CN112016753A - Metamorphic rock buried hill productivity prediction method based on ternary coupling - Google Patents
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Abstract
The invention discloses a metamorphic rock buried hill productivity prediction method based on ternary coupling, which comprises the steps of firstly, establishing a lithology characterization coefficient calculation model based on the morphological change of dark mineral content difference in neutron and density curves; secondly, normalizing the amplitude difference of the deep and shallow resistivities and the midpoint response value, and establishing a crack characterization index calculation method; thirdly, establishing a gas logging total hydrocarbon value correction method, and establishing a metamorphic rock buried hill oil-gas response coefficient by using the amplitude and form change of the corrected gas logging total hydrocarbon value; and finally, applying the calculation result and the method to the coupling coefficient calculation, and establishing a productivity prediction equation by utilizing the coupling coefficient and the divided effective thickness of the reservoir and combining the actual test result of the drilled well of the metamorphic rock buried hill. The invention provides a metamorphic rock buried hill productivity prediction method, which improves the productivity prediction precision, realizes quantitative evaluation of metamorphic rock buried hill productivity and has important guiding significance for logging evaluation of similar reservoirs.
Description
Technical Field
The invention belongs to the field of metamorphic rock buried hill evaluation and the field of rock physical parameters, and particularly relates to a metamorphic rock buried hill productivity prediction method based on lithology, cracks and oil gas filling capacity coupling.
Background
In recent years, with the breakthrough of deep submerged mountains in the Bohai sea, the key target layer of Bohai sea research moves downwards, and more exploration wells reveal fractured submerged mountainous reservoirs. But in exploration evaluation, mismatching exists between actually tested oil and gas well productivity and the conditions of porosity, crack development and the like. When the porosity is larger, the actual test effect is poorer; when the porosity is small, the actual test productivity is high, which brings great doubt to geological and well logging researchers.
The reservoir productivity prediction technology has important guiding significance for evaluating the exploration effect of the oil-gas field and developing well deployment. At present, the productivity prediction technology at home and abroad mainly aims at reservoir types such as sandstone, conglomerate, compact bed, carbonate rock and the like and estimates according to logging data. The commonly used productivity prediction method is mainly based on conventional well logging, nuclear magnetic resonance well logging, imaging well logging and other methods.
The productivity prediction method based on conventional logging information mainly aims at shallow sandstone reservoirs, has simple pore structures, and performs productivity prediction by integrating parameters such as porosity, permeability, saturation, reservoir thickness and the like. Metamorphic rock buried hill lithology is complex, reservoir heterogeneity is strong, reservoir space is mainly seam and hole, determination difficulty of reservoir permeability and saturation parameters is high, and large errors are brought by only depending on conventional well logging to predict productivity.
The capacity prediction method based on nuclear magnetic resonance logging is mainly used for combining the capillary pressure curve form of a laboratory and the oil testing capacity of a reservoir with a complex pore structure, and establishes an intuitive classification standard of the natural capacity grade of the reservoir based on the capillary pressure curve form. On the basis of visual classification, the laboratory pore structure parameters and the test oil production result are combined, the effective porosity, the permeability, the displacement pressure, the pore throat average value, the sorting coefficient and the maximum mercury inlet saturation are preferably selected as reservoir classification standards, and a reservoir classification comprehensive evaluation index curve is constructed.
In the formula:
ZZ is a reservoir classification comprehensive evaluation index and is dimensionless;
K is nuclear magnetic resonance logging calculated permeability, mD;
Spcalculating the sorting coefficient based on the nuclear magnetic resonance logging without dimension;
Smaxcalculating the maximum mercury intrusion saturation,%, for a nuclear magnetic resonance log;
DMcalculating the mean pore throat radius based on nuclear magnetic resonance logging without dimension;
Pdthe displacement pressure value, MPa, was calculated based on nuclear magnetic resonance logging.
And determining the output capacities of different reservoirs based on the reservoir classification comprehensive evaluation indexes, as shown in the table 1. In metamorphic rock buried mountains, the influence of factors such as the mineralization degree of drilling fluid, well temperature and the like is caused, the influence of a nuclear magnetic resonance logging environment is large, the logging quality is poor, and the productivity prediction requirement is difficult to meet.
