Classification Interpretation and Evaluation Method and System for Fluid Saturation in Ultra-Shallow Unconsolidated Reservoirs in Sea Areas

Abstract

The present invention belongs to the technical field of oil exploration and development, and relates to a method and system for classifying, interpreting and evaluating the fluid saturation of ultra-shallow unconsolidated reservoirs in the sea area. The method steps are as follows: obtaining the results of petrophysical experiments on artificial cores and the logging curve data of the target reservoir that conform to the characteristics of ultra-shallow unconsolidated target reservoirs in the sea area; classifying the cores based on the nuclear magnetic resonance distribution spectrum; calculating the fluid index according to the porosity and permeability of the artificial cores, and establishing a core type classification standard based on the fluid index; based on the core classification results, re-establishing the fitting relationships between the resistivity increase factor and the water saturation, and between the formation factor and the porosity of the target layer for different types of cores, obtaining the petroelectric parameters corresponding to different types of cores, determining the type of the target reservoir based on the core type classification standard, and further determining the petroelectric parameters of the target reservoir; calculating the water saturation of the target reservoir according to the petroelectric parameters of the target reservoir. The present invention can finely evaluate the fluid saturation of ultra-shallow unconsolidated reservoirs in the sea area.

Description

Technical Field

[0001] The present invention belongs to the technical field of oil and gas exploration and development, relates to the classification interpretation and evaluation technology of reservoir fluid saturation, and particularly relates to a method and system for classifying and interpreting the fluid saturation of ultra-shallow unconsolidated reservoirs in the sea area. Background Art

[0002] In the field of oil and gas exploration and development, the interpretation and evaluation of fluid saturation, as a key technology, is used to quantitatively describe the filling degree of various fluids (such as water, oil, and gas) in the pores of reservoir rocks, and is one of the core parameters for predicting reservoir productivity and reserves. Traditional fluid saturation calculation methods usually rely on formed and pressure-bearing piston cores to conduct rock physics experiments, obtain rock electrical parameters, and build saturation interpretation models (such as Archie's formula or its variants) based on this.

[0003] However, for ultra-shallow gas-bearing reservoirs in the sea area, most of the rocks are in an unconsolidated and uncemented state, with loose rock structures, making coring operations difficult and lacking supporting rock physics experimental data. In this case, using existing fluid saturation calculation methods, the saturation accuracy is relatively low, seriously restricting the accurate assessment of shallow gas reserves in the sea area. To improve the calculation accuracy, preparing artificial cores matching the characteristics of the target target layer has become an important way to obtain rock electrical parameters of the target target layer. Even so, there are still practical problems of insufficient calculation accuracy in the saturation evaluation of ultra-shallow gas-bearing reservoirs in the sea area.

[0004] Currently, the fine evaluation of fluid saturation mostly adopts the idea of phase control, that is, calculating the saturation separately according to different reservoir categories to achieve refined evaluation. Common saturated fluid calculation methods include the fluid unit index method, the chart method, and machine learning methods, etc. These methods are mainly applicable to low-porosity and low-permeability reservoirs (such as shale, tight sandstone oil and gas reservoirs), fracture-vuggy carbonate reservoirs, and volcanic rock reservoirs. For ultra-shallow unconsolidated natural gas reservoirs in the sea area, the fluid saturation evaluation mostly uses the unified rock electrical parameters substituted into Archie's formula, or the Simandoux formula considering the influence of shale additional conductivity for overall calculation (for example, usually setting the rock electrical parameters as a = b = 1, m = n = 2). However, practical applications show that Archie's formula will seriously underestimate the gas saturation with extremely high porosity and permeability in high-quality reservoirs; although the Simandoux formula considers the additional conductivity of shale, it fails to fully consider the influence of the formation water salinity of the ultra-shallow layer in the sea area on the macroscopic conductivity, resulting in the calculated gas saturation being higher than the actual value during the calculation process due to the superposition of shale additional conductivity. The above problems directly lead to the difficulty in meeting the actual exploration and development requirements in the calculation of fluid saturation of ultra-shallow unconsolidated natural gas reservoirs in the sea area. Therefore, how to achieve the refined evaluation of fluid saturation of ultra-shallow unconsolidated natural gas reservoirs in the sea area has become a key technical problem that needs to be overcome urgently. Summary of the Invention

[0005] In view of the problems existing in the prior art, the present invention provides a method and system for classifying, interpreting and evaluating the fluid saturation of ultra-shallow unconsolidated reservoirs in the sea area, which can achieve a fine evaluation of the fluid saturation of ultra-shallow unconsolidated reservoirs in the sea area.

