-vertical well section is outputted by the saturated fluid transversely isotropic shale rock physics model.

[0025] Preferably, when the Hashin-Shtrikman limit is used to calculate the upper limit and the lower limit of the bulk modulus and the shear modulus of the brittle mineral mixture, the calculation formula of the HS limit module is as follows:

[0026]

[0027] wherein: is the upper limit of the equivalent bulk modulus of the mixture; is the lower limit of the equivalent bulk modulus of the mixture; is the upper limit of the equivalent shear product modulus of the mixture; is the lower limit of the equivalent shear modulus of the mixture; is the maximum shear modulus in the mixture; is the minimum shear modulus in the mixture; is the maximum bulk modulus in the mixture; is the minimum bulk modulus in the mixture;

[0028] The isotropic SCA model of the dry brittle rock physics model is as follows:

[0029]

[0030] wherein, is the volume fraction of the i-th material; , are both the geometric factor of the i-th material; is the equivalent bulk modulus; is the equivalent shear modulus; N is the number of material types; is the equivalent bulk modulus of the i-th material, G i is the equivalent shear modulus of the i-th material;

[0031] The isotropic DEM model of the brittle rock physics model is:

[0032]

[0033] where, , B and G are the bulk and shear modulus of the inclusion, respectively; f is the volume fraction of the inclusion, dimensionless; B eq is the equivalent bulk modulus; G eq is the equivalent shear modulus; f 1 is the geometric factor 1 of the inclusion; f 2 is the geometric factor 2 of the inclusion;

[0034] The calculation formula of the anisotropic SCA model in the anisotropic SCA module is:

[0035]

[0036] where, C eq is the equivalent stiffness tensor of the SCA model; T n is the Eshelby stiffness tensor of the n-th phase material; I is the fourth-order unit stiffness tensor; C n is the stiffness tensor of the n-th phase material; f n is the volume fraction of the n-th phase material; N is the total number of phases of the material; f p is the volume fraction of the p-th phase material; T p is the Eshelby stiffness tensor of the p-th phase material; C p is the stiffness tensor of the p-th phase material;

[0037] The calculation formula of the anisotropic DEM model in the dry clay-cheese root mixture physics module is:

[0038]

[0039] where, C b is the stiffness tensor of the background medium; C i is the stiffness tensor of the inclusion; T i is the Eshelby stiffness tensor of the inclusion; I is the fourth-order unit stiffness tensor; V is the volume of the added item; C p is the stiffness tensor of the p-th phase material;

[0040] The calculation formula of the Backus averaging theory in the dry shale rock physics module is:

[0041]

[0042] wherein the symbol represents a weighted average by volume of the parameters in the parentheses; 、 、 、 、 is the equivalent dry shale stiffness coefficient; 、 、 、 、 is the stiffness coefficient of each material;

[0043] The Wood equation in the saturated fluid isotropic shale rock physics model is:

[0044]

[0045] wherein is the bulk modulus of the gas; is the bulk modulus of water; is the equivalent bulk modulus of the mixed fluid; is the gas saturation; is the equivalent bulk modulus of the mixed fluid;

[0046] The calculation equation of the Brown-Korringa model in the saturated fluid isotropic shale rock physics model is:

[0047]

[0048] wherein is the compliance tensor of the saturated rock; is the compliance tensor of the dry rock skeleton; 、 is the compressibility of the fluid and rock matrix; is the porosity; is the compressibility of the dry rock skeleton; is the compressibility of the rock matrix.

[0049] As preferred, in step four, when predicting the non-vertical section predicted acoustic travel time in the non-vertical section logging condition by using the non-vertical section anisotropic stiffness coefficient obtained in step three, the calculation equation used in the prediction is:

[0050]

[0051] wherein θ is the angle between the acoustic propagation direction and the normal direction of the isotropic shale formation; p is the density of the rock; c 11 ,c 13 、 c 33 、 c 44 、 c 66 is the rigidity coefficient of transverse isotropy; DTC, DTSV and DTSH are the time difference of P-wave, SV-wave and SH-wave respectively.

[0052] As preferred, in step five, when calculating the vertical time difference of the acoustic wave of the non-vertical well section after verticalization of the formation of the non-vertical well section, the calculation formula is:

[0053]

[0054] wherein, p is the density of the rock; c 33 、 c 44 is the rigidity coefficient of transverse isotropy; 、 are the vertical time difference of P-wave and the time difference of S-wave respectively after verticalization.

[0055] As preferred, in step six, when predicting the pore pressure of the shale formation of the non-vertical well section, the calculation formula is:

[0056]

[0057] wherein, is the predicted pore pressure of the formation; is the vertical ground stress; A and B are the fitting coefficients of the pore pressure of the formation; is the vertical time difference of P-wave after verticalization;

[0058] The vertical ground stress can be calculated by using the density logging data, and the specific calculation formula is:

[0059]

[0060] wherein, p is the density of the rock; g is the acceleration of gravity; TVD is the vertical depth.