TABLE 1 reservoir Classification evaluation criteria Table
The productivity prediction method based on imaging logging information mainly aims at carbonate reservoirs, cracks are picked up quantitatively through imaging logging, and productivity prediction is carried out through establishing the relation between parameters such as crack density and crack porosity and productivity. Because the cracks are picked up manually, the picking-up states and the picking-up quantity of different interpreters are different, and the time of the crack picking-up process is long, the method has poor popularization and great uncertainty of the capacity prediction result.
Disclosure of Invention
In order to solve the problem of insufficient production energy prediction in metamorphic rock buried hill in the prior art, the invention provides a metamorphic rock buried hill productivity prediction method based on lithology, crack and oil gas filling capacity coupling by combining conventional logging information, test information, logging information, imaging logging information and other information, thereby greatly improving the metamorphic rock buried hill productivity prediction precision and laying a foundation for subsequent metamorphic rock buried hill exploration evaluation and development well deployment.
The technical scheme of the invention is operated according to the following steps:
acquiring density and neutron logging values, and calculating lithology characterization coefficients;
step (2) calculating a fracture characterization index according to resistivity logging;
calculating an oil gas response coefficient according to the gas logging and the specific gravity of the drilling fluid;
and (4) establishing a productivity prediction model and predicting the productivity.
The calculation method in the step (1), the step (2), the step (3) and the step (4) mainly comprises the following steps:
step (1): determination of metamorphic rock buried hill lithology characteristic coefficient Lith
For metamorphic rock buried hill, due to the difference of the actions of original rock, magma hydrothermal solution, structure movement and the like, lithology is complex, and logging response characteristics are disordered. The metamorphic rock mineral component is mainly three light-color minerals and one or two dark-color minerals; the light-colored minerals mainly comprise quartz, alkaline feldspar and plagioclase, and the dark-colored minerals mainly comprise biotite, amphibole and pyroxene. When the content of light-colored minerals in the mineral components of the rock is high, the rock is good in brittleness, and cracks and joint seams are easy to generate under the action of structural stress; when the dark color mineral content in the rock mineral component is high, the rock toughness is strong, and cracks are not easy to generate. As the neutron and density logging response characteristic values of the light-color minerals and the dark-color minerals are greatly different, the neutron and density curves can be used for representing the difference of the metamorphic rock buried hill mineral components.
In the formula:
the Lith is a normalized lithology characterization coefficient and is dimensionless;
rho is the measured density value of the well logging in g/cm3；
ρmaxMaximum of the Density log response, g/cm3；
ρminIs the minimum value of the density log response, g/cm3；
Step (2): metamorphic rock buried hill crack characterization index KfDetermining
The metamorphic rock buried hill storage space is mainly a seam and a hole (a hole), and the configuration relationship between the seam and the hole directly influences the effectiveness of a buried hill oil-gas layer, thereby playing a decisive role in contributing to productivity. According to the past experience, the friction coefficient of the fracture and the production capacity have a good exponential relationship, but the fracture pickup is influenced by factors such as interpreters and logging quality, and the uncertainty is large. According to the water tank model experiment, the fracture occurrence and the double-lateral logging have a better correlation relationship, so that the fracture characterization index is established based on the amplitude difference of the deep resistivity and the shallow resistivity and the midpoint response value, and the metamorphic rock buried hill fracture development characteristics can be effectively judged.
In the formula:
Kfis a normalized fracture characterization index, dimensionless;
Kf1the amplitude difference of the deep and shallow resistivity is dimensionless;
Kf1MAXthe amplitude difference value of the deep and shallow resistivities is maximum, and no dimension exists;
Kf2the response values of the middle points of the deep resistivity and the shallow resistivity are dimensionless;
Kf2MAXthe medium resistivity is the maximum value of the midpoint response value of the deep resistivity and the shallow resistivity, and is dimensionless;
RDdeep resistivity, Ω · m;
RSshallow resistivity, Ω · m;
Rmaxmaximum value for resistivity log, Ω · m;
Rminis the minimum value of the resistivity log, Ω · m.