[0006] In the first aspect of the present invention, a method for classifying, interpreting and evaluating the fluid saturation of ultra-shallow unconsolidated reservoirs in the sea area is provided, and the steps are as follows:

[0007] Data acquisition step: Obtain the petrophysical experiment results of artificial cores and the logging curve data of the target reservoir that conform to the characteristics of ultra-shallow unconsolidated reservoirs in the sea area; the experiment results include nuclear magnetic resonance distribution spectrum, porosity, permeability, water saturation, resistivity increase factor, formation factor;

[0008] Core classification step: Classify the cores according to different intervals of the nuclear magnetic resonance distribution spectrum distribution;

[0009] Division standard construction step: Screen the cores that conform to the same type according to the core classification results, calculate the fluid index of each core according to the porosity and permeability of each core, and establish the core type division standard according to the fluid index;

[0010] Rock-electric parameter determination step: For cores of the same type, establish the fitting relationships between the resistivity increase factor and the water saturation, and between the formation factor and the porosity of the target layer, and obtain the corresponding rock-electric parameters of the cores of the same type according to the fitting relationships;

[0011] Reservoir type determination step: Calculate the porosity of the target reservoir according to the logging curve data of the target reservoir, calculate the permeability of the target reservoir according to the porosity of the target reservoir, calculate the fluid index of the target reservoir according to the porosity and permeability of the target reservoir, and determine the type of the target reservoir based on the core type division standard according to the fluid index;

[0012] Saturation calculation step: Determine the corresponding rock-electric parameters of the target reservoir according to the reservoir type to which the target reservoir belongs, and calculate the water saturation of the target reservoir according to the rock-electric parameters of the target reservoir.

[0013] In some embodiments, in the data acquisition step, the method for obtaining the petrophysical experiment results of artificial cores with the characteristics of ultra-shallow unconsolidated reservoirs in the sea area is as follows:

[0014] Fabricate artificial cores that conform to the characteristics of ultra-shallow unconsolidated reservoirs in the sea area;

[0015] Measure the porosity and permeability of the artificial cores under the set temperature conditions;

[0016] Saturate the artificial cores with brine of the set salinity;

[0017] Put the saturated artificial core into the nuclear magnetic resonance imaging system. After setting the echo spacing time, waiting time, number of acquired echo trains, and number of scans, measure the nuclear magnetic resonance distribution spectrum;

[0018] Under formation conditions, measure the core resistivity and water saturation under different water saturation conditions through displacement experiments, and calculate the resistivity increase factor and formation factor based on the core resistivity.

[0019] In some embodiments, calculate the resistivity increase factor based on the core resistivity through the resistivity increase factor calculation formula;

[0020]

[0021] In the formula, is the resistivity increase factor of the core, is the core resistivity after displacement, is the core resistivity at saturation.

[0022] In some embodiments, calculate the formation factor based on the core resistivity through the formation factor calculation formula;

[0023]

[0024] In the formula, is the formation factor of the core, is the core resistivity at saturation, is the resistivity of the saturated solution.

[0025] In some embodiments, in the step of constructing the division criterion, calculate the fluid index of the core through the fluid index calculation formula according to the porosity and permeability of the core;

[0026]

[0027] In the formula, is the fluid index of the core, is the permeability of the core, is the porosity of the core.

[0028] In some embodiments, in the step of determining the petrophysical parameters, the fitting relationship between the resistivity increase factor and the water saturation is expressed as:

[0029]

[0030] In the formula, is the resistivity increase factor of the core, is the lithology parameter, the water saturation of the core, is the saturation index;

[0031] The fitting relationship between the formation factor and porosity:

[0032]

[0033] In the formula, is the formation factor of the core, is the lithology parameter, is the porosity of the core, is the cementation index.

[0034] In some embodiments, in the step of determining the reservoir type, the method for calculating the porosity of the target reservoir according to the logging curve data of the target reservoir is:

[0035] Calculate the relative value of natural gamma;

[0036]

[0037] In the formula, is the relative value of natural gamma; is the natural gamma logging value of the target layer, unit: API; is the natural gamma logging value of the pure lithology formation, unit: API; is the natural gamma logging value of the pure shale formation, unit: API;

[0038] Calculate the shale content of the reservoir according to the relative value of natural gamma;

[0039]

[0040] In the formula, is the shale content of the reservoir, is the empirical coefficient related to the formation age;

[0041] Calculate the density porosity after shale correction and the neutron porosity after shale correction respectively according to the shale content of the reservoir;

[0042]

[0043]

[0044] In the formula, is the density porosity after shale correction, unit: decimal; is the neutron porosity after shale correction, unit: decimal; is the density value of the rock skeleton, unit: g / cm 3 ; is the density value of the formation fluid, unit: g / cm 3 ; is the density value of mudstone, unit: g / cm 3 ; is the density log value of the target layer, unit: g / cm 3 ; is the neutron value of the rock skeleton, unit: %; is the neutron value of the formation fluid, unit: %; is the neutron value of mudstone, unit: %; is the neutron log value of the target layer, unit: %; is the shale content of the reservoir, unit: decimal;

[0045] Calculate the porosity of the target reservoir according to the shale-corrected density porosity and the shale-corrected neutron porosity;

[0046]

[0047] In the formula, is the porosity of the target reservoir.

