CN119936359A - Classification, interpretation and evaluation method and system for fluid saturation of ultra-shallow undiagenetic reservoirs in offshore areas - Google Patents
Classification, interpretation and evaluation method and system for fluid saturation of ultra-shallow undiagenetic reservoirs in offshore areas Download PDFInfo
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Abstract
The invention belongs to the technical field of petroleum exploration and development, and relates to a method and a system for classifying, explaining and evaluating the fluid saturation of a reservoir with ultra-shallow non-diagenetic stratum in a sea area, wherein the method comprises the steps of obtaining a physical experiment result of an artificial rock core and logging curve data of a target reservoir, which accord with the characteristics of the target reservoir with ultra-shallow non-diagenetic stratum in the sea area; the method comprises the steps of classifying rock cores based on nuclear magnetic resonance distribution spectrums, calculating fluid indexes according to the porosities and the permeability of artificial rock cores, establishing rock core type classification standards based on the fluid indexes, reestablishing fitting relations between resistivity increase coefficients and water saturation of different types of rock cores, formation factors and porosity of a target layer based on rock core classification results to obtain rock electric parameters corresponding to different types of rock cores, determining the type of the target reservoir based on the rock core type classification standards, further determining the rock electric parameters of the target reservoir, and calculating the water saturation of the target reservoir according to the rock electric parameters of the target reservoir. The method can finely evaluate the fluid saturation of the ultra-shallow non-diagenetic reservoir in the sea area.
Description
Technical Field
The invention belongs to the technical field of oil and gas exploration and development, relates to reservoir fluid saturation classification interpretation and evaluation technology, and in particular relates to a reservoir fluid saturation classification interpretation and evaluation method and system for ultra-shallow non-diagenetic reservoirs in a sea area.
Background
In the field of oil and gas exploration and development, the interpretation and evaluation of fluid saturation is used as a key technology for quantitatively describing the filling degree of various fluids (such as water, oil and gas) in the rock pores of a reservoir, and is one of core parameters for predicting the productivity and the reserve of the reservoir. In a traditional fluid saturation calculation method, a petrophysical experiment is usually carried out by depending on a formed plunger core capable of bearing pressure, so that rock electric parameters are obtained, and a saturation interpretation model (such as an Alqi formula or deformation thereof) is constructed based on the rock electric parameters.
However, for the ultra-shallow gas reservoir in the sea, the rock is in an unconsolidated and unconsolidated state, the rock structure is loose, the coring operation is difficult, and the supporting rock physical experiment data support is lacked. Under the condition, the existing fluid saturation calculation method is used, the saturation precision is low, and accurate assessment of the shallow natural gas reserves in the sea area is severely restricted. In order to improve the calculation accuracy, the preparation of the artificial rock core matched with the characteristics of the target layer becomes an important way for obtaining the rock electric parameters of the target layer. Even so, there is still a real problem of insufficient calculation accuracy for the saturation evaluation of the ultra-shallow gas reservoir in the sea area.
At present, the fine evaluation of the fluid saturation mostly adopts a phase control idea, namely, the saturation is calculated according to different reservoir categories, so as to realize the fine evaluation. Common saturated fluid calculation methods include fluid unit index methods, graphic methods, machine learning methods and the like, and the methods are mainly applicable to low-pore low-permeability reservoirs (such as shale and tight sandstone oil and gas reservoirs), fracture-cavity carbonate reservoirs and volcanic reservoirs. For natural gas reservoirs with ultra shallow and unibody sea areas, fluid saturation evaluation is generally performed by substituting uniform rock electrical parameters into an alchi formula, or performing overall calculation by using a siemens formula considering the influence of the argillaceous additional conductivity (for example, the rock electrical parameters are generally set to a=b=1, and m=n=2). However, practical application shows that the Alqi formula can seriously underestimate the extremely high pore permeability gas saturation in a high-quality reservoir, and the Siemens formula considers the additional conductivity of the argillaceous, but fails to fully consider the influence of the ultra-shallow stratum water mineralization of the sea area on the macroscopic conductivity, so that the calculated gas saturation is higher than the practical value due to the superposition of the argillaceous additional conductivity in the calculation process. The problems directly lead to the fact that in the calculation of the fluid saturation of the ultra-shallow non-diagenetic natural gas reservoir in the sea area, the accuracy of the existing method is difficult to meet the requirements of actual exploration and development. Therefore, how to realize the refined evaluation of the saturation of the sea area ultra-shallow non-diagenetic natural gas-containing reservoir fluid becomes a key technical problem to be overcome currently.
Disclosure of Invention
Aiming at the problems existing in the prior art, the invention provides a classification, interpretation and evaluation method and a system for the fluid saturation of the ultra-shallow non-diagenetic reservoir in the sea area, which can realize the fine evaluation of the fluid saturation of the ultra-shallow non-diagenetic reservoir in the sea area.
The invention provides a sea area ultra-shallow non-diagenetic reservoir fluid saturation classification interpretation and evaluation method, which comprises the following steps:
The data acquisition step comprises the steps of acquiring a rock physical experiment result of an artificial rock core and logging curve data of a target reservoir, wherein the artificial rock core and the logging curve data of the target reservoir accord with the characteristics of the target reservoir of ultra-shallow non-diagenetic in a sea area, and the experiment result comprises nuclear magnetic resonance Distribution spectrum, porosity, permeability, water saturation, resistivity increase coefficient, formation factor;
classifying the core according to nuclear magnetic resonance Classifying the rock cores according to different intervals of distribution spectrum distribution;
Screening rock cores conforming to the same type according to the rock core classification result, calculating the fluid index of each rock core according to the porosity and permeability of each rock core, and establishing a rock core type classification standard according to the fluid index;
The rock electric parameter determining step, namely, establishing a fitting relation between the resistivity increase coefficient and the water saturation, between the formation factor and the porosity of the target layer for the rock cores of the same type, and obtaining the rock electric parameters corresponding to the rock cores of the same type according to the fitting relation;
A reservoir type determining step of calculating a target reservoir porosity according to target reservoir logging curve data, calculating a target reservoir permeability according to the target reservoir porosity, calculating a fluid index of the target reservoir according to the target reservoir porosity and the target reservoir permeability, and determining a target reservoir type based on a core type dividing standard according to the fluid index;
and the saturation calculating step is used for determining the rock electric parameters corresponding to the target reservoir according to the reservoir type of the target reservoir and calculating the water saturation of the target reservoir according to the rock electric parameters of the target reservoir.