And (3): determination of metamorphic rock buried hill oil Gas response coefficient Gas
The change of the gas logging amplitude value and the form is the direct embodiment of the metamorphic rock buried hill oil and gas migration response, but the gas logging value is influenced by the specific gravity of the drilling fluid and the likeThe factor influences greatly. According to statistics of drilling fluid specific gravity of drilled metamorphic rock buried hill in Bohai sea, gas logging and other data, when the drilling fluid specific gravity is less than or equal to 1.11g/cm3In time, the gas logging total hydrocarbon value is obviously increased by the decrease of the specific gravity of the well drilling fluid, so the gas logging value needs to be corrected.
TG＝TGAS+10-7.6884*mw+8.2825 (6)
On the basis, the amplitude value and the form change of the gas logging are integrated, and the metamorphic rock buried hill oil-gas response coefficient is established as follows:
in the formula:
gas is a normalized oil-Gas response coefficient and is dimensionless;
TG is corrected gas log total hydrocarbon value,%;
TGAS is the total hydrocarbon value,%, measured by gas logging;
mw is the specific gravity of drilling fluid, g/cm3；
TGbaseIs the corrected gas logging total hydrocarbon substrate value,%;
TGmaxis the maximum value of the corrected gas logging total hydrocarbon value,%;
TGminis the minimum value of the corrected gas logging total hydrocarbon value percent.
And (4): metamorphic rock buried hill productivity prediction model determination
Based on conventional well logging, imaging well logging, array sound wave and production well logging, and in combination with formation testing, well drilling coring, assay analysis and other data, the effective thickness lower limit standard meeting the regional rule can be finally established, namely the total porosity is more than or equal to 2%, the longitudinal wave time difference is more than or equal to 53us/ft, and the deep resistivity is less than or equal to 510 omega.m. According to the standard, the effective reservoir thickness H of the reservoir can be accurately identified.
Secondly, the yield of the metamorphic rock buried hill test depends on multiple factors such as the strength of oil gas filling, the development condition of cracks, lithology characteristics and the like. On the basis of comprehensive lithology, cracks and oil gas filling capacity, the difficulty of quantitative evaluation of liquid production capacity can be realized.
Based on the ternary coupling coefficient, determining a productivity prediction model as follows by establishing an objective function:
Q＝0.0268*(F*H)2.6326(R2＝0.9544) (9)
in the formula:
q is the predicted yield value, 104m3/d；
F is a ternary coupling coefficient and is dimensionless;
h is well logging interpretation reservoir thickness, m;
r is a correlation coefficient and is dimensionless.
The invention has the following effective effects: the invention provides a productivity prediction calculation method for an untested layer section of metamorphic rock buried hill. Based on the neutron and density curve morphological characteristics, a lithology characterization coefficient is established for judging the metamorphic rock buried hill brittleness characteristics and indicating crack development and storage; establishing a fracture characterization index based on the separation degree and the midpoint position characteristics of the dual laterolog, and judging the development degree and the permeability of the reservoir fracture; on the basis of considering the influence of the specific gravity of the drilling fluid on gas measurement, correcting the total hydrocarbon value of the gas measurement, integrating the amplitude and the base value change, and establishing an oil-gas response coefficient for representing the oil-gas filling response characteristic; on the basis of the research, the lithology, the crack and the oil gas filling are subjected to ternary coupling, and the correlation between the coupling coefficient and the productivity is established to predict the productivity change of the metamorphic rock buried hill reservoir. The prediction result of the method is well matched with the actual well test result, and the method has important guiding significance for subsequent metamorphic rock buried hill exploration evaluation, development and deployment.
