Tight reservoir formation index prediction method

Abstract

The invention provides a tight reservoir formation index prediction method, and the method comprises the steps: 1, carrying out the pre-stack seismic elastic parameter inversion, and obtaining the three-dimensional space distribution of a plurality of elastic parameters; 2, based on rock physical analysis, establishing a porosity prediction model; 3, establishing an equivalent hydrocarbon expulsion pressure prediction model based on the porosity of the sand body; establishing a formation pressure and residual surrounding rock pressure prediction model based on the hydrostatic pressure and the well point actual measurement pressure coefficient; and 4, establishing a reservoir forming index prediction model, obtaining quantitative evaluation parameters of the deep compact clastic rock reservoir based on the reservoir forming index, and predicting the deep compact reservoir. Quantitative evaluation of the sweet spots of the deep compact clastic rock reservoir is achieved, the targets of favorable zones and the sweet spots are implemented, and a basis is provided for exploration and development of compact reservoirs.

Description

Technical Field

[0001] The invention relates to the technical field of geophysical exploration and development, and in particular to a method for predicting a tight reservoir accumulation index. Background Art

[0002] In recent years, many scholars at home and abroad have conducted fruitful research on reservoir physical parameters and lithologic oil and gas reservoir formation conditions. However, the prediction methods and evaluation methods of its reservoir formation conditions are all realized by applying actual drilling data and logging data. In the absence of drilling and logging data, it is still impossible to effectively predict and quantitatively calculate the factors of lithologic oil and gas reservoir formation.

[0003] The use of dynamic ideas and methods to study the process of oil and gas accumulation is the direction that the petroleum geology community has been working on. Many scholars have studied the dynamics of accumulation and believe that the expansion force generated by hydrocarbon generation and the diffusion force caused by hydrocarbon concentration difference are the main driving forces for the accumulation of lithologic oil reservoirs, while rock adsorption and viscosity are the main resistances to accumulation. The dynamic genesis types of sandstone lenses include capillary force overpressure joint control type and overpressure single control type. Sandstone lens oil and gas reservoirs in a strong overpressure state may have two fluid discharge modes, lateral and vertical. It is proposed to use equivalent hydrocarbon expulsion pressure and accumulation index to evaluate the formation of lithologic oil reservoirs. Exploration practice shows that the oil content of lithologic traps varies greatly, and most of the current research is in the qualitative evaluation stage. The quantitative evaluation of the oil content of lithologic traps has become an important basis for influencing exploration decisions. Therefore, starting from the dynamics of accumulation, it is of great significance to study the oil content of lithologic oil and gas reservoirs. According to reservoir dynamics theory, after the oil and gas in the source rock is generated, abnormal fluid high pressure is formed under the action of overlying strata compaction and hydrothermal pressurization, resulting in a residual pressure difference between the source rock and the reservoir rock mass, which becomes the driving force for the formation of lithologic oil and gas reservoirs. The formation of lithologic oil and gas reservoirs is the result of the combined action of reservoir dynamics (i.e., residual surrounding rock pressure) and reservoir resistance, so there is a need for parameters that comprehensively reflect the results of the combined action of the two. According to reservoir dynamics analysis, the greater the residual surrounding rock pressure reflecting reservoir dynamics, the stronger the ability of oil and gas to enter lithologic traps; under the same reservoir dynamics conditions, the smaller the equivalent hydrocarbon expulsion pressure reflecting reservoir resistance, the greater the possibility of oil and gas entering lithologic traps; conversely, the smaller the possibility of reservoir formation. Summary of the invention

[0004] In view of the above problems, the present invention is proposed to provide a method for predicting tight reservoir accumulation index that overcomes the above problems or at least partially solves the above problems.