In some embodiments, in the step of obtaining data, the method for obtaining the rock physical experiment result of the artificial rock core of the ultra-shallow non-diagenetic objective reservoir characteristic of the sea area comprises the following steps:
manufacturing an artificial rock core which accords with the characteristics of the reservoir stratum of the ultra-shallow non-diagenetic purpose of the sea area;
measuring the porosity and permeability of the artificial rock core under the set temperature condition;
Adopting brine with set mineralization degree to saturate the artificial rock core;
Placing the saturated artificial core into a nuclear magnetic resonance imaging system, setting echo interval time, waiting time, number of acquired echo strings and scanning times, and measuring magnetic resonance A distribution spectrum;
Under stratum conditions, core resistivity and water saturation under different water saturation conditions are measured through displacement experiments, and resistivity increase coefficients and stratum factors are calculated according to the core resistivity.
In some embodiments, the resistivity increase factor is calculated from the core resistivity by a resistivity increase factor calculation formula;
In the formula, The resistivity of the core is increased by a factor,In order to achieve the resistivity of the core after displacement,Is the core resistivity at saturation.
In some embodiments, the formation factor is calculated from the core resistivity by a formation factor calculation formula;
In the formula, As the formation factor of the core,Is the resistivity of the core when in saturation,Is the resistivity of the saturated solution.
In some embodiments, in the partitioning criteria constructing step, calculating a fluid index of the core from the porosity and permeability of the core by a fluid index calculation formula;
In the formula, As the fluid index of the core,For the permeability of the core,Is the porosity of the core.
In some embodiments, in the step of determining the electrical rock parameter, the fitted relationship of the resistivity increase coefficient to the water saturation is expressed as:
In the formula, The resistivity of the core is increased by a factor,Is a parameter of the lithology of the rock,The water saturation of the core,Is a saturation index;
Fitting relationship of formation factor to porosity:
In the formula, As the formation factor of the core,Is a parameter of the lithology of the rock,Is the porosity of the core, and the porosity of the core,Is a cementation index.
In some embodiments, in the reservoir type determining step, the method of calculating the target reservoir porosity from the target reservoir log data is:
calculating a natural gamma relative value;
In the formula, Is a natural gamma relative value; For the natural gamma logging value of the target layer, the unit is: an API; is the natural gamma logging value of the pure lithology stratum, and the unit is API; is the natural gamma logging value of clear clay rock stratum, unit is API;
calculating the shale content of the reservoir according to the natural gamma relative value;
In the formula, For the shale content of the reservoir,Is an empirical coefficient related to formation age;
Respectively calculating the density porosity after the shale correction and the neutron porosity after the shale correction according to the shale content of the reservoir;
In the formula, The unit is decimal for the density porosity after clay correction; the unit is decimal for neutron porosity after clay correction; The density value of the rock skeleton is given in g/cm 3; is the density value of the stratum fluid, and the unit is g/cm 3; The density value of the mudstone is given in g/cm 3; For the density logging value of the target layer, g/cm 3 is adopted; Neutron value of rock skeleton in%; Neutron value of formation fluid in percent; Neutron value of mudstone, unit is percent; the unit is percent of neutron logging value in the target layer; the unit is decimal for the clay content of the reservoir;
Calculating the porosity of the target reservoir according to the density porosity after the muddy correction and the neutron porosity after the muddy correction;
In the formula, Reservoir porosity for the purpose.
In some embodiments, in the reservoir type determining step, the method of calculating the target reservoir permeability from the target reservoir porosity is:
establishing a porosity-permeability fitting relation according to the porosity and permeability of the artificial rock core in the data acquisition step;
and calculating the permeability of the target reservoir according to the porosity of the target reservoir through the porosity-permeability fitting relation.
In some embodiments, in the saturation calculating step, the water saturation of the reservoir of interest is calculated by an alchi formula from the determined petroelectric parameter;
In the formula, For the purpose of water saturation of the reservoir,Is a parameter of the lithology of the rock,For the purposes of the cement index,In the sense of the saturation index,For the purpose of reservoir porosity,For the formation water resistivity to be high,Reservoir resistivity log values for the purpose.
The second aspect of the invention provides a classification, interpretation and evaluation system for the saturation of a fluid in an ultra-shallow non-diagenetic reservoir in a sea area, which is used for realizing the classification, interpretation and evaluation method for the saturation of the fluid in the ultra-shallow non-diagenetic reservoir in the sea area, and comprises the following steps:
The data acquisition module is used for acquiring the rock physical experiment result of the artificial rock core and the logging curve data of the target reservoir, which are in accordance with the characteristics of the target reservoir of the ultra-shallow non-diagenetic sea area;
Core classification module according to nuclear magnetic resonance Classifying the rock cores according to different intervals of distribution spectrum distribution;
the partition standard construction module is used for screening the rock cores conforming to the same type according to the rock core classification result, calculating the fluid index of each rock core according to the porosity and the permeability of each rock core, and establishing a rock core type partition standard according to the fluid index;
the rock electric parameter determining module is used for establishing a fitting relation between the resistivity increase coefficient and the water saturation, between the formation factor and the porosity of the target layer for the rock cores of the same type, and obtaining rock electric parameters corresponding to the rock cores of the same type according to the fitting relation;
The reservoir type determining module is used for calculating the porosity of the target reservoir according to the logging curve data of the target reservoir, calculating the permeability of the target reservoir according to the porosity of the target reservoir, calculating the fluid index of the target reservoir according to the porosity of the target reservoir and the permeability of the target reservoir, and determining the type of the target reservoir based on the core type dividing standard according to the fluid index;
and the saturation calculation module is used for determining the rock electric parameters corresponding to the target reservoir according to the reservoir type of the target reservoir and calculating the water saturation of the target reservoir according to the rock electric parameters of the target reservoir.