Drawings
FIG. 1 is a flowchart of a metamorphic rock buried hill productivity prediction technique according to an embodiment of the present invention;
FIG. 2a is a graph showing the relationship between the neutron and density curves of the mixed granite and the contents of Fe and Mg elements according to the embodiment of the present invention;
FIG. 2b is a graph showing the relationship between neutron and density curves of schistose and the content of iron and magnesium elements provided by the embodiment of the present invention;
FIG. 2c is a graph showing the relationship between neutron and density curves of the angle-blende rock and the contents of iron and magnesium elements, according to an embodiment of the present invention;
FIG. 3a is a graph of the deep and shallow resistivity ratios versus fracture density provided by an embodiment of the present invention;
FIG. 3b is a graph of deep and shallow resistivity ratios versus fracture porosity provided by an embodiment of the present invention;
FIG. 4 is a comparison of a W-well resistivity log and a production profile provided by an embodiment of the present invention;
FIG. 5 is an X-well log provided by an embodiment of the present invention;
FIG. 6 is a Y-well test high-production section gas log provided by an embodiment of the present invention;
FIG. 7 is a Z-well test low-yield segment gas log provided by an embodiment of the invention;
FIG. 8 is a plot of X well gas log correction and hydrocarbon response coefficients provided by an embodiment of the present invention;
FIG. 9 is a W-well coupling coefficient achievement diagram provided by an embodiment of the present invention;
FIG. 10 is a condensate layer productivity prediction diagram according to an embodiment of the present invention;
FIG. 11 is a graph of N well productivity predictions provided by embodiments of the present invention.
Detailed Description
The invention provides a metamorphic rock buried hill productivity prediction method based on ternary coupling, which is described in detail below by combining embodiments and accompanying drawings.
As shown in the flow of FIG. 1, the metamorphic rock buried hill productivity prediction method based on ternary coupling is operated according to the following steps:
acquiring density and neutron logging values, and calculating lithology characterization coefficients;
step (2) calculating a fracture characterization index according to resistivity logging;
calculating an oil gas response coefficient according to the gas logging and the specific gravity of the drilling fluid;
and (4) establishing a productivity prediction model and predicting the productivity.
The calculation method in the step (1), the step (2), the step (3) and the step (4) mainly comprises the following steps:
step (1): determination of metamorphic rock buried hill lithology characteristic coefficient Lith
For metamorphic rock buried hill, due to the difference of the actions of original rock, magma hydrothermal solution, structure movement and the like, lithology is complex, and logging response characteristics are disordered. The metamorphic rock mineral component is mainly three light-color minerals and one or two dark-color minerals; the light-colored minerals mainly comprise quartz, alkaline feldspar and plagioclase, and the dark-colored minerals mainly comprise biotite, amphibole and pyroxene. When the content of light-colored minerals in the mineral components of the rock is high, the rock is good in brittleness, and cracks and joint seams are easy to generate under the action of structural stress; when the dark color mineral content in the rock mineral component is high, the rock toughness is strong, and cracks are not easy to generate. As shown in fig. 2, the specific gravity of Fe and Mg elements is small, which indicates that the content of dark minerals is low, and neutron and density curves are characterized by "positive difference"; as the proportion of Fe and Mg elements is increased, the content of dark minerals is increased, and neutron and density curves are characterized by negative difference. Therefore, the neutron and density curves are used for representing the difference of the mineral components of the metamorphic rock buried hill.
In the formula:
the Lith is a normalized lithology characterization coefficient and is dimensionless;
rho is the measured density value of the well logging in g/cm3；
ρmaxMaximum of the Density log response, g/cm3；
ρminIs the minimum value of the density log response, g/cm3；
Through the calculation of the formula (1), when the content of the metamorphic rock buried hill dark color mineral is less and the neutron and density curve is in a positive difference, the value of the lithological characterization coefficient Lith is greater than 0.5; when the content of dark minerals is high and the neutron and density curves are in negative difference, the value of the lithology characterization coefficient Lith calculated is less than 0.5.