[0005] According to one aspect of the present invention, a method for predicting a tight reservoir accumulation index is provided, the method comprising:

[0006] Step 1: Perform pre-stack seismic elastic parameter inversion to obtain the three-dimensional spatial distribution of multiple elastic parameters;

[0007] Step 2: Establish a porosity prediction model based on rock physics analysis;

[0008] Step 3: Establish an equivalent hydrocarbon expulsion pressure prediction model based on the sand body porosity; establish a formation pressure and residual surrounding rock pressure prediction model based on the hydrostatic pressure and the well point measured pressure coefficient;

[0009] Step 4: Establish a reservoir-forming index prediction model, obtain quantitative evaluation parameters of deep tight clastic reservoirs based on the reservoir-forming index, and predict deep tight reservoirs.

[0010] Optionally, the multiple elastic parameters include: longitudinal and shear wave velocities, density, and Poisson's ratio.

[0011] Optionally, the step 2: establishing a porosity prediction model based on rock physics analysis specifically includes:

[0012] Based on rock physics analysis, a porosity prediction model is established using drilling and logging data.

[0013] Optionally, the step 3, establishing an equivalent hydrocarbon expulsion pressure prediction model based on sand body porosity; and establishing a formation pressure and residual surrounding rock pressure prediction model based on hydrostatic pressure and well point measured pressure coefficient specifically includes:

[0014] During the sediment deposition and compaction process, the mechanical relationship between the residual surrounding rock pressure Ps and the change of porosity and the formation of abnormal pore pressure conforms to the effective stress formula:

[0015] P s =P f -P ov

[0016] Where: Pf is the pore fluid pressure (Mpa), Pov is the overlying formation pressure (Mpa).

[0017] Optionally, the overlying formation pressure refers to the pressure formed by the weight of the overlying rock skeleton and the fluid in the pore space;

[0018] P ov =H[(1-φ)ρ ma +φρ f ] or P ov =ρ av gh

[0019] Among them, P ov is the overlying formation pressure, MPa, which increases with the depth H; φ represents the average porosity of the overlying rock formation, dimensionless; ρ ma is the average density of the overlying rock matrix g / cm3; ρ f is the average density of the pore fluid in the overlying rock layer g / cm3; ρ maIt is the average density of the overlying strata, g / cm3.

[0020] Optionally, the pore fluid pressure P f The calculation formula is as follows:

[0021] P f =P p +P g =P p +(P ov -P h )

[0022] Among them, P f is the pore fluid pressure MPa, P ov is the overlying formation pressure MPa, P p is the formation pressure MPa; Pg is the particle support pressure, also known as the rock skeleton pressure MPa; P h Represents the hydrostatic pressure in MPa.

[0023] Optionally, the residual surrounding rock pressure Ps is rewritten as:

[0024] P s =P f -P ov =P p +(P ov -P h )-P ov =P p -P h

[0025] The formation pressure Pp is measured by the well point pressure coefficient α p Calculated with the hydrostatic pressure Ph, where the pressure coefficient α p It is the ratio of actual formation pressure to hydrostatic pressure, reflecting the degree of deviation of the formation pressure value at a certain point in the formation from the normal formation pressure value, dimensionless:

[0026]

[0027] Among them, Ph represents the hydrostatic pressure in MPa; Pp represents the formation pressure in MPa.

[0028] Optionally, the value of the hydrostatic pressure is related to the density of the fluid and the height of the fluid column, and has nothing to do with the size, shape and distribution range of the fluid. The calculation formula is as follows:

[0029] P h =l0 -3 ρ w gh

[0030] Among them, ρ wrepresents the average density of formation water g / cm3, h represents the vertical height of the water column m, and g is the acceleration of gravity m / s 2 ;

[0031] Hydrostatic pressure generally increases with depth, with the rate of change being related only to density;

[0032] Density is often related to its salinity, temperature and dissolved gas content. The density of pure water is 1.0g / cm3, and the density of salt water is 1.04g / cm3.

[0033] Optionally, the equivalent hydrocarbon expulsion pressure is closely related to the porosity. e Empirical relationship with porosity: in, is the porosity of the sand body, p e is the equivalent hydrocarbon discharge pressure MaP, a and b are empirical coefficients.