[0061] A device for predicting the pore pressure of the shale formation of the non-vertical well section, comprising:

[0062] A data acquisition module for acquiring logging data;

[0063] A model construction module for constructing a transversely isotropic shale rock physics model;

[0064] The non-vertical well section anisotropic stiffness coefficient calculation model is used for inputting the shale physical property parameters in the non-vertical well section in the logging data obtained by the data acquisition module into the transversely isotropic shale rock physical model, and calculating the non-vertical well section anisotropic stiffness coefficient.

[0065] The non-vertical well section anisotropic stiffness coefficient output module is used for predicting the non-vertical well section predicted acoustic travel time in the non-vertical well section logging condition by using the non-vertical well section anisotropic stiffness coefficient calculated by the non-vertical well section anisotropic stiffness coefficient calculation model.

[0066] The non-vertical well section acoustic travel time calculation module is used for calculating the non-vertical well section acoustic travel time after verticalization of the non-vertical well section formation by using the non-vertical well section anisotropic stiffness coefficient output by the non-vertical well section anisotropic stiffness coefficient output module.

[0067] The pore pressure prediction module is used for predicting the pore pressure of the shale formation in the non-vertical well section by using the non-vertical well section acoustic travel time obtained by the non-vertical well section acoustic travel time calculation module and the vertical ground stress calculated by using the density logging data.

[0068] A computing device comprises a memory and a processor, the memory stores a computer program, and the processor implements the steps of the shale formation pore pressure prediction method in the non-vertical well section when executing the computer program.

[0069] A computer readable storage medium stores a computer program, and the computer program implements the steps of the shale formation pore pressure prediction method in the non-vertical well section when executed by a processor.

[0070] Compared with the prior art, the shale formation pore pressure prediction method in the non-vertical well section has the following beneficial effects:

[0071] The shale formation pore pressure prediction method in the non-vertical well section based on rock physical modeling is constructed, and the formation pore pressure predicted by the shale formation pore pressure prediction method in the non-vertical well section can provide basic data for subsequent shale formation ground stress prediction, mud density window determination, wellbore stability analysis and the like in the non-vertical well section.

[0072] The present application can effectively predict the shale formation pore pressure of the non-vertical well section by predicting the acoustic interval transit time of the non-vertical well section under the logging condition of the non-vertical well section, comparing the predicted acoustic interval transit time with the logging data, selectively outputting the anisotropic stiffness coefficient of the non-vertical well section according to the comparison result, calculating the vertical acoustic interval transit time of the non-vertical well section based on the anisotropic stiffness coefficient of the non-vertical well section, and using the vertical stress calculated by the density logging data, effectively solving the problem that the acoustic interval transit time of the non-vertical well section cannot be directly used for formation pore pressure prediction, and the prediction accuracy of the shale formation pore pressure is higher. BRIEF DESCRIPTION OF DRAWINGS

[0073] Figure 1 It is a flowchart of the present application;

[0074] Figure 2 It is a calculation flowchart of the present application;

[0075] The first track is a wellbore indication track, including: inclination, wellbore diameter, wellbore diameter expansion indication and gamma curve; the second track is a pore and fluid indication track, including: density, neutron, porosity and gas saturation; the third track is a shale component track, the shale minerals of the well include: quartz, clay, calcite, dolomite, feldspar, kerogen, pyrite; and the last track is the acoustic interval transit time measured by logging, wherein DTCm is the longitudinal wave interval transit time measured by logging, and DTSm is the transverse wave interval transit time measured by logging.

[0076] Figure 3 It is a shale physical parameter diagram of the present application;

[0077] Figure 4 It is a structure diagram of the transversely isotropic shale rock physics model of the present application;

[0078] Figure 5 It is a diagram of the formation acoustic verticalization result and the formation pore pressure gradient prediction result of the present application. DETAILED DESCRIPTION

[0079] The present application will be further described below in conjunction with the drawings. The embodiments of the present application include but are not limited to the following examples.

[0080] Example 1

[0081] The present embodiment provides a shale formation pore pressure prediction method for a non-vertical well section, and the specific steps are as shown in Figure 1 The specific steps are as follows:

[0082] Step 1: Obtain logging data;

[0083] The logging data is obtained by logging, and includes shale physical parameters, such as mineral components and content of each component, formation fluid components and content of each component, formation porosity, fluid saturation, etc. The mineral components include quartz, clay, calcite, dolomite, feldspar, kerogen and pyrite; and the formation fluid components mainly include gas and water.

[0084] Step two, constructing a transversely isotropic shale rock physics model;

[0085] In the construction of the transversely isotropic shale rock physics model, the transversely isotropic shale rock physics model includes an HS limit module, a dry brittle rock physics model, an anisotropic SCA module, a dry clay-kerogen mixture physics module, a dry shale rock physics module and a saturated fluid transversely isotropic shale rock physics model.

[0086] The HS limit module is configured to calculate the upper limit value and the lower limit value of the bulk modulus and the shear modulus of the brittle mineral mixture by using the Hashin-Shtrikman limit according to the shale physical parameters in the non-vertical well section in the logging data obtained in step one, and take the average of the upper limit value and the lower limit value as the bulk modulus and the shear modulus of the brittle mineral mixture.