Compared with the prior art, the invention has the advantages and positive effects that:
the sea area ultra-shallow non-diagenetic reservoir fluid saturation classification interpretation and evaluation method and system provided by the invention are based on core experimental results, and core physical properties and rock electric parameter distribution rules of different pore structure types are searched according to nuclear magnetic resonance The method comprises the steps of classifying rock cores in different intervals of distribution spectrum distribution, calculating a fluid index according to a qualitative relation among porosity, permeability and fluid index, establishing a rock core type classification standard according to the fluid index, determining rock electric parameters of different types of the rock cores according to a fitting relation between a reestablished resistivity increase coefficient, water saturation, formation factors and porosity of a target layer, determining the type of the target reservoir based on the rock core type classification standard, further determining the rock electric parameters of the target reservoir, and calculating the fluid saturation of the target reservoir according to the rock electric parameters of the target reservoir. According to the method, on the basis that the rock electricity relationship is complex caused by the difference of different reservoir pore permeation types, a rock core type division standard is constructed according to a rock core type classification result, the fitting relationship between the resistivity increase coefficient and the water saturation, and between the formation factor and the porosity of a target layer is reconstructed, rock electricity parameters corresponding to different rock core types are obtained according to the fitting relationship, the division indexes are quantized and unified, the fine evaluation of the saturation of the ultra-shallow non-diagenetic reservoir in the sea area is realized, and the method has important guiding significance for the fine calculation of the saturation of the ultra-shallow non-diagenetic reservoir in the sea area and the subsequent reserve popularization.
Drawings
Fig. 1 is a flow chart of a classification, interpretation and evaluation method for the saturation of a sea area ultra-shallow non-diagenetic reservoir fluid according to an embodiment of the invention;
FIG. 2 is a flow chart of a method for obtaining artificial core petrophysical experiment results of ultra-shallow non-diagenetic target reservoir characteristics in a sea area according to an embodiment of the present invention;
FIG. 3 is a flow chart of a method for calculating a target reservoir porosity from target reservoir log data according to an embodiment of the present invention;
FIG. 4 is a method for calculating a target reservoir permeability based on target reservoir porosity according to an embodiment of the present invention
FIG. 5 is a structural block diagram of a classification, interpretation and evaluation system for the saturation of a sea area ultra-shallow non-diagenetic reservoir fluid according to an embodiment of the invention;
FIG. 6 is a schematic diagram of the measurement results of the porosity and permeability of an artificial core conforming to the characteristics of an ultra-shallow non-diagenetic natural gas reservoir in a sea area according to an embodiment of the present invention;
FIG. 7 is a schematic diagram showing the measurement results of water saturation and resistivity increase coefficient of an artificial core according to the characteristics of a natural gas reservoir with ultra-shallow non-diagenetic rock in a sea area according to an embodiment of the present invention;
FIG. 8 is a schematic diagram of the measurement results of the porosity and formation factor of an artificial core conforming to the characteristics of an ultra-shallow non-diagenetic natural gas reservoir in a sea area according to an embodiment of the present invention;
FIG. 9 is a schematic illustration of a core NMR according to an embodiment of the invention A distribution spectrum diagram;
FIG. 10 is a schematic illustration of a core NMR according to an embodiment of the invention A result diagram after distribution spectrum classification;
FIG. 11 is a graph showing the relationship and parameters of the resistivity increase coefficient and the water saturation after classification according to the embodiment of the present invention;
FIG. 12 is a graph of the relationship and parameters of the re-established porosity versus formation factor after classification in accordance with an embodiment of the present invention;
FIG. 13 is a diagram illustrating the X1 well parameters and classification results according to an embodiment of the present invention;
FIG. 14 is a schematic diagram of the result of calculating saturation by using uniform parameters for the X1 well according to the embodiment of the present invention;
FIG. 15 is a schematic diagram of the result of classifying and calculating saturation of an X1 well according to an embodiment of the present invention.
In the figure, a data acquisition module, a core classification module and a data acquisition module, 3, dividing the standard to construct a module, and 4, a rock electric parameter determining module, 5, a reservoir type determining module, 6 and a saturation calculating module.
Detailed Description
The invention will now be described in more detail by way of exemplary embodiments with reference to the accompanying drawings. It is to be understood that elements, structures, and features of one embodiment may be beneficially incorporated in other embodiments without further recitation.
The invention provides a sea area ultra-shallow non-diagenetic reservoir fluid saturation classification interpretation and evaluation method and system, which are based on nuclear magnetic resonance by conforming to artificial core experimental results of sea area ultra-shallow non-diagenetic reservoir characteristics containing natural gasThe method comprises the steps of classifying rock cores according to a distribution spectrum, calculating a fluid index according to the porosity and permeability of an artificial rock core, establishing a rock core type classification standard based on the fluid index, reestablishing fitting relations between resistivity increase coefficients and water saturation of different types of rock cores and between formation factors and porosity of a target layer based on the rock core classification result to obtain rock electric parameters corresponding to different types of rock cores, determining a target reservoir type based on the rock core type classification standard, further determining rock electric parameters of the target reservoir, and calculating the water saturation of the target reservoir according to the rock electric parameters of the target reservoir to achieve fine evaluation of the fluid saturation of the ultra-shallow non-diagenetic reservoir in a sea area. The method and the system for classifying, explaining and evaluating the fluid saturation of the ultra-shallow non-diagenetic reservoir in the sea area are described in detail below with reference to the accompanying drawings.
Referring to fig. 1, an embodiment of the first aspect of the present invention provides a method for classifying, explaining and evaluating the saturation of a fluid in an ultra-shallow non-diagenetic reservoir in a sea area, which includes the steps of:
S1, acquiring a rock physical experiment result of an artificial rock core and logging curve data of a target reservoir, wherein the rock physical experiment result and the logging curve data of the target reservoir accord with the characteristics of the ultra-shallow non-diagenetic target reservoir in a sea area. The experimental results include nuclear magnetic resonance Distribution spectrum, porosity, permeability, water saturation, resistivity increase factor, formation factor.