[0034] Optionally, in step 4, a reservoir formation index prediction model is established to obtain quantitative evaluation parameters of deep tight clastic reservoirs based on the reservoir formation index. Predicting deep tight reservoirs specifically includes:

[0035] Through the analysis of pore fluid pressure, equivalent hydrocarbon expulsion pressure and residual surrounding rock pressure, a prediction model for the accumulation index of tight reservoirs is established;

[0036] The calculation formula of reservoir index is: I d =P s / P e

[0037] Among them, I d It is the reservoir-forming index of the sand body, a dimensionless quantity. The larger its value is, the more conducive it is for the sand body to form lithologic oil and gas reservoirs, and vice versa. Ps is the residual surrounding rock pressure in MPa, and Pe is the equivalent hydrocarbon expulsion pressure in MPa.

[0038] The present invention provides a method for predicting the accumulation index of a tight reservoir, the method comprising: step 1: performing pre-stack seismic elastic parameter inversion to obtain the three-dimensional spatial distribution of multiple elastic parameters; step 2: establishing a porosity prediction model based on rock physics analysis; step 3: establishing an equivalent hydrocarbon expulsion pressure prediction model based on sand body porosity; establishing a formation pressure and residual surrounding rock pressure prediction model based on hydrostatic pressure and well point measured pressure coefficient; step 4: establishing an accumulation index prediction model, obtaining quantitative evaluation parameters of deep tight clastic reservoirs based on the accumulation index, and predicting deep tight reservoirs. The method realizes the quantitative evaluation of the "sweet spots" of deep tight clastic reservoirs, forms a "sweet spot" prediction technology suitable for the exploration and development of deep tight reservoirs, implements favorable zones and "sweet spot" targets, and provides a basis for the exploration and development of tight reservoirs. The method has good application effects and promotion prospects.

[0039] The above description is only an overview of the technical solution of the present invention. In order to more clearly understand the technical means of the present invention, it can be implemented according to the contents of the specification. In order to make the above and other purposes, features and advantages of the present invention more obvious and easy to understand, the specific implementation methods of the present invention are listed below. BRIEF DESCRIPTION OF THE DRAWINGS

[0040] In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the accompanying drawings required for use in the description of the embodiments will be briefly introduced below. Obviously, the accompanying drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other accompanying drawings can be obtained based on these accompanying drawings without paying creative work.

[0041] Figure 1 A flowchart of a method for predicting a tight reservoir accumulation index provided by an embodiment of the present invention;

[0042] Figure 2 The longitudinal wave velocity well section in a specific embodiment 1 of the present invention;

[0043] Figure 3 The shear wave velocity well section in a specific embodiment 1 of the present invention;

[0044] Figure 4 The density well-connected profile in a specific embodiment 1 of the present invention;

[0045] Figure 5 It is a porosity well-connected profile in a specific embodiment of the present invention;

[0046] Figure 6 The plane distribution of the porosity of the main sand body in a specific embodiment 1 of the present invention;

[0047] Figure 7 The equivalent hydrocarbon expulsion pressure prediction model in a specific embodiment 1 of the present invention;

[0048] Figure 8 It is a well-connected section of the reservoir formation index in a specific embodiment 1 of the present invention;

[0049] Fig. 9 The planar distribution of the reservoir forming index in a specific embodiment 1 of the present invention;

[0050] Fig.10 A reservoir histogram for identifying reservoirs by the reservoir forming index in a specific embodiment 1 of the present invention;

[0051] Fig.11 The longitudinal wave velocity well section in a specific embodiment 2 of the present invention;

[0052] Fig.12The shear wave velocity well-connected profile in a specific embodiment 2 of the present invention;

[0053] Fig.13 It is a density well-connected profile in a specific embodiment 2 of the present invention;

[0054] Fig.14 It is a 2-porosity well-connected profile in a specific embodiment of the present invention;

[0055] Fig.15 This is the planar distribution of the porosity of the main sand body in a specific embodiment 2 of the present invention.