[0087] When the HS limit module calculates the upper limit value and the lower limit value of the bulk modulus and the shear modulus of the brittle mineral mixture by using the Hashin-Shtrikman limit, the calculation formula is as follows:

[0088]

[0089] wherein, is the upper limit of the equivalent bulk modulus of the mixture, and the unit is GPa; is the lower limit of the equivalent bulk modulus of the mixture, and the unit is GPa; is the upper limit of the equivalent shear modulus of the mixture, and the unit is GPa; is the lower limit of the equivalent shear modulus of the mixture, and the unit is GPa; is the maximum shear modulus in the mixture, and the unit is GPa; is the minimum shear modulus in the mixture, and the unit is GPa; is the maximum bulk modulus in the mixture, and the unit is GPa; is the minimum bulk modulus in the mixture, and the unit is GPa.

[0090] The brittle rock physics model is used for adding inorganic pores into a brittle mineral mixture to obtain a brittle mineral equivalent mixture by using an isotropic SCA model and an isotropic DEM model, and establishing a rock physics model of the brittle rock; and taking the bulk modulus and the shear modulus output by the HS limit module as inputs of the rock physics model of the brittle rock.

[0091] The isotropic SCA model of the brittle rock physics model is as follows:

[0092]

[0093] wherein, is the volume fraction of the i-th material, dimensionless; i is the geometric factor 1 of the i-th material, dimensionless; , is the geometric factor 2 of the i-th material, dimensionless; i is the equivalent bulk modulus, unit: GPa; is the equivalent shear modulus, unit: GPa; N is the number of material types, dimensionless; is the equivalent bulk modulus of the i-th material, unit: GPa, is the equivalent shear modulus of the i-th material, unit: GPa.

[0094] The isotropic DEM model of the brittle rock physics model is as follows:

[0095]

[0096] wherein, , are the bulk modulus and the shear modulus of the inclusion, unit: GPa; is the volume fraction of the inclusion, dimensionless; is the equivalent bulk modulus, unit: GPa; is the equivalent shear modulus, unit: GPa;

[0097] and are the same, with v_vol indicating the added volume v; is the same as μ*, with v_vol indicating the added volume v, is the geometric factor 1 of the inclusion; is the geometric factor 2 of the inclusion;

[0098] The anisotropic SCA module is used for simulating the equivalent elastic properties of clay-cheese root by using an anisotropic SCA model, and calculating the corresponding equivalent elastic stiffness matrix.

[0099] ​The calculation formula of the anisotropic SCA model in the anisotropic SCA module is as follows:

[0100]

[0101] wherein, is the equivalent stiffness tensor of the SCA model, with the unit of GPa; is the Eshelby stiffness tensor of the nth phase material; is the fourth-order unit stiffness tensor, without dimension; is the stiffness tensor of the nth phase material, with the unit of GPa; is the volume fraction of the nth phase material; N is the total phase number of the material, without dimension; is the volume fraction of the pth phase material, without dimension; is the Eshelby stiffness tensor of the pth phase material, without dimension; is the stiffness tensor of the pth phase material, without dimension.

[0102] The dry clay-dry kerogen mixture physics module is configured to add inorganic pores into the clay-dry kerogen mixture by using the anisotropic DEM model to establish a rock physics model of the dry clay-dry kerogen mixture, and take the equivalent elastic stiffness matrix output by the anisotropic SCA module as the input of the dry clay-dry kerogen mixture physics module;

[0103] The calculation formula of the anisotropic DEM model in the dry clay-dry kerogen mixture physics module is as follows:

[0104]

[0105] wherein, is the stiffness tensor of the background medium, with the unit of GPa; is the inclusion stiffness tensor, with the unit of GPa; is the Eshelby stiffness tensor of the inclusion; is the fourth-order unit stiffness tensor; is the volume of the added item, with the unit of decimal; is the stiffness tensor of the pth phase material.

[0106] The dry shale rock physics module is configured to mix the dry clay-dry kerogen mixture and dry brittle rock by using the Backus averaging theory to establish a dry shale rock physics model, and take the output of the dry brittle rock physics model and the output of the dry clay-dry kerogen mixture physics module as the input of the dry shale rock physics module, and output the elastic tensor of the dry shale;

[0107] The calculation formula of the Backus averaging theory in the dry shale rock physics module is as follows:

[0108]

[0109] where the symbol represents a volume-weighted average of the parameters in the parentheses;

[0110] , , , , is the equivalent dry shale stiffness coefficient, with the unit of GPa;

[0111] , , , , is the stiffness coefficient of each substance, with the unit of GPa.

[0112] The saturated fluid transversely isotropic shale rock physics model is used to calculate the bulk modulus of the gas-water mixture in the pore according to the gas saturation and water saturation by using the Wood formula, and is converted into the stiffness tensor; the Brown-Korringa model is used to add the mixed fluid to the dry shale to obtain the saturated fluid shale, and the saturated fluid transversely isotropic shale rock physics model is established; the elastic tensor of the dry shale output by the dry shale rock physics module is taken as the input of the saturated fluid transversely isotropic shale rock physics model, and the non-vertical well section anisotropic stiffness coefficient is output by the saturated fluid transversely isotropic shale rock physics model.