[0048] In some embodiments, in the reservoir type determination step, the method for calculating the permeability of the target reservoir according to the porosity of the target reservoir is:

[0049] Establish a porosity-permeability fitting relationship according to the porosity and permeability of the artificial core in the data acquisition step;

[0050] Calculate the permeability of the target reservoir through the porosity-permeability fitting relationship according to the porosity of the target reservoir.

[0051] In some embodiments, in the saturation calculation step, calculate the water saturation of the target reservoir according to the determined rock electrical parameters through Archie's formula;

[0052]

[0053] In the formula, is the water saturation of the target reservoir, is the lithology parameter, is the cementation exponent, is the saturation exponent, is the porosity of the target reservoir, is the resistivity of formation water, is the resistivity log value of the target reservoir.

[0054] In the second aspect of the present invention, there is provided a classification interpretation and evaluation system for the fluid saturation of ultra-shallow unconsolidated reservoirs in the sea area, which is used to implement the classification interpretation and evaluation method for the fluid saturation of ultra-shallow unconsolidated reservoirs in the sea area described in the first aspect of the present invention, including:

[0055] A data acquisition module, configured to acquire the petrophysical experiment results of artificial cores and the logging curve data of the target reservoir that conform to the reservoir characteristics of the ultra-shallow unconsolidated formations in the sea area;

[0056] A core classification module, which classifies cores according to different intervals of the nuclear magnetic resonance distribution spectrum;

[0057] A division standard construction module, which screens cores of the same type according to the core classification results, calculates the fluid index of each core according to the porosity and permeability of each core, and establishes a core type division standard based on the fluid index;

[0058] A rock-electric parameter determination module, for cores of the same type, establishes the fitting relationships between the resistivity increase factor and the water saturation, and between the formation factor and the porosity of the target layer, and obtains the corresponding rock-electric parameters of cores of the same type according to the fitting relationships;

[0059] A reservoir type determination module, which 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 and permeability of the target reservoir, and determines the type of the target reservoir based on the core type division standard according to the fluid index;

[0060] A saturation calculation module, which determines the corresponding rock-electric parameters of the target reservoir according to the reservoir type to which the target reservoir belongs, and calculates the water saturation of the target reservoir according to the rock-electric parameters of the target reservoir.

[0061] Compared with the prior art, the advantages and positive effects of the present invention are as follows:

[0062] The method and system for classifying, interpreting and evaluating the fluid saturation of ultra-shallow unconsolidated reservoirs in the sea area provided by the present invention are based on the core experiment results. By finding the distribution laws of the physical properties and rock-electric parameters of cores with different pore structure types, according to nuclear magnetic resonance Classify cores with different intervals of the distribution spectrum. According to the qualitative relationship among porosity, permeability, and fluid index, calculate the fluid index. Establish a core type classification standard based on the fluid index. Determine the petrophysical parameters of different types of cores according to the re-established fitting relationships between the resistivity increase factor and water saturation, and between the formation factor and the porosity of the target layer. Determine the target reservoir type based on the core type classification standard, and then determine the petrophysical parameters of the target reservoir. Calculate the fluid saturation of the target reservoir according to the petrophysical parameters of the target reservoir. On the basis of clarifying that the complexity of the petrophysical relationship is caused by the differences in pore-permeability types of different reservoirs, according to the classification results of core types, this invention constructs a core type classification standard, reconstructs the fitting relationships between the resistivity increase factor and water saturation, and between the formation factor and the porosity of the target layer. Obtain the petrophysical parameters corresponding to different core types according to the fitting relationships, quantify the classification indicators, and unify the standards, realizing the fine evaluation of the fluid saturation of ultra-shallow unconsolidated reservoirs in the sea area, which has important guiding significance for the fine calculation of the saturation of ultra-shallow unconsolidated reservoirs in the sea area and the subsequent reserve general survey. BRIEF DESCRIPTION OF THE DRAWINGS

[0063] Figure 1 It is a schematic flow chart of the method for classifying, interpreting, and evaluating the fluid saturation of ultra-shallow unconsolidated reservoirs in the sea area according to the embodiments of the present invention;

[0064] Figure 2 It is a schematic flow chart of the method for obtaining the petrophysical experimental results of artificial cores for the characteristics of