[0056] Fig.16 It is a well-connected section of the reservoir formation index in a specific embodiment 2 of the present invention;

[0057] Fig.17 This is the planar distribution of the reservoir formation index in a specific embodiment 2 of the present invention. DETAILED DESCRIPTION

[0058] The exemplary embodiments of the present disclosure will be described in more detail below with reference to the accompanying drawings. Although the exemplary embodiments of the present disclosure are shown in the accompanying drawings, it should be understood that the present disclosure can be implemented in various forms and should not be limited by the embodiments set forth herein. On the contrary, these embodiments are provided to enable a more thorough understanding of the present disclosure and to fully convey the scope of the present disclosure to those skilled in the art.

[0059] The terms "comprises" and "having" and any variations thereof in the description embodiments, claims and drawings of the present invention are intended to cover non-exclusive inclusions, for example, including a series of steps or units.

[0060] The technical solution of the present invention is further described in detail below in conjunction with the accompanying drawings and embodiments.

[0061] like Figure 1 As shown, Figure 1 The flowchart of the method for quantitatively predicting the accumulation index of tight reservoirs based on three-dimensional prestack seismic inversion of the present invention is shown in FIG. The modeling method includes the following steps:

[0062] Step 1: Perform pre-stack seismic elastic parameter inversion to obtain the three-dimensional spatial distribution of various elastic parameters such as P-wave velocity, S-wave velocity, density, and Poisson's ratio.

[0063] Step 2: Based on rock physics analysis and using drilling and logging data, a porosity prediction model is established.

[0064] Step 3: Establish an equivalent hydrocarbon expulsion pressure prediction model based on the sand body porosity; establish a formation pressure and residual surrounding rock pressure prediction model based on the hydrostatic pressure and the measured pressure coefficient of the well point.

[0065] Step 4: Establish a reservoir-forming index prediction model to obtain quantitative evaluation parameters of deep tight clastic reservoirs based on the reservoir-forming index and realize the prediction of the “sweet spot” of deep tight reservoirs.

[0066] In step 1, the three-dimensional spatial distribution of elastic parameters such as P- and S-wave velocity, density, and Poisson's ratio is obtained through pre-stack seismic elastic parameter inversion.

[0067] In step 2, a porosity prediction model is established based on rock physics analysis and using drilling and logging data.

[0068] In step 3, an equivalent hydrocarbon expulsion pressure prediction model is established based on the sand body porosity; a formation pressure and residual surrounding rock pressure prediction model is established based on the hydrostatic pressure and the measured pressure coefficient of the well point:

[0069] During the sediment deposition and compaction process, the mechanical relationship between the residual surrounding rock pressure (Ps) and the change in porosity and the formation of abnormal pore pressure conforms to the effective stress formula:

[0070] P s =P f -P ov

[0071] Where: Pf is the pore fluid pressure (Mpa), Pov is the overlying formation pressure (Mpa).

[0072] (1) Overlying formation pressure

[0073] Overburden pressure refers to the pressure formed by the weight of the overburden rock skeleton and the fluid in the pore space. That is:

[0074] P ov =H[(l-φ)ρ ma +φρ f ] or P ov =ρ av gh

[0075] Where: Pov represents the overburden pressure (MPa), which increases with the depth H (m); φ represents the average porosity of the overburden, dimensionless; ρma is the average density of the overburden matrix (g / cm3); ρf is the average density of the pore fluid in the overburden (g / cm3). ρma is the average density of the overburden (g / cm3).

[0076] (2) Pore fluid pressure

[0077] Pore ​​fluid pressure P f The calculation formula is as follows:

[0078] P f =P p +P g =Pp +(P ov -P h )

[0079] Where: Pf is the pore fluid pressure (Mpa), Pov is the overlying formation pressure (Mpa), Pp is the formation pressure (Mpa); Pg is the particle support pressure, also known as the rock skeleton pressure (Mpa); Ph represents the hydrostatic pressure (Mpa).