In an embodiment of the present application, referring to fig. 2, the method for obtaining the rock physical experiment result of the artificial rock core of the ultra-shallow non-diagenetic objective reservoir characteristic of the sea area is as follows:
s11, manufacturing an artificial rock core which meets the characteristics of the ultra-shallow non-diagenetic target reservoir in the sea area.
When the artificial rock core is manufactured, parameters such as a porosity distribution range, a permeability distribution range and the like of the artificial rock core need to be inhibited with an undisturbed stratum, and are consistent with characteristics of a reservoir stratum with the purpose of ultra-shallow and non-diagenetic in a sea area.
S12, measuring the porosity and permeability of the artificial rock core under the set temperature condition.
S13, adopting brine with set mineralization degree to saturate the artificial rock core.
S14, placing the saturated artificial rock core into a nuclear magnetic resonance imaging system, setting echo interval time, waiting time, collecting the number of echo strings and scanning times, and measuring magnetic resonanceA distribution spectrum.
And S15, under stratum conditions, measuring the core resistivity and the water saturation under different water saturation conditions through a displacement experiment, and calculating a resistivity increase coefficient and a stratum factor according to the core resistivity.
In experimental test and analysis, the measurement conditions required to be consistent with the undisturbed stratum include stratum temperature, stratum pressure, stratum water mineralization degree and the like.
Specifically, in an embodiment of the present application, the resistivity increase coefficient is calculated according to the core resistivity by a resistivity increase coefficient calculation formula;
In the formula, The resistivity of the core is increased by a factor,In order to achieve the resistivity of the core after displacement,Is the core resistivity at saturation.
Specifically, in an embodiment of the present application, a formation factor is calculated according to a core resistivity by a formation factor calculation formula;
In the formula, As the formation factor of the core,Is the resistivity of the core when in saturation,Is the resistivity of the saturated solution.
S2, classifying the rock core according to nuclear magnetic resonanceThe cores are classified according to different intervals of distribution spectrum distribution.
Note that, nuclear magnetic resonanceThe distribution spectrum size may characterize the pore size. Nuclear magnetic resonance of different coresThe distribution spectrum forms have obvious difference and nuclear magnetic resonanceThe overall morphology of the distribution spectrum is consistent. Mainly in a unimodal form, nuclear magnetic resonance between different types of coresDistribution spectrum is as high as the peak size and nuclear magnetic resonanceThe distribution spectrum is different in distribution range. Thus, according to nuclear magnetic resonanceThe different intervals of the distribution spectrum distribution can effectively classify the rock cores.
And S3, screening the rock cores conforming to the same type according to the rock core classification result, calculating the fluid index of each rock core according to the porosity and permeability of each rock core, and establishing a rock core type classification standard according to the fluid index.
Specifically, in an embodiment of the present application, the fluid index of the core is calculated according to the porosity and permeability of the core through a fluid index calculation formula;
In the formula, As the fluid index of the core,For the permeability of the core,Is the porosity of the core.
The fluid index is calculated by integrating the porosity and the permeability, so that a multi-parameter coupled classification standard is constructed, and the problem of classification deviation caused by the fact that the traditional method only depends on the porosity or the permeability is solved.
It should be noted that, for the same type of core, itThe values are concentrated in a range of values,The larger the value, the better the reservoir porosity structure, the larger the communicated pores occupy more, and the better the pore-throat relationship. Statistical determination of cores of the same typeUpper and lower limits of values, different types of coresThe interval distribution of values may divide the core into different types. For example, a type I core, a type II core, a type III core, wherein the type I core corresponds to a higher coreThe value is higher, the permeability is higher, the core permeability is better, the porosity structure is better, and the class II core corresponds to mediumThe value is between the class I core and the class III core, the physical property of the core is medium, and the class III core is relatively lowThe value is lower, the permeability is lower, the general mud content is higher, and the pore connectivity is poor.
And S4, determining the rock electric parameters, namely establishing a fitting relation between the resistivity increase coefficient and the water saturation and between the formation factor and the porosity of the rock cores of the same type, and obtaining the rock electric parameters corresponding to the rock cores of the same type according to the fitting relation.
Specifically, in one embodiment of the present application, the fit of the resistivity increase coefficient to the water saturation is expressed as:
In the formula, The resistivity of the core is increased by a factor,Is a parameter of the lithology of the rock,The water saturation of the core,Is a saturation index;
specifically, in one embodiment of the present application, the formation factor is fitted to the porosity:
In the formula, As the formation factor of the core,Is a parameter of the lithology of the rock,Is the porosity of the core, and the porosity of the core,Is a cementation index.
Based on the core experimental results, the fitting relation between the resistivity increase coefficient and the water saturation of different types of cores and between the formation factor and the porosity is established, the correlation coefficient is obviously better, and the saturation of reservoirs with different pore-permeability relations can be better reflected.
And S5, a reservoir type determining step, namely calculating the porosity of the target reservoir according to the logging curve data of the target reservoir, calculating the permeability of the target reservoir according to the porosity of the target reservoir, calculating the fluid index of the target reservoir according to the porosity of the target reservoir and the permeability of the target reservoir, and determining the type of the target reservoir based on the core type dividing standard according to the fluid index.
Specifically, referring to fig. 3, in one embodiment of the present application, the method for calculating the porosity of the target reservoir according to the log data of the target reservoir is as follows:
S511, calculating a natural gamma relative value;
In the formula, Is a natural gamma relative value; For the natural gamma logging value of the target layer, the unit is: an API; is the natural gamma logging value of the pure lithology stratum, and the unit is API; is a natural gamma log value of clear clay rock stratum, unit is API.
S512, calculating the shale content of the reservoir according to the natural gamma relative value;
In the formula, For the shale content of the reservoir,For empirical coefficients related to formation age, when the target reservoir is a new formation (i.e., near-ancient, recent), takeWhen the target reservoir is an old stratum, take =3.7=2.0。
S513, respectively calculating the density porosity after the shale correction and the neutron porosity after the shale correction according to the shale content of the reservoir;
In the formula, The unit is decimal for the density porosity after clay correction; the unit is decimal for neutron porosity after clay correction; The density value of the rock skeleton is given in g/cm 3; is the density value of the stratum fluid, and the unit is g/cm 3; The density value of the mudstone is given in g/cm 3; For the density logging value of the target layer, g/cm 3 is adopted; Neutron value of rock skeleton in%; Neutron value of formation fluid in percent; Neutron value of mudstone, unit is percent; the unit is percent of neutron logging value in the target layer; the unit is decimal for the clay content of the reservoir;
S514, calculating the porosity of the target reservoir according to the density porosity after the muddy correction and the neutron porosity after the muddy correction;
In the formula, Reservoir porosity for the purpose.