Step (2): metamorphic rock buried hill crack characterization index KfDetermining
The metamorphic rock buried hill storage space is mainly a seam and a hole (a hole), and the configuration relationship between the seam and the hole directly influences the effectiveness of a buried hill oil-gas layer, thereby playing a decisive role in contributing to productivity. According to the past experience, the friction coefficient of the fracture and the production capacity have a good exponential relationship, but the fracture pickup is influenced by factors such as interpreters and logging quality, and the uncertainty is large. According to the water tank model experiment, the fracture occurrence and the dual laterolog have a better correlation, and meanwhile, as shown in fig. 3, the fracture density and the fracture porosity of the reservoir development section and the ratio of the deep resistivity and the shallow resistivity have a better consistency. Therefore, the crack characterization index is established based on the amplitude difference of the deep and shallow resistivity and the midpoint response value, and the metamorphic rock buried hill crack development characteristics can be effectively judged.
In the formula:
Kfis a normalized fracture characterization index, dimensionless;
Kf1the amplitude difference of the deep and shallow resistivity is dimensionless;
Kf1MAXthe amplitude difference value of the deep and shallow resistivities is maximum, and no dimension exists;
Kf2the response values of the middle points of the deep resistivity and the shallow resistivity are dimensionless;
Kf2MAXthe medium resistivity is the maximum value of the midpoint response value of the deep resistivity and the shallow resistivity, and is dimensionless;
RDdeep resistivity, Ω · m;
RSshallow resistivity, Ω · m;
Rmaxmaximum value for resistivity log, Ω · m;
Rminis the minimum value of the resistivity log, Ω · m.
As shown in FIG. 4, the 4 th curve Kf1For the amplitude difference of the deep and shallow resistivities, curve 5Kf2The 6 th curve trace K is the midpoint response value of the deep and shallow resistivityfIndices were characterized for normalized fractures. Normalized fracture characterization index K in plot 6 tracefThe fracture fluid production profile logging method has the advantages of good coincidence relation with the contribution capacity of the output of each layer section determined by the 7 th fluid production profile logging, high output capacity and corresponding fracture characterization index KfThe value is large.
And (3): determination of metamorphic rock buried hill oil Gas response coefficient Gas
The gas logging information is the direct basis for finding oil and gas reservoirs in the exploration, development and evaluation process of oil and gas fields. The gas logging amplitude value and the morphological change are direct representations of metamorphic rock buried hill oil and gas migration response, but the gas logging is greatly influenced by factors such as the specific gravity of drilling fluid, gas logging matrix, drilling engineering and the like. As shown in fig. 5, mw of trace 2 is the drilling fluid density and TGAS is the gas log total hydrocarbon value; and the 5 th passages C1, C2 and C3 are hydrocarbon gas components of methane, ethane and propane respectively. The specific gravity of the well drilling fluid is reduced, and the total hydrocarbon value TGAS and the component methane C1, ethane C2 and propane C3 values are increased.
According to statistics of drilling fluid specific gravity of drilled metamorphic rock buried hill in Bohai sea, gas logging and other data, when the drilling fluid specific gravity is less than or equal to 1.11g/cm3In time, the gas logging total hydrocarbon value is obviously increased by the decrease of the specific gravity of the well drilling fluid, so the gas logging value needs to be corrected.
TG＝TGAS+10-7.6884*mw+8.2825 (6)
In the formula:
TG is corrected gas log total hydrocarbon value,%;
TGAS is the total hydrocarbon value,%, measured by gas logging;
mw is the specific gravity of drilling fluid, g/cm3。
Meanwhile, by combining data such as testing, logging and the like, a well with high testing productivity is tested, the fluctuation change of gas logging is large, the gas logging total hydrocarbon value of a reservoir section is high, and the components are complete, as shown in figure 6; the well with low test productivity has poor gas logging, or the fluctuation of the total hydrocarbon value and the components in the reservoir section and the compact section is small, as shown in figure 7. On the basis, the amplitude value and the form change of the gas logging are integrated, and the metamorphic rock buried hill oil-gas response coefficient is established as follows:
in the formula:
gas is a normalized oil-Gas response coefficient and is dimensionless;
TGbaseis the corrected gas logging total hydrocarbon substrate value,%;
TGmaxis the maximum value of the corrected gas logging total hydrocarbon value,%;
TGminis the minimum value of the corrected gas logging total hydrocarbon value percent.