[0113] The Wood formula in the saturated fluid transversely isotropic shale rock physics model is:

[0114]

[0115] where, is the bulk modulus of the gas, with the unit of GPa; is the bulk modulus of the water, with the unit of GPa; is the equivalent bulk modulus of the mixed fluid, with the unit of GPa; is the gas saturation; is the equivalent bulk modulus of the mixed fluid, with the unit of GPa;

[0116] The calculation formula of the Brown-Korringa model in the saturated fluid transversely isotropic shale rock physics model is:

[0117]

[0118] where, is the compliance tensor of the saturated rock, with the unit of GPa -1 . is the compliance tensor of dry rock skeleton, unit: GPa -1 ; is the compliance tensor of rock matrix, unit: GPa -1 ; unit: GPa -1 ; , is the compressibility of fluid and rock matrix, unit: GPa -1 ; is the porosity; is the compressibility of dry rock skeleton, 1 / GPa; is the compressibility of rock matrix, 1 / GPa.

[0119] When constructing the transversely isotropic shale rock physics model, the elastic modulus of each mineral and fluid is shown in Table 1.

[0120] Table 1 Elastic modulus of shale rock minerals and fluids

[0121]

[0122] Step three, inputting the shale physical property parameters in the non-vertical well section in the logging data obtained in step one into the transversely isotropic shale rock physics model, calculating the anisotropic stiffness coefficients in the non-vertical well section;

[0123] Using the constructed transversely isotropic shale rock physics model, five independent anisotropic stiffness coefficients can be predicted: , , , , .

[0124] Step four, using the anisotropic stiffness coefficients in the non-vertical well section obtained in step three to predict the non-vertical well section predicted acoustic travel time under the logging condition of the non-vertical well section; if the difference between the predicted non-vertical well section predicted acoustic travel time and the non-vertical well section acoustic travel time in the logging data is less than a preset threshold, outputting the anisotropic stiffness coefficients in the non-vertical well section, and entering step five; if the difference between the predicted non-vertical well section predicted acoustic travel time and the non-vertical well section acoustic travel time in the logging data is greater than the preset threshold, returning to step two, resetting the pore aspect ratio, and constructing the transversely isotropic shale rock physics model again until the difference between the predicted non-vertical well section predicted acoustic travel time and the non-vertical well section acoustic travel time in the logging data is less than the preset threshold;

[0125] When predicting the non-vertical well section predicted acoustic travel time under the logging condition of the non-vertical well section using the anisotropic stiffness coefficients in the non-vertical well section obtained in step three, the calculation formula used for prediction is:

[0126]

[0127] in, θ The angle between the direction of sound wave propagation and the direction of the normal to the transversely isotropic shale formation is expressed in rad. p Density of rock, in g / cm³ 3 ; c 11 , c 13 , c 33 , c 44 , c 66 is the transversely isotropic stiffness coefficient, in GPa; DTC, DTSV, and DTSH are the time differences of longitudinal waves, SV transverse waves, and SH transverse waves, respectively, in µs / ft.

[0128] The predicted P-wave and S-wave transit times under non-vertical well logging conditions are compared with the measured P-wave and S-wave transit times as follows: Figure 5 The fourth longitudinal wave time difference channel and Figure 4 As shown in the fifth transverse wave time channel, longitudinal wave time channel (DTC) was used in the process of constructing the transversely isotropic shale petrographic model. m Constraints were applied to the model's construction results, therefore the predicted P-wave transit time (PTS) in the deviated well case is not significantly different from the PTS measured by well logging, with relative errors ranging from -6.75% to 3.18%, and an average absolute relative error of 1.49%, indicating high accuracy. Regarding the predicted S-wave transit time (DTS), the well logging data provides a DTS... m Corresponding to SV shear wave, shear wave time difference DTSV and logging shear wave time difference DTS m The relative error ranges from -11.85% to 3.34%, with an average absolute value of 3.85%, which meets the requirements of engineering applications.

[0129] Step 5: Using the anisotropic stiffness coefficient of the non-vertical well section output in Step 4, calculate the acoustic transit time of the non-vertical well section after formation verticalization.

[0130] When calculating the acoustic transit time of the non-vertical well section after formation verticalization, the formula is as follows:

[0131]

[0132] in, p Density of rock, in g / cm³ 3 ; c 33 , c 44 The stiffness coefficient is transversely isotropic and is expressed in GPa. , The vertical wave time difference and the transverse wave time difference after verticalization, respectively, in units of us / ft.

[0133] In Figure 5 the 6th column of Table 1, DTC0° represents the vertical wave time difference after verticalization, which is larger than the vertical wave time difference before verticalization. According to statistics, the relative difference between the vertical wave time differences before and after verticalization is between 9.59% and 32.01%, and the average relative difference is 20.04%. The difference between the vertical wave time differences before and after verticalization is large, which has a non-negligible impact on engineering applications. DTS0° represents the transverse wave time difference after verticalization. Generally, the transverse wave time differences before and after verticalization are of different sizes. According to statistics, the relative difference between the transverse wave time differences before and after verticalization is between -5.41% and 13.76%, and the average absolute value of the relative difference is 6.31%.