[0080] The residual surrounding rock pressure (Ps) can be rewritten as:

[0081] P s =P f -Po v =P p +(P ov -P h )-P ov =P p -P h

[0082] The formation pressure (Pp) can be calculated by the measured pressure coefficient (αp) and the hydrostatic pressure (Ph) at the well point. The pressure coefficient (αp) is the ratio of the actual formation pressure to the hydrostatic pressure, which reflects the degree of deviation of the formation pressure value at a certain point in the formation from the normal formation pressure value. It is dimensionless:

[0083]

[0084] Where: Ph represents hydrostatic pressure (MPa); Pp represents formation pressure (MPa). The value of hydrostatic pressure is related to the density of the fluid and the height of the fluid column, but has nothing to do with the size, shape and distribution range of the fluid. The calculation formula is as follows:

[0085] P h =10 -3 ρ w gh

[0086] Where: ρw represents the average density of formation water (g / cm3), h represents the vertical height of the water column (m), and g is the acceleration due to gravity (m / s2). Hydrostatic pressure usually increases with depth, and its rate of change is only related to density. Density is often related to its salinity, temperature, and dissolved gas content. It is generally believed that the density of pure water is (1.0g / cm3) and the density of salt water is (1.04g / cm3).

[0087] (3) Equivalent hydrocarbon expulsion pressure

[0088] The equivalent hydrocarbon expulsion pressure is often closely related to the porosity. e ) and porosity:

[0089]

[0090] In the formula, is the porosity of the sand body, p e is the equivalent hydrocarbon discharge pressure (MaP), a and b are empirical coefficients.

[0091] In step 4, a reservoir formation index prediction model is established to obtain quantitative evaluation parameters of deep tight clastic reservoirs based on the reservoir formation index, thereby realizing the prediction of the “sweet spot” of deep tight reservoirs.

[0092] Through the analysis of pore fluid pressure, equivalent hydrocarbon expulsion pressure and residual surrounding rock pressure, a prediction model for the accumulation index of tight reservoirs is established.

[0093] The calculation formula of reservoir formation index is:

[0094] I d =P s / P e

[0095] Where: Id is the reservoir-forming index of the sand body, a dimensionless quantity. The larger its value is, the more conducive it is to the formation of lithologic oil and gas reservoirs in the sand body, and vice versa; Ps is the residual surrounding rock pressure (Mpa), and Pe is the equivalent hydrocarbon expulsion pressure (Mpa).

[0096] The formation of lithologic oil and gas reservoirs is the result of the combined effect of reservoir-forming dynamics (i.e., residual surrounding rock pressure) and reservoir-forming resistance. Accumulation is possible only when the former is greater than the latter. Therefore, there is a need for parameters that comprehensively reflect the combined effect of the two. According to reservoir-forming dynamics analysis: the greater the residual surrounding rock pressure that reflects reservoir-forming dynamics, the stronger the ability of oil and gas to enter lithologic traps; under the same reservoir-forming dynamics conditions, the smaller the equivalent hydrocarbon expulsion pressure that reflects reservoir-forming resistance, the greater the possibility of oil and gas entering lithologic traps, and vice versa, the smaller the possibility of reservoir formation.

[0097] The method for quantitatively predicting the accumulation index of tight reservoirs based on three-dimensional prestack seismic inversion of the present invention analyzes formation pressure, residual surrounding rock pressure and effective hydrocarbon expulsion pressure through hydrostatic pressure, well point measured pressure coefficient and sand body porosity, and establishes an accumulation index prediction model suitable for tight reservoirs in the study area, thereby achieving quantitative evaluation of the "sweet spots" of deep tight clastic reservoirs, forming a "sweet spot" prediction technology suitable for the exploration and development of deep tight reservoirs, implementing favorable zones and "sweet spot" targets, and providing a basis for the exploration and development of tight reservoirs. The method has good application effects and promotion prospects.

[0098] Embodiment 1:

[0099] In a specific embodiment 1 of the present invention, the method for quantitatively predicting the accumulation index of a tight reservoir based on three-dimensional prestack seismic inversion of the present invention includes the following steps:

[0100] Step 1: For the target layer of Qigu Formation in Yong1-3 well area, based on prestack seismic elastic inversion, obtain the three-dimensional spatial distribution of elastic parameters such as P-wave velocity, S-wave velocity, density, Poisson's ratio, etc., where: Figure 2 This is the well-to-well section of the Qigu Formation P-wave velocity in the Yong1-3 well area. Figure 3 This is the shear wave velocity well-to-well section of the Qigu Formation in the Yong1-3 well area; Figure 4 This is the density well connection profile of the Qigu Formation in the Yong1-3 well area.