The total hydrocarbon value of the gas logging is corrected by the formula (6), and the oil-gas response coefficient is calculated by the formula (7). As shown in FIG. 8, TG in lane 3 is the GAS survey total hydrocarbon correction and GAS in lane 4 is the normalized hydrocarbon response factor.
And (4): metamorphic rock buried hill productivity prediction model determination
The metamorphic rock buried hill is influenced by factors such as buried depth and parent rock components, the logging response characteristics are complex, the reservoir heterogeneity is strong, and effective reservoir division is difficult. According to the data of cable stratum testing, sampling, well drilling coring and the like, the lower limit standard of the effective thickness of the metamorphic rock buried hill reservoir is established by combining conventional well logging, imaging well logging, array sound wave and element well logging, namely the total porosity is more than or equal to 2 percent, the longitudinal wave time difference is more than or equal to 53us/ft, and the deep resistivity is less than or equal to 510 omega.m. According to the standard, the effective reservoir thickness H of the reservoir can be accurately identified.
Secondly, the yield of the metamorphic rock buried hill test depends on multiple factors such as the strength of oil gas filling, the development condition of cracks, lithology characteristics and the like. The metamorphic rock buried hill lithology characteristic coefficient Lith is higher, namely the lithologic dark mineral is less, the brittleness is stronger, and the crack development and the storage are facilitated; fracture characterization index KfThe higher, i.e. the better the fracture development, the better the reservoir permeability; the higher the Gas-oil response coefficient Gas is, the stronger the Gas filling capacity of the surface reservoir. The height of the metamorphic rock buried hill test productivity is in direct proportion to the strength of oil gas filling, the development condition of cracks and the lithology characteristics, and the quantitative evaluation problem of the liquid production capacity can be realized on the basis of integrating the lithology, the cracks and the oil gas filling capacity.
Calculating the lithology characterization coefficient Lith by using the step (1), and calculating the fracture characterization index K by using the step (2)fAnd (4) calculating an oil-Gas response coefficient Gas by using the step (3), and calculating a coupling coefficient F by using a formula (8). As shown in FIG. 9, F in the 9 th trace is the calculated coupling coefficient, and QZI in the 10 th trace is the production capacity of each section of the fluid production profile log. The consistency of the matching relationship between the coupling coefficient F calculated based on lithology, fracture and oil gas filling capacity and the contribution capacity QZI of each layer section output determined by the well logging of a liquid production profile is better, and the relationship between the W well output capacity and the capacity characterization parameter is shown in a table 2.
TABLE 2 relation table of production capacity and productivity characterization parameters of W well
Based on the ternary coupling coefficient, determining a condensate gas layer productivity prediction model as follows by establishing an objective function:
Q＝0.0268*(F*H)2.6326(R2＝0.9544) (9)
in the formula:
q is the predicted yield value, 104m3/d；
F is a ternary coupling coefficient and is dimensionless;
h is well logging interpretation reservoir thickness, m;
r is a correlation coefficient and is dimensionless.
By combining the coupling coefficient and the condensate gas layer non-resistance flow relation chart, as shown in fig. 10, the capacity prediction of the newly drilled well can be performed. Fig. 10 shows the result of the ternary coupling coefficient calculation in the 9 th curve, the result of the effective reservoir partitioning in the 10 th curve, the mean value of the coupling coefficients of the N-wells calculated by using the formula (8) is 0.0265, the effective thickness of the reservoir is 106.8m, and the non-resistance flow capacity of the condensate gas layer predicted by using the formula (9) is 0.41 × 104m3D, actual test productivity 1.1X 104m3D, unimpeded flow of 0.03X 104m3And d, the predicted result is matched with the actual test result.
Claims (5)
1. A metamorphic rock buried hill productivity prediction method based on ternary coupling is characterized by comprising the following steps:
acquiring density and neutron logging values, and calculating lithology characterization coefficients;
step (2) calculating a fracture characterization index according to resistivity logging;
calculating an oil gas response coefficient according to the gas logging and the specific gravity of the drilling fluid;
and (4) establishing a productivity prediction model.