The ultra-shallow non-diagenetic reservoir in the sea area has the characteristics of high formation water mineralization degree, high argillaceous content and sand shale heterogeneity, and neutron and density logging is not influenced by argillaceous distribution and compaction degree, but is sensitive to the influence reaction of argillaceous. Therefore, the target reservoir porosity is calculated by adopting a neutron-density intersection method, and in the calculation process of the target reservoir porosity, the muddy correction is carried out simultaneously, so that the accuracy of the calculated target reservoir porosity is high.
Specifically, in one embodiment of the present application, referring to fig. 4, the method for calculating the permeability of the target reservoir according to the porosity of the target reservoir is as follows:
S521, establishing a porosity-permeability fitting relation according to the porosity and permeability of the artificial rock core in the data acquisition step;
S522, calculating the target reservoir permeability according to the target reservoir porosity through a porosity-permeability fitting relation.
And S6, determining a rock electricity parameter corresponding to the target reservoir according to the reservoir type of the target reservoir, and calculating the water saturation of the target reservoir according to the rock electricity parameter of the target reservoir.
Specifically, in one embodiment of the application, the water saturation of the target reservoir is calculated according to the determined rock electricity parameters through an Alqi formula;
In the formula, For the purpose of water saturation of the reservoir,Is a parameter of the lithology of the rock,For the purposes of the cement index,In the sense of the saturation index,For the purpose of reservoir porosity,For the formation water resistivity to be high,Reservoir resistivity log values for the purpose.
According to the classification, interpretation and evaluation method for the fluid saturation of the ultra-shallow non-diagenetic reservoir in the sea area, on the basis of determining that the rock-electricity relationship is complex due to the difference of pore-permeation types of different reservoirs, a rock core type classification standard is constructed according to a rock core type classification result, the fitting relationship between the resistivity increase coefficient and the water saturation as well as between the formation factor and the porosity of a target layer is reconstructed, rock-electricity parameters corresponding to different rock core types are obtained according to the fitting relationship, the classification index is quantized and unified, fine evaluation of the fluid saturation of the ultra-shallow non-diagenetic reservoir in the sea area is realized, and the method has important guiding significance for the fine calculation of the saturation of the ultra-shallow non-diagenetic reservoir in the sea area and the subsequent general reserve.
Referring to fig. 5, in a second aspect of the present invention, a classification, interpretation and evaluation system for fluid saturation of a shallow and non-diagenetic reservoir in a sea area is provided, where the classification, interpretation and evaluation method for fluid saturation of a shallow and non-diagenetic reservoir in a sea area according to the first aspect of the present invention includes:
the data acquisition module 1 is used for acquiring the rock physical experiment result of the artificial rock core and the logging curve data of the target reservoir, which accord with the characteristics of the ultra-shallow non-diagenetic target reservoir in the sea area;
Core classification module 2, based on nuclear magnetic resonance Classifying the rock cores according to different intervals of distribution spectrum distribution;
The division standard construction module 3 is used for screening the rock cores conforming to the same type according to the rock core classification result, calculating the fluid index of each rock core according to the porosity and the permeability of each rock core, and establishing a rock core type division standard according to the fluid index;
The rock electric parameter determining module 4 establishes a fitting relation between the resistivity increase coefficient and the water saturation, and between the formation factor and the porosity of the target layer for the rock cores of the same type, and obtains the rock electric parameters corresponding to the rock cores of the same type according to the fitting relation;
The reservoir type determining module 5 calculates the porosity of the target reservoir according to the logging curve data of the target reservoir, calculates the permeability of the target reservoir according to the porosity of the target reservoir, calculates the fluid index of the target reservoir according to the porosity of the target reservoir and the permeability of the target reservoir, and determines the type of the target reservoir based on the core type dividing standard according to the fluid index;
the saturation calculation module 6 calculates the water saturation of the reservoir of interest from the determined petroelectric parameters.
According to the classification, interpretation and evaluation system for the saturation of the ultra-shallow non-diagenetic reservoir fluid in the sea area, on the basis of determining that the rock-electricity relationship is complex due to the difference of pore-permeation types of different reservoirs, a rock core type classification standard is constructed according to a rock core type classification result, the fitting relationship between a resistivity increase coefficient and water saturation as well as between a formation factor and the porosity of a target layer is reconstructed, rock-electricity parameters corresponding to different rock core types are obtained according to the fitting relationship, and the classification index is quantized and unified, so that the fine evaluation of the saturation of the ultra-shallow non-diagenetic reservoir fluid in the sea area is realized, and the method has important guiding significance for the fine calculation of the saturation of the ultra-shallow non-diagenetic reservoir in the sea area and the subsequent general reserve.
In order to verify the effectiveness of the method and the system for classifying, explaining and evaluating the fluid saturation of the ultra-shallow non-diagenetic reservoir in the sea area according to the embodiment of the invention, the following specific embodiment is used for explanation.
Example A destination reservoir selects the Qiongsoutheast basin ultra-deep ultra-shallow water tomb water 36-1 block Ledong group.