[0134] Step six, based on the non-vertical well section acoustic time difference obtained in step five, the vertical stress is calculated using the density logging data to predict the shale formation pore pressure in the non-vertical well section.

[0135] When predicting the shale formation pore pressure in the non-vertical well section, the calculation formula is:

[0136]

[0137] wherein, P is the predicted formation pore pressure, in units of MPa; σz is the vertical stress, in units of MPa; A and B are formation pore pressure fitting coefficients; DTC0° is the vertical wave time difference after verticalization, in units of us / ft;

[0138] Vertical stress can be calculated using density logging data, and the specific calculation formula is:

[0139]

[0140] wherein, p ρ is the density of rock, in units of g / cm 3 ; g g is the acceleration of gravity, in units of m / s 2 ; TVD h is the vertical depth, in units of m.

[0141] In order to facilitate comparison with the actual drilling fluid density, the predicted formation pore pressure is converted into equivalent density, and the results are shown in Figure 5 column 6. From top to bottom, the purple origin is the formation pore pressure equivalent density obtained by micro-annular test at X056.125 m in the well, which is 1.74 g / cm 3 ; the black curve is the actual drilling fluid density during drilling, which is 1.63 g / cm 3The red curve is the formation pore pressure equivalent density predicted by using the uncorrected acoustic travel time DTCm, and the predicted result at X056.125 m is 1.08 g / cm 3 Compared with the measured result, the relative error is 37.93%. The blue curve is the formation pore pressure equivalent density predicted by using the corrected acoustic travel time DTC0°, and the predicted result at X056.125 m is 1.81 g / cm 3 Compared with the measured result, the relative error is 4.02%; from the predicted results of the corrected and uncorrected formation pore pressure equivalent densities, it is obvious that the accuracy of the formation pore pressure equivalent density predicted by using the corrected acoustic travel time is higher. In addition, the formation pore pressure equivalent density predicted by using the uncorrected acoustic travel time is less than the actual drilling fluid density, and the gas invasion phenomenon occurs in the well sections of X055.00-X059.45 m and X065.00-X075.00 m (in the range of the blue square in the figure), which indicates that the formation pore pressure equivalent density in the above two depth sections is greater than the drilling fluid density, and the formation pore pressure equivalent density predicted by using the uncorrected acoustic travel time is greatly different from the actual situation, but the formation pore pressure equivalent density predicted by using the corrected acoustic travel time is greater than the actual drilling fluid density, which is more consistent with the actual situation.

[0142] Embodiment 2

[0143] The embodiment also provides a shale formation pore pressure prediction device for a non-vertical well section, comprising:

[0144] a data acquisition module configured to acquire logging data;

[0145] a model construction module configured to construct a transversely isotropic shale rock physics model;

[0146] a non-vertical well section anisotropic stiffness coefficient calculation model configured to input the non-vertical well section shale physical property parameters in the logging data acquired by the data acquisition module into the transversely isotropic shale rock physics model and calculate a non-vertical well section anisotropic stiffness coefficient;

[0147] a non-vertical well section anisotropic stiffness coefficient output module configured to predict a non-vertical well section predicted acoustic travel time under a non-vertical well section logging condition by using the non-vertical well section anisotropic stiffness coefficient calculated by the non-vertical well section anisotropic stiffness coefficient calculation model; if the difference between the predicted non-vertical well section predicted acoustic travel time and the non-vertical well section acoustic travel time in the logging data is less than a preset threshold, output the non-vertical well section anisotropic stiffness coefficient and enter a non-vertical well section acoustic travel time calculation module; if the difference between the predicted non-vertical well section predicted acoustic travel time and the non-vertical well section acoustic travel time in the logging data is greater than the preset threshold, return to the model construction module and reconstruct the transversely isotropic shale rock physics model.

[0148] a non-vertical well section acoustic travel time calculation module configured to calculate a non-vertical well section acoustic travel time of a verticalized non-vertical well section formation based on the non-vertical well section anisotropy stiffness coefficient output by the non-vertical well section anisotropy stiffness coefficient output module;

[0149] a pore pressure prediction module configured to predict a pore pressure of a shale formation in the non-vertical well section based on the non-vertical well section acoustic travel time calculated by the non-vertical well section acoustic travel time calculation module and a vertical in-situ stress calculated based on the density logging data.

[0150] Embodiment 3

[0151] The embodiment also provides a computing device including a memory and a processor, wherein the memory stores a computer program, and the processor implements the steps of the shale formation pore pressure prediction method in the non-vertical well section as described above when executing the computer program.

[0152] The computer device can be a desktop computer, a notebook computer, a palm computer, a cloud server, or the like. The computer device can interact with a user through a keyboard, a mouse, a remote controller, a touchpad, a voice control device, or the like.