And (5) for the new well of the metamorphic rock buried hill reservoir productivity to be predicted, calculating each characterization coefficient according to the steps (1), (2) and (3), and quantitatively predicting according to the prediction model (4).
2. The method for predicting the potential hilly capacity of the metamorphic rock based on the ternary coupling as claimed in claim 1, wherein the lithological character characterization coefficient Lith of the potential hilly of the metamorphic rock in the step (1) is determined as follows:
as the neutron and density logging response characteristic values of the light-color minerals and the dark-color minerals have large difference, the neutron and density curves can be used for representing the difference of the metamorphic rock buried hill mineral components:
in the formula:
the Lith is a normalized lithology characterization coefficient and is dimensionless;
rho is the measured density value of the well logging in g/cm3；
ρmaxMaximum of the Density log response, g/cm3；
ρminIs the minimum value of the density log response, g/cm3；
3. The method for predicting the potential hilly capacity of metamorphic rock based on ternary coupling as claimed in claim 1, wherein the characterization index K of the potential hilly crack of metamorphic rock in the step (2)fDetermining:
according to the water tank model experiment, the fracture occurrence and the double-lateral logging have a better correlation relationship, so that the fracture characterization index is established based on the amplitude difference of the deep and shallow resistivity and the midpoint response value, and the metamorphic rock buried hill fracture development characteristics can be effectively judged:
in the formula:
Kfis a normalized fracture characterization index, dimensionless;
Kf1the amplitude difference of the deep and shallow resistivity is dimensionless;
Kf1maxthe amplitude difference value of the deep and shallow resistivities is maximum, and no dimension exists;
Kf2the response values of the middle points of the deep resistivity and the shallow resistivity are dimensionless;
Kf2maxthe medium resistivity is the maximum value of the midpoint response value of the deep resistivity and the shallow resistivity, and is dimensionless;
RDdeep resistivity, Ω · m;
RSshallow resistivity, Ω · m;
Rmaxmaximum value for resistivity log, Ω · m;
Rminis the minimum value of the resistivity log, Ω · m.
4. The method for predicting the productivity of the metamorphic rock buried hill based on the ternary coupling as claimed in claim 1, wherein the step (3) of determining the oil-Gas response coefficient Gas of the metamorphic rock buried hill is as follows:
and correcting the gas logging value:
TG＝TGAS+10-7.6884*mw+8.2825 (5)
on the basis, the amplitude value and the form change of the gas logging are integrated, and the metamorphic rock buried hill oil-gas response coefficient is established as follows:
in the formula:
gas is a normalized oil-Gas response coefficient and is dimensionless;
TG is corrected gas log total hydrocarbon value,%;
TGAS is the total hydrocarbon value,%, measured by gas logging;
mw is the specific gravity of drilling fluid, g/cm3；
TGbaseIs the corrected gas logging total hydrocarbon substrate value,%;
TGmaxis the maximum value of the corrected gas logging total hydrocarbon value,%;
TGminis the minimum value of the corrected gas logging total hydrocarbon value percent.
5. The method for predicting the potential hill productivity of the metamorphic rock based on the ternary coupling as claimed in claim 1, wherein the step (4) of predicting the potential hill productivity of the metamorphic rock determines that:
the yield of the metamorphic rock buried hill test depends on various factors such as the strength of oil gas filling, the development condition of cracks, lithology characteristics and the like; on the basis of comprehensive lithology, cracks and oil gas filling capacity, the difficulty of quantitative evaluation of liquid production capacity can be realized;
based on the ternary coupling coefficient, determining a productivity prediction model as follows by establishing an objective function:
Q＝0.0268*(F*H)2.6326(R2＝0.9544) (8)
in the formula:
q is the predicted yield value, 104m3/d；
F is a ternary coupling coefficient and is dimensionless;
h is well logging interpretation reservoir thickness, m;
r is a correlation coefficient and is dimensionless.
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