S1, preparing a batch of plunger rock samples for simulating the physical characteristics of ultra-high pore rock seepage of the shallow layer non-diagenetic non-consolidated extremely fine sediment on the sea according to the statistical analysis result of the ultra-deep water ultra-shallow layer cemetery water 36-1 block Ledong group of the southeast basin of the agar, wherein the characteristic parameters accord with the characteristics of high formation water mineralization, high argillaceous content and non-uniformity of sandy shale of the natural gas reservoir in the ultra-shallow non-diagenetic region of the sea. The experimental study was conducted according to the national standard SY/T6385-2016 of the method for measuring rock porosity and permeability under overburden by the people's republic of China and the national standard SY/T5385-2007 of the method for measuring and calculating rock resistivity parameter laboratory, and the porosity and permeability of 120 artificial cores were measured at the design temperature of 18 ℃, as shown in FIG. 6. Core saturation is carried out by adopting saturated solution with mineralization degree of 35000 ppm by using an evacuating and pressurizing saturation device, under stratum conditions, core resistivity under different water saturation conditions is measured by using an array type capillary pressure resistivity joint measurement system, water saturation, resistivity increase coefficient and stratum factor are obtained, porosity-stratum factor is fitted, water saturation-resistivity increase coefficient is established, power function relation is established, and rock electric parameters are determined、、、As shown in fig. 7 and 8. Obtaining
Relationship of resistivity increase coefficient to water saturation:
Relationship between formation factor and porosity:
Rock nuclear magnetic resonance experiments by measuring nuclear magnetic resonance signals of pore fluid hydrogen nuclei in a plunger rock sample, the transverse relaxation time closely related to the change in signal intensity and pore structure is determined Distribution, which provides an important basis for assessing rock pore structure. Because the core has higher porosity, the size distribution of the void space in the rock sample is wider, and a MicroMR-040V nuclear magnetic resonance imaging system is adopted to set the echo interval time in order to prevent signal loss and keep the instrument stable in the test process0.3Ms, the number of acquired echo strings NECH is 15000, and the waiting time is5000Ms and 16 scans. 120 nuclear magnetic resonanceThe distribution spectrum distribution is shown in fig. 9.
S2, according to the core experiment result of the step S1, nuclear magnetic resonance-basedDistribution spectrum according to nuclear magnetic resonanceAnd classifying the rock cores according to different distribution spectrum distribution intervals. From nuclear magnetic resonanceIn terms of distribution spectrum distribution ranges, the main distribution range of the type I sample is 100-300ms, the peak value is mainly concentrated at about 150ms, the main distribution range of the type II sample is 30-100ms, the peak value is mainly concentrated at about 50ms, the main distribution range of the type III sample is 6-30ms, and the peak value is mainly concentrated at about 20 ms. The core classification results are shown in fig. 10.
And S3, screening the rock cores conforming to the same type according to the rock core classification result, calculating the fluid index of each rock core according to the porosity and the permeability of each rock core, and establishing a rock core type classification standard according to the fluid index.
Corresponding to the same core type, whichThe values are concentrated in a certain range, and the same type of rock core is statistically determinedUpper and lower limits of values, different types of coresInterval distribution of values. The class I core corresponds to higherThe value of the sum of the values,More than or equal to 15, higher permeability, good core seepage capability and better porosity structure, and class II core corresponds to mediumValue, 15 ]12, Between class I and class III, the core physical properties are medium, class III corresponds to a lower FI value, 12 is less than or equal toThe permeability is lower, the general mud content is higher, and the pore connectivity is poor.
S4, according toClassifying all 120 cores into corresponding I, II and III, and reestablishing resistivity increase coefficientsSaturation with waterThe correlation coefficient of the (B) is obviously better, and the resistivity increase coefficient can be better reflectedSaturation with waterAs shown in fig. 11, the relationships thereof after classification are as follows:
Class I:
class II:
Class III:
Reestablishing formation factors And porosity ofThe correlation coefficient of the water-soluble polymer is obviously better, and stratum factors can be better reflectedAnd porosity ofAs shown in fig. 12, the relationships thereof after classification are as follows:
Class I:
class II:
Class III:
after classifying the core, the correlation between resistivity-saturation-porosity becomes better. Based on the analysis results, different types of division standards and selected rock electric parameters are determined as shown in table 1.
TABLE 1
S5, calculating the porosity of the target reservoir according to the logging curve data of the target reservoir, calculating the permeability of the target reservoir according to the porosity of the target reservoir, calculating the fluid index of the target reservoir according to the porosity of the target reservoir and the permeability of the target reservoir, and determining the type of the target reservoir based on the core type dividing standard according to the fluid index.
The ultra-shallow non-diagenetic zone 36-1 of the tomb water in the embodiment has the characteristics of high formation water mineralization, high argillaceous content and sandy argillaceous heterogeneity of the natural gas reservoir, and neutron and density logging is not influenced by argillaceous distribution and compaction degree, but is sensitive to the influence of argillaceous, so that a neutron-density intersection method is adopted to calculate the porosity of the target reservoir, and corresponding argillaceous correction is carried out.
In calculating the porosity of the target reservoir, the natural gas reservoir is taken as a new reservoir due to the ultra-shallow non-diagenetic natural gas reservoir of the cemetery water 36-1 block in the embodiment=3.7。
And (3) calculating the permeability of the reservoir by adopting a core hole-permeability fitting formula, establishing a porosity-permeability relation curve according to the porosity and permeability parameters measured by the artificial core which accords with the characteristics of the natural gas reservoir in the ultra-shallow non-diagenetic rock of the sea area in the step (S1), and calculating the permeability of the stratum according to the fitting curve, wherein the permeability is obtained according to the porosity-permeability relation fitting formula.
Specifically, parameters such as the well clearance, permeability and the like of the cemetery water 36-1 block X1 are calculated, and the classification result is shown in FIG. 13. The first channel in the graph is a depth channel, the ultra-shallow non-diagenetic natural gas-containing reservoir in the sea area is usually within 500m of the sea floor, the depth in the graph is the sea level depth, the second channel is a natural GR curve, the third channel is a deep and shallow resistivity curve, the fourth channel is a neutron porosity well logging curve and a density porosity well logging curve, the fifth channel is a permeability curve calculated according to a porosity-permeability relation fitting formula, the sixth channel is a porosity curve and a lithology profile curve calculated according to a target reservoir porosity calculation formula, and the seventh channel is different reservoir types obtained through calculation and classification.
And S6, calculating the gas saturation of the reservoir according to the reservoir classification result and the rock electric parameters in the step S5 and combining an Alqi formula.