[0153] The memory includes at least one type of readable storage medium, such as a flash memory, a hard disk, a multimedia card, a card-type memory (e.g., an SD or D interface display memory, or the like), a random access memory (RAM), a static random access memory (SRAM), a read-only memory (ROM), an electrically erasable programmable read-only memory (EEPROM), a programmable read-only memory (PROM), a magnetic memory, a magnetic disk, an optical disk, or the like. In some embodiments, the memory can be an internal storage unit of the computer device, such as a hard disk or a memory of the computer device. In other embodiments, the memory can also be an external storage device of the computer device, such as a plug-in hard disk, a smart media card (SMC), a secure digital (SD) card, a flash card, or the like. Of course, the memory can include both the internal storage unit and the external storage device of the computer device. In the embodiment, the memory is usually used to store an operating system and various application software installed in the computer device, such as program codes of the shale formation pore pressure prediction method in the non-vertical well section, or the like. In addition, the memory can also be used to temporarily store various data that have been output or will be output.

[0154] The processor can be a Central Processing Unit (CPU), a controller, a microcontroller, a microprocessor, or other data processing chip in some embodiments. The processor is generally used to control the overall operation of the computer device. In the present embodiment, the processor is used to run program codes or process data stored in the memory, for example, program codes of the non-vertical well section shale formation pore pressure prediction method.

[0155] Embodiment 4

[0156] The present embodiment also provides a computer readable storage medium, and the computer readable storage medium stores a computer program. The computer program is executed by a processor to implement the steps of the non-vertical well section shale formation pore pressure prediction method described above.

[0157] The computer readable storage medium stores an interface display program, and the interface display program can be executed by at least one processor to enable the at least one processor to perform the steps of the non-vertical well section shale formation pore pressure prediction method described above.

[0158] From the above description of the embodiments, those skilled in the art can clearly understand that the above-mentioned embodiment method can be realized by means of software and the necessary general hardware platform, of course, it can also be realized by hardware, but in many cases, the former is a better embodiment. Based on such understanding, the technical solutions of the present application can be embodied in the form of a software product in essence or in the form of a contribution to the prior art. The computer software product is stored in a storage medium (such as a ROM / RAM, a magnetic disk, or an optical disk), and includes a plurality of instructions for enabling a terminal device (which can be a mobile phone, a computer, a server, or a network device, etc.) to perform the methods described in the various embodiments of the present application.

Claims

1. A method for predicting pore pressure in a shale formation for a non-vertical well section, the method comprising: The method comprises the following steps: Step one, obtaining logging data; Step two, constructing a transversely isotropic shale rock physics model, the transversely isotropic shale rock physics model comprising: a HS limit module, configured to calculate upper limit values and lower limit values of bulk modulus and shear modulus of a brittle mineral mixture by using Hashin-Shtrikman limits according to shale physical parameters in a non-vertical well section in the logging data obtained in step one, and taking an average of the upper limit values and the lower limit values as the bulk modulus and the shear modulus of the brittle mineral mixture; a dry brittle rock physics model, configured to add inorganic pores to the brittle mineral mixture to obtain a brittle mineral equivalent mixture by using an isotropic SCA model and an isotropic DEM model, and establish a rock physics model of a dry brittle rock; and taking the bulk modulus and the shear modulus output by the HS limit module as input of the dry brittle rock physics model; an anisotropic SCA module, configured to simulate equivalent elastic properties of clay-chei equivalent by using an anisotropic SCA model, and calculate a corresponding equivalent elastic stiffness matrix; a dry clay-chei mixture physics module, configured to add inorganic pores to the clay-chei mixture to establish a rock physics model of a dry clay-chei mixture by using an anisotropic DEM model; and taking the equivalent elastic stiffness matrix output by the anisotropic SCA module as input of the dry clay-chei mixture physics module; a dry shale rock physics module, configured to mix the dry clay-chei mixture and the dry brittle rock to establish a dry shale rock physics model by using Backus average theory; taking output of the dry brittle rock physics model and output of the dry clay-chei mixture physics module as input of the dry shale rock physics module, and outputting an elastic tensor of the dry shale; a saturated fluid transversely isotropic shale rock physics model, configured to calculate bulk modulus of a gas-water mixture in pores by using a Wood formula according to gas saturation and water saturation, and convert the bulk modulus into a stiffness tensor; add the mixed fluid to the dry shale to obtain a saturated fluid shale, and establish a saturated fluid transversely isotropic shale rock physics model by using a Brown-Korringa model; take the elastic tensor of the dry shale output by the dry shale rock physics module as input of the saturated fluid transversely isotropic shale rock physics model, and output anisotropic stiffness coefficients of the non-vertical well section by the saturated fluid transversely isotropic shale rock physics model; Step three, inputting shale physical parameters in the non-vertical well section in the logging data obtained in step one into the transversely isotropic shale rock physics model, and calculating anisotropic stiffness coefficients of the non-vertical well section. In step four, the non-vertical well section anisotropic stiffness coefficient obtained in step three is used to predict the non-vertical well section predicted acoustic interval in the non-vertical well section logging condition; if the difference between the predicted non-vertical well section predicted acoustic interval and the non-vertical well section acoustic interval in the logging data is less than a preset threshold, the non-vertical well section anisotropic stiffness coefficient is output, and step five is entered; if the difference between the predicted non-vertical well section predicted acoustic interval and the non-vertical well section acoustic interval in the logging data is greater than the preset threshold, step two is returned to rebuild the transversely isotropic shale rock physical model; In step five, the non-vertical well section anisotropic stiffness coefficient output in step four is used to calculate the non-vertical well section acoustic interval after verticalization of the non-vertical well section formation, and in the calculation of the non-vertical well section acoustic interval after verticalization of the non-vertical well section formation, the calculation formula is: wherein, In step six, based on the non-vertical well section acoustic interval obtained in step five, the vertical in-situ stress calculated by using the density logging data is used to predict the non-vertical well section shale formation pore pressure. D is the density of the rock; c33, c44 are the stiffness coefficients of transverse isotropy; DTC0°, DTS0° are the vertical converted compressional and shear time differences, respectively; The non-vertical well section shale physical parameters include mineral components and the content of each component, formation fluid components and the content of each component, formation porosity, and fluid saturation.