[0101] Step 2: Based on rock physics analysis, use drilling and logging data to establish a porosity prediction model. Through rock physics analysis of well points in Yongjin area, the following porosity prediction model is established:

[0102]

[0103] In the formula, is the porosity of the sand body (%), ρ is the density (g / cm3), VP and VS are the longitudinal wave velocity and shear wave velocity (m / s), respectively.

[0104] The porosity prediction model mentioned above is used to calculate the porosity three-dimensional data volume of the target layer of the Qigu Formation in the Yong1-3 well area, where: Figure 5 This is the well-connected porosity section of the Qigu Formation in the Yong1-3 well area; Figure 6 This is the plane distribution map of the porosity of the main sand body of the Qigu Formation in the Yong1-3 well area.

[0105] Step 3: Establish an equivalent hydrocarbon expulsion pressure prediction model based on sand body porosity; establish a formation pressure and residual surrounding rock pressure prediction model based on hydrostatic pressure and well point measured pressure coefficient. Table 1 shows the well point pressure coefficients of 15 wells in the Yongjin area in the Qigu Formation. The equivalent hydrocarbon expulsion pressure in this area is often closely related to porosity ( Figure 7 ), and based on the measured data in the surrounding areas, the equivalent hydrocarbon expulsion pressure prediction model is established as follows:

[0106]

[0107] Where: Pe is the equivalent hydrocarbon expulsion pressure (MaP), is the porosity of the sand body (%).

[0108] Table 1

[0109]

[0110]

[0111] Step 4: Establish a reservoir-forming index prediction model to obtain quantitative evaluation parameters of deep tight clastic reservoirs based on the reservoir-forming index, where: Figure 8This is the well-connected section of the Qigu formation reservoir index in the Yong1-3 well area; Fig. 9 This is the plane distribution map of the main sand body reservoir index of the Qigu Formation in the Yong1-3 well area. Fig.10 The histogram of reservoir identification of the main sand body accumulation index of the Qigu Formation in Yongjin area is shown in Figure 1. Fig.10 It can be seen that the accumulation index values ​​corresponding to most oil layers are large (accumulation index>13.7), while the accumulation index values ​​corresponding to dry layers and water layers are small (accumulation index<13.7). This shows that the larger the accumulation index value, the better the reservoir properties, and vice versa. It can be used as a quantitative evaluation standard for the prediction of sweet spots in tight reservoirs.

[0112] Embodiment 2:

[0113] In a specific embodiment 2 of the present invention, the method for quantitatively predicting the accumulation index of a tight reservoir based on three-dimensional prestack seismic inversion of the present invention includes the following steps:

[0114] Step 1: For the target layer of Qigu Formation in Yong3 well area, based on prestack seismic elastic inversion, obtain the three-dimensional spatial distribution of elastic parameters such as P-wave velocity, S-wave velocity, density, Poisson's ratio, etc., where: Fig.11 This is the well-to-well section of the Qigu Formation P-wave velocity in the Yong3 well area. Fig.12 This is the shear wave velocity well section of Qigu Formation in Yong3 well area; Fig.13 This is the density well-connected profile of the Qigu Formation in the Yong3 well area.

[0115] Step 2: Based on rock physics analysis, use drilling and logging data to establish a porosity prediction model. Through rock physics analysis of well points in Yongjin area, the following porosity prediction model is established:

[0116]

[0117] In the formula, is the porosity of the sand body (%), ρ is the density (g / cm3), VP and VS are the longitudinal wave velocity and shear wave velocity (m / s), respectively.