Specifically, according to the Waxman-Smits model, the argillaceous sandstone conductivity is seen as a result of the combined effect of free formation water conduction in the rock pores and cation-exchange conduction associated with clay. Under the condition of low mineralization equilibrium solution, the conductivity of the stratum is simultaneously influenced by the combination of the argillaceous and the stratum water, and the conductivity of argillaceous sandstone presents nonlinearity. When the mineralization of the solution exceeds 20200ppm, the cation exchange mobility will reach a constant (maximum), the conductivity of the formation water is enhanced, the duty ratio of the argillaceous additional conductive contribution is reduced, the conductivity of the argillaceous sandstone is linear and parallel to the pure sandstone line, and the Alqi formula is still applicable to the argillaceous sandstone reservoir. According to the result of analysis and test data of the water of the target layer of the cemetery 36-1 block, the mineralization degree of the stratum water of the natural gas-containing reservoir layer of the ultra-shallow non-diagenetic stratum of the south China sea area is 35000ppm, so that the saturation degree can be evaluated by adopting an Alqi formula.
Specifically, the rock electric parameter is determined according to the relation between the porosity and the stratum factor obtained by the experiment in the step S1 and the water saturation and the resistivity increase coefficient=1.0、=1.0、=1.51、=2.17, The X1 well full section saturation was calculated using the allch formula and the siemens formula with uniform parameters, respectively, and the calculation result is shown in fig. 14. The first to sixth channels in the graph are consistent with the graph in FIG. 9, the seventh channel is an X1 well whole-well section water saturation curve calculated by adopting a Siemens formula, an Alqi formula and rock electric parameters obtained by closed coring, and the eighth channel is a logging interpretation conclusion.
The calculation result shows that the rock electric parameters determined based on the artificial rock sample experimental result are that m=1.511 and n=2.17, the influence of sand and shale heterogeneous reservoir is larger, the water saturation is calculated to be higher by the traditional Arch formula for a low-resistance reservoir section, the influence of the additional electric conduction effect of the argil on the formation resistivity can be eliminated to a certain extent by the argil correction by the Siemens formula, but in the practical application process, the accuracy of the saturation calculation is limited due to the reasons of model assumption conditions, parameter selection and the like, on the one hand, the argil is assumed to contain oil, gas and water like pure sandstone by the Siemens formula, pore bound water is regarded as free water by subtracting the water after the argil correction, and the water saturation is calculated to be lower by the traditional Alqi formula, and on the other hand, the rock electric parameters are usually used as empirical values or values obtained by rock electric experiments directly, but are not rock electric parameter values without the influence of the argil electric conduction.
Specifically, the saturation results of the X1 well are calculated as shown in FIG. 15. The first to seventh channels in the graph are consistent with the graph in FIG. 14, the eighth channel is a saturation curve calculated by the water saturation curve obtained by calculation of the method and the system in the application, the experimental result obtained by closed coring is calculated, the ninth channel is a difference value of results of two saturation calculation methods, and the tenth channel is a logging interpretation conclusion. By comparing the calculated results of different reservoir sections, the calculated water saturation of the class I reservoir is lower, the calculated water saturation of the class II reservoir is equivalent to the calculated water saturation of the class II reservoir, and the calculated water saturation of the class III reservoir is higher compared with the closed coring result. The method and the system of the application improve the gas saturation of the class I high-quality reservoir and reduce the saturation of the class III relatively low-quality reservoir. The saturation calculation result is compared with the actual stratum test result, the class I reservoir pore-permeation relationship is best, the pore connectivity is good, gas is easy to fill, and the gas saturation is higher. According to the method and the system, through fine classification of the reservoirs, rock electric parameters of different reservoir types are obtained, saturation calculation is carried out based on an Archie formula, and gas saturation fine interpretation and evaluation of the ultra-shallow non-diagenetic reservoirs in the sea are realized.
The above-described embodiments are intended to illustrate the present invention, not to limit it, and any modifications and variations made thereto are within the spirit of the invention and the scope of the appended claims.
Claims (10)
1. A sea area ultra-shallow non-diagenetic reservoir fluid saturation classification interpretation and evaluation method is characterized by comprising the following steps:
The data acquisition step comprises the steps of acquiring a rock physical experiment result of an artificial rock core and logging curve data of a target reservoir, wherein the artificial rock core and the logging curve data of the target reservoir accord with the characteristics of the target reservoir of ultra-shallow non-diagenetic in a sea area, and the experiment result comprises nuclear magnetic resonance Distribution spectrum, porosity, permeability, water saturation, resistivity increase coefficient, formation factor;
classifying the core according to nuclear magnetic resonance Classifying the rock cores according to different intervals of distribution spectrum distribution;
Screening rock cores conforming to the same type according to the rock core classification result, calculating the fluid index of each rock core according to the porosity and permeability of each rock core, and establishing a rock core type classification standard according to the fluid index;
the rock electric parameter determining step, namely establishing a fitting relation between the resistivity increase coefficient and the water saturation, and between the formation factor and the porosity of the rock core of the same type, and obtaining rock electric parameters corresponding to the rock core of the same type according to the fitting relation;
A reservoir type determining step of calculating a target reservoir porosity according to target reservoir logging curve data, calculating a target reservoir permeability according to the target reservoir porosity, calculating a fluid index of the target reservoir according to the target reservoir porosity and the target reservoir permeability, and determining a target reservoir type based on a core type dividing standard according to the fluid index;
and the saturation calculating step is used for determining the rock electric parameters corresponding to the target reservoir according to the reservoir type of the target reservoir and calculating the water saturation of the target reservoir according to the rock electric parameters of the target reservoir.
2. The method for classifying, interpreting and evaluating the saturation of a reservoir fluid in an ultra-shallow non-diagenetic area of a sea as claimed in claim 1, wherein in the step of obtaining data, the method for obtaining the results of the artificial core petrophysical experiment of the reservoir characteristics in the ultra-shallow non-diagenetic area of the sea is as follows:
manufacturing an artificial rock core which accords with the characteristics of the reservoir stratum of the ultra-shallow non-diagenetic purpose of the sea area;
measuring the porosity and permeability of the artificial rock core under the set temperature condition;
Adopting brine with set mineralization degree to saturate the artificial rock core;
Placing the saturated artificial core into a nuclear magnetic resonance imaging system, setting echo interval time, waiting time, number of acquired echo strings and scanning times, and measuring magnetic resonance A distribution spectrum;
Under stratum conditions, core resistivity and water saturation under different water saturation conditions are measured through displacement experiments, and resistivity increase coefficients and stratum factors are calculated according to the core resistivity.