2. A method of predicting pore pressure in a shale formation for a non-vertical well section according to claim 1, wherein:

3. The non-vertical well section shale formation pore pressure prediction method according to claim 1, wherein: In the calculation of the upper limit value and the lower limit value of the bulk modulus and the shear modulus of the brittle mineral mixture by using the Hashin-Shtrikman limit in the HS limit module, the calculation formula is: The isotropic SCA model of the dry brittle rock physical model is: wherein: is the upper limit of the equivalent volume modulus of the mixture; is the lower limit of the equivalent volume modulus of the mixture; is the upper limit of the equivalent shear product modulus of the mixture; is the lower limit of the equivalent shear modulus of the mixture; is the maximum shear modulus in the mixture; is the minimum shear modulus in the mixture; is the maximum volume modulus in the mixture; is the minimum volume modulus in the mixture; The isotropic DEM model of the dry brittle rock physical model is: In the formula, For the first i Volume fraction of the material; , All are the first i Geometric factors of the material; This is the equivalent bulk modulus; The equivalent shear modulus; N is the number of material types; For the first i The equivalent bulk modulus of the material For the first i The equivalent shear modulus of the material; The calculation formula of the anisotropic SCA model in the anisotropic SCA module is: wherein, , are the bulk modulus and the shear modulus of the inclusion, respectively; is the volume fraction of the inclusion, dimensionless; is the equivalent bulk modulus; is the equivalent shear modulus; is the geometric factor 1 of the inclusion; is the geometric factor 2 of the inclusion; The calculation formula of the anisotropic DEM model in the dry clay-dry kerogen mixture physical module is: wherein, is the stiffness tensor equivalent to the SCA model; is the Eshelby stiffness tensor of the nth phase material; is the fourth order unit stiffness tensor; is the stiffness tensor of the nth phase material; is the volume fraction of the nth phase material; N is the total number of phases of the material; is the volume fraction of the pth phase material; is the Eshelby stiffness tensor of the pth phase material; is the stiffness tensor of the pth phase material; The calculation formula of the Backus average theory in the dry shale rock physical module is: wherein, is the background medium stiffness tensor; is the inclusion stiffness tensor; is the Eshelby stiffness tensor for the inclusion; is the fourth order unit stiffness tensor; is the volume of the added item; is the stiffness tensor of the p-th phase material; The Wood formula in the saturated fluid transversely isotropic shale rock physical model is: wherein the symbols represent a weighted average by volume of the parameters in the parentheses; , , , , is the equivalent dry shale stiffness coefficient; , , , , is the stiffness coefficient of each material; The calculation formula of the Brown-Korringa model in the saturated fluid transversely isotropic shale rock physical model is: wherein, is the bulk modulus of the gas; is the bulk modulus of water; is the equivalent bulk modulus of the mixed fluid; is the gas saturation; is the equivalent bulk modulus of the mixed fluid; In step four, in the prediction of the non-vertical well section predicted acoustic interval in the non-vertical well section logging condition by using the non-vertical well section anisotropic stiffness coefficient obtained in step three, the calculation formula used in the prediction is: wherein, is the compliance tensor of the saturated rock; is the compliance tensor of the dry rock skeleton; , is the compressibility coefficient of the fluid and rock matrix distribution; is the porosity; is the compressibility coefficient of the dry rock skeleton; is the compressibility coefficient of the rock matrix.

4. The method of predicting pore pressure in a shale formation of a non-vertical well section of claim 1, wherein: In step six, in the prediction of the non-vertical well section shale formation pore pressure, the calculation formula is: wherein, Wherein, ρ is the density of rock; g is the acceleration of gravity; and TVD is the vertical depth. is the angle between the direction of sound wave propagation and the normal direction of the transversely isotropic shale formation; The data acquisition module is configured to acquire logging data. is the density of the rock; c 11 , c 13 , c 33 , c 44 , c 66 is the stiffness coefficient of transverse isotropy; DTC, DTSV, DTSH are the time difference of P-wave, SV-wave, SH-wave, respectively.