[0118] The porosity prediction model mentioned above is used to calculate the porosity three-dimensional data volume of the target layer of the Qigu Formation in the Yong3 well area, where: Fig.14 This is the well-connected porosity section of the Qigu Formation in the Yong3 well area; Fig.15 This is the plane distribution map of the porosity of the main sand body of the Qigu Formation in the Yong3 well area.

[0119] Step 3: Establish an equivalent hydrocarbon expulsion pressure prediction model based on sand body porosity; establish a formation pressure and residual surrounding rock pressure prediction model based on hydrostatic pressure and well point measured pressure coefficient. Table 1 shows the well point pressure coefficients of 15 wells in the Yongjin area in the Qigu Formation. The equivalent hydrocarbon expulsion pressure in this area is often closely related to porosity, such as Figure 7As shown in the figure, the equivalent hydrocarbon expulsion pressure prediction model is established based on the measured data in the surrounding areas as follows:

[0120]

[0121] Where: Pe is the equivalent hydrocarbon expulsion pressure MaP, is the porosity of the sand body.

[0122] Step 4: Establish a reservoir-forming index prediction model to obtain quantitative evaluation parameters of deep tight clastic reservoirs based on the reservoir-forming index, where: Fig.16 This is the well-connected section of the Qigu formation reservoir index in the Yong3 well area; Fig.17 This is the plane distribution map of the main sand body reservoir index of the Qigu Formation in the Yong3 well area. Fig.10 The histogram of reservoir identification of the main sand body accumulation index of the Qigu Formation in Yongjin area is shown in Figure 1. Fig.10 It can be seen that the accumulation index values ​​corresponding to most oil layers are large (accumulation index>13.7), while the accumulation index values ​​corresponding to dry layers and water layers are small (accumulation index<13.7). This shows that the larger the accumulation index value, the better the reservoir properties, and vice versa. It can be used as a quantitative evaluation standard for the prediction of sweet spots in tight reservoirs.

[0123] Beneficial effects: The present invention studies a quantitative prediction method for tight reservoir formation index based on three-dimensional prestack seismic inversion, establishes an equivalent hydrocarbon expulsion pressure prediction model based on sand body porosity; establishes formation pressure and residual surrounding rock pressure prediction models based on hydrostatic pressure and well point measured pressure coefficient; establishes a formation index prediction model suitable for tight reservoirs in the study area, realizes quantitative evaluation of the "sweet spots" of deep tight clastic reservoirs, forms a "sweet spot" prediction technology suitable for the exploration and development of deep tight reservoirs, implements favorable zones and "sweet spot" targets, and provides a basis for the exploration and development of tight reservoirs.

[0124] The above specific implementation methods further illustrate the objectives, technical solutions and beneficial effects of the present invention in detail. It should be understood that the above are only specific implementation methods of the present invention and are not intended to limit the scope of protection of the present invention. Any modifications, equivalent substitutions, improvements, etc. made within the spirit and principles of the present invention should be included in the scope of protection of the present invention.

Claims

1. A method for predicting tight reservoir accumulation index, characterized in that: The prediction method comprises: Step 1: Perform pre-stack seismic elastic parameter inversion to obtain the three-dimensional spatial distribution of multiple elastic parameters; Step 2: Establish a porosity prediction model based on rock physics analysis; Step 3: Establish an equivalent hydrocarbon expulsion pressure prediction model based on the sand body porosity; establish a formation pressure and residual surrounding rock pressure prediction model based on the hydrostatic pressure and the well point measured pressure coefficient; Step 4: Establish a reservoir-forming index prediction model, obtain quantitative evaluation parameters of deep tight clastic reservoirs based on the reservoir-forming index, and predict deep tight reservoirs.

2. A method for predicting tight reservoir accumulation index according to claim 1, characterized in that: The multiple elastic parameters include: longitudinal and transverse wave velocities, density, and Poisson's ratio.

3. A method for predicting tight reservoir accumulation index according to claim 1, characterized in that: The step 2: establishing a porosity prediction model based on rock physics analysis specifically includes: Based on rock physics analysis, a porosity prediction model is established using drilling and logging data.

4. A method for predicting tight reservoir accumulation index according to claim 1, characterized in that: The step 3, establishing an equivalent hydrocarbon expulsion pressure prediction model based on sand body porosity; establishing a formation pressure and residual surrounding rock pressure prediction model based on hydrostatic pressure and well point measured pressure coefficient, specifically includes: During the sediment deposition and compaction process, the mechanical relationship between the residual surrounding rock pressure Ps and the change of porosity and the formation of abnormal pore pressure conforms to the effective stress formula: P s =P f -P ov Where: Pf is the pore fluid pressure (Mpa), Pov is the overlying formation pressure (Mpa).

5. A method for predicting tight reservoir accumulation index according to claim 4, characterized in that: The overlying formation pressure refers to the pressure formed by the weight of the overlying rock skeleton and the fluid in the pore space; P ov =H[(1-φ)ρ ma +fr f ] orP ov =ρ av gh Among them, P ov is the overlying formation pressure, MPa, which increases with the depth H; φ represents the average porosity of the overlying rock formation, dimensionless; ρ ma is the average density of the overlying rock matrix g / cm3; ρ f is the average density of the pore fluid in the overlying rock layer g / cm3; ρ ma It is the average density of the overlying strata, g / cm3.

6. A method for predicting tight reservoir accumulation index according to claim 4, characterized in that: The pore fluid pressure P f The calculation formula is as follows: P f =P p +P g =P p +(P ov -P h ) Among them, P f is the pore fluid pressure MPa, P ov is the overlying formation pressure MPa, P p is the formation pressure MPa; Pg is the particle support pressure, also known as the rock skeleton pressure MPa; P h Represents the hydrostatic pressure in MPa.

7. A method for predicting tight reservoir accumulation index according to claim 4, characterized in that: The residual surrounding rock pressure Ps is rewritten as: P s =P f -P ov =P p +(P ov -P h )-P ov =P p -P h The formation pressure Pp is measured by the well point pressure coefficient α p Calculated with the hydrostatic pressure Ph, where the pressure coefficient α p It is the ratio of actual formation pressure to hydrostatic pressure, reflecting the degree of deviation of the formation pressure value at a certain point in the formation from the normal formation pressure value, dimensionless: Among them, Ph represents the hydrostatic pressure in MPa; Pp represents the formation pressure in MPa.

8. A method for predicting tight reservoir accumulation index according to claim 4, characterized in that: The value of the hydrostatic pressure is related to the density of the fluid and the height of the fluid column, and has nothing to do with the size, shape and distribution range of the fluid. The calculation formula is as follows: P h =10 -3 ρ w gh Among them, ρ w represents the average density of formation water g / cm3, h represents the vertical height of the water column m, and g is the acceleration of gravity m / s 2 ; Hydrostatic pressure generally increases with depth, with the rate of change being related only to density; Density is often related to its salinity, temperature and dissolved gas content. The density of pure water is 1.0g / cm3, and the density of salt water is 1.04g / cm3.

9. A method for predicting tight reservoir accumulation index according to claim 4, characterized in that: The equivalent hydrocarbon expulsion pressure is closely related to the porosity. e Empirical relationship with porosity: in, is the porosity of the sand body, p e is the equivalent hydrocarbon discharge pressure MaP, a and b are empirical coefficients.

10. A method for predicting tight reservoir accumulation index according to claim 1, characterized in that: The step 4 is to establish a reservoir formation index prediction model to obtain quantitative evaluation parameters of deep tight clastic reservoirs based on the reservoir formation index. The prediction of deep tight reservoirs specifically includes: Through the analysis of pore fluid pressure, equivalent hydrocarbon expulsion pressure and residual surrounding rock pressure, a prediction model for the accumulation index of tight reservoirs is established; The calculation formula of reservoir index is: I d =P s / P e Among them, I d It is the reservoir-forming index of the sand body, a dimensionless quantity. The larger its value is, the more conducive it is for the sand body to form lithologic oil and gas reservoirs, and vice versa. Ps is the residual surrounding rock pressure in MPa, and Pe is the equivalent hydrocarbon expulsion pressure in MPa.

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