3. The classification, interpretation and evaluation method for the saturation of the ultra-shallow non-diagenetic reservoir fluid in the sea area as claimed in claim 2, wherein the resistivity increase coefficient is calculated according to the core resistivity by a resistivity increase coefficient calculation formula;
In the formula, The resistivity of the core is increased by a factor,In order to achieve the resistivity of the core after displacement,Is the core resistivity at saturation.
4. The classification, interpretation and evaluation method for the saturation of the ultra-shallow non-diagenetic reservoir fluid in the sea area as claimed in claim 2, wherein the formation factor is calculated according to the rock core resistivity through a formation factor calculation formula;
In the formula, As the formation factor of the core,Is the resistivity of the core when in saturation,Is the resistivity of the saturated solution.
5. The classification interpretation and evaluation method of the saturation of the ultra-shallow non-diagenetic reservoir fluid in the sea area according to claim 1, wherein in the step of constructing the partition criteria, the fluid index of the core is calculated according to the porosity and permeability of the core by a fluid index calculation formula;
In the formula, As the fluid index of the core,For the permeability of the core,Is the porosity of the core.
6. The classification interpretation and evaluation method of the saturation of ultra shallow non-diagenetic reservoir fluid in the sea area as claimed in claim 1, wherein in the step of determining the rock electrical parameter, the fitting relation of the resistivity increase coefficient and the water saturation is expressed as:
In the formula, The resistivity of the core is increased by a factor,Is a parameter of the lithology of the rock,The water saturation of the core,Is a saturation index;
The fit of the formation factor to the porosity is expressed as:
In the formula, As the formation factor of the core,Is a parameter of the lithology of the rock,Is the porosity of the core, and the porosity of the core,Is a cementation index.
7. The method for classifying, interpreting and evaluating the saturation of ultra-shallow non-diagenetic reservoir fluid in a sea area according to claim 1, wherein in the reservoir type determining step, the method for calculating the porosity of the target reservoir according to the logging profile data of the target reservoir is as follows:
calculating a natural gamma relative value;
In the formula, Is a natural gamma relative value; For the natural gamma logging value of the target layer, the unit is: an API; is the natural gamma logging value of the pure lithology stratum, and the unit is API; is the natural gamma logging value of clear clay rock stratum, unit is API;
calculating the shale content of the reservoir according to the natural gamma relative value;
In the formula, For the shale content of the reservoir,Is an empirical coefficient related to formation age;
Respectively calculating the density porosity after the shale correction and the neutron porosity after the shale correction according to the shale content of the reservoir;
In the formula, The unit is decimal for the density porosity after clay correction; the unit is decimal for neutron porosity after clay correction; The density value of the rock skeleton is given in g/cm 3; is the density value of the stratum fluid, and the unit is g/cm 3; The density value of the mudstone is given in g/cm 3; For the density logging value of the target layer, g/cm 3 is adopted; Neutron value of rock skeleton in%; Neutron value of formation fluid in percent; Neutron value of mudstone, unit is percent; the unit is percent of neutron logging value in the target layer; the unit is decimal for the clay content of the reservoir;
Calculating the porosity of the target reservoir according to the density porosity after the muddy correction and the neutron porosity after the muddy correction;
In the formula, Reservoir porosity for the purpose.
8. The method for classifying, interpreting and evaluating the saturation of ultra-shallow non-diagenetic reservoir fluid in a sea area according to claim 1, wherein in said reservoir type determining step, the method for calculating the target reservoir permeability according to the target reservoir porosity comprises the steps of:
establishing a porosity-permeability fitting relation according to the porosity and permeability of the artificial rock core in the data acquisition step;
and calculating the permeability of the target reservoir according to the porosity of the target reservoir through the porosity-permeability fitting relation.
9. The method for classifying, interpreting and evaluating the saturation of ultra-shallow non-diagenetic reservoir fluid in a sea area according to claim 1, wherein in the step of calculating the saturation, the water saturation of the target reservoir is calculated by an alchi formula according to the determined rock electric parameters;
In the formula, For the purpose of water saturation of the reservoir,Is a parameter of the lithology of the rock,For the purposes of the cement index,In the sense of the saturation index,For the purpose of reservoir porosity,For the formation water resistivity to be high,Reservoir resistivity log values for the purpose.
10. A classification, interpretation and evaluation system for the saturation of a sea area ultra-shallow non-diagenetic reservoir fluid, for implementing the classification, interpretation and evaluation method for the saturation of a sea area ultra-shallow non-diagenetic reservoir fluid according to any one of claims 1 to 9, comprising:
The data acquisition module is used for acquiring the rock physical experiment result of the artificial rock core and the logging curve data of the target reservoir, which are in accordance with the characteristics of the target reservoir of the ultra-shallow non-diagenetic sea area;
Core classification module according to nuclear magnetic resonance Classifying the rock cores according to different intervals of distribution spectrum distribution;
the partition standard construction module is used for screening the rock cores conforming to the same type according to the rock core classification result, calculating the fluid index of each rock core according to the porosity and the permeability of each rock core, and establishing a rock core type partition standard according to the fluid index;
the rock electric parameter determining module is used for establishing a fitting relation between the resistivity increase coefficient and the water saturation, between the formation factor and the porosity of the target layer for the rock cores of the same type, and obtaining rock electric parameters corresponding to the rock cores of the same type according to the fitting relation;
The reservoir type determining module is used for calculating the porosity of the target reservoir according to the logging curve data of the target reservoir, calculating the permeability of the target reservoir according to the porosity of the target reservoir, calculating the fluid index of the target reservoir according to the porosity of the target reservoir and the permeability of the target reservoir, and determining the type of the target reservoir based on the core type dividing standard according to the fluid index;
and the saturation calculation module is used for determining the rock electric parameters corresponding to the target reservoir according to the reservoir type of the target reservoir and calculating the water saturation of the target reservoir according to the rock electric parameters of the target reservoir.
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