5. The method of predicting pore pressure in a shale formation of a non-vertical well section of claim 1, wherein: The model building module is configured to build a transversely isotropic shale rock physical model, and the transversely isotropic shale rock physical model comprises: wherein, is the predicted formation pore pressure; is the vertical in-situ stress; A and B are formation pore pressure fitting coefficients; is the vertical slowness of the P-wave; Vertical stress The vertical stress can be calculated using density log data, with the formula: The HS limit module is configured to calculate the upper limit value and the lower limit value of the bulk modulus and the shear modulus of the brittle mineral mixture by using the Hashin-Shtrikman limit according to the non-vertical well section shale physical parameters in the logging data acquired in step one, and take the average value of the upper limit value and the lower limit value as the bulk modulus and the shear modulus of the brittle mineral mixture.

6. A non-vertical section shale formation pore pressure prediction device characterized by, ​ ​ ​ ​ The dry brittle rock physics model is used for adding inorganic pores into the brittle mineral mixture to obtain a brittle mineral equivalent mixture by using the isotropic SCA model and the isotropic DEM model, and establishing a rock physics model of the dry brittle rock; the bulk modulus and the shear modulus output by the HS boundary module are taken as inputs of the dry brittle rock physics model; The anisotropic SCA module is used for simulating equivalent elastic properties of clay-ketone and calculating a corresponding equivalent elastic stiffness matrix by using the anisotropic SCA model; The dry clay-ketone mixture physics module is used for adding inorganic pores into the clay-ketone mixture to establish a rock physics model of the dry clay-ketone mixture by using the anisotropic DEM model; the equivalent elastic stiffness matrix output by the anisotropic SCA module is taken as an input of the dry clay-ketone mixture physics module; The dry shale rock physics module is used for mixing the dry clay-ketone mixture and the dry brittle rock to establish a dry shale rock physics model by using the Backus average theory; the outputs of the dry brittle rock physics model and the dry clay-ketone mixture physics module are taken as inputs of the dry shale rock physics module, and an elastic tensor of the dry shale is output; The saturated fluid transversely isotropic shale rock physics model is used for calculating a bulk modulus of a gas-water mixture in a pore according to a gas saturation and a water saturation by using a Wood formula, and converting the bulk modulus into a stiffness tensor; the saturated fluid shale is obtained by adding the mixed fluid into the dry shale to establish the saturated fluid transversely isotropic shale rock physics model by using a Brown-Korringa model; the elastic tensor of the dry shale output by the dry shale rock physics module is taken as an input of the saturated fluid transversely isotropic shale rock physics model, and an anisotropic stiffness coefficient of a non-vertical well section is output by the saturated fluid transversely isotropic shale rock physics model; The non-vertical well section anisotropic stiffness coefficient calculation model is used for inputting shale physical property parameters of the non-vertical well section in the logging data obtained by the data acquisition module into the transversely isotropic shale rock physics model, and calculating the anisotropic stiffness coefficient of the non-vertical well section; The non-vertical well section anisotropic stiffness coefficient output module is used for predicting a non-vertical well section predicted acoustic travel time in the non-vertical well section logging condition by using the anisotropic stiffness coefficient of the non-vertical well section obtained by the non-vertical well section anisotropic stiffness coefficient calculation model; if a difference between the predicted non-vertical well section predicted acoustic travel time and the non-vertical well section acoustic travel time in the logging data is less than a preset threshold, the anisotropic stiffness coefficient of the non-vertical well section is output, and the non-vertical well section acoustic travel time calculation module is entered; if the difference between the predicted non-vertical well section predicted acoustic travel time and the non-vertical well section acoustic travel time in the logging data is greater than the preset threshold, the model construction module is returned, and the transversely isotropic shale rock physics model is reconstructed; The non-vertical well section acoustic travel time calculation module is used for calculating a non-vertical well section acoustic travel time of a verticalized non-vertical well section formation by using the anisotropic stiffness coefficient of the non-vertical well section output by the non-vertical well section anisotropic stiffness coefficient output module; in the calculation of the non-vertical well section acoustic travel time of the verticalized non-vertical well section formation, a calculation formula is as follows: wherein, ​ is the density of the rock; c 33 , c 44 is the transversely isotropic stiffness coefficient; DTC0°, DTS0° are the vertical converted compressional and shear time differences, respectively. A pore pressure prediction module is configured to predict the pore pressure of the shale formation in the non-vertical well section based on the acoustic travel time of the non-vertical well section obtained by the acoustic travel time calculation module, and the vertical stress calculated by the density logging data.

7. A computing device, characterized by: The non-vertical well section shale formation pore pressure prediction method comprises a memory and a processor, the memory stores a computer program, and the processor executes the computer program to realize the steps of the non-vertical well section shale formation pore pressure prediction method.

8. A computer-readable storage medium, characterized in that: The readable storage medium stores a computer program, and the computer program is executed by the processor to realize the steps of the non-vertical well section shale formation pore pressure prediction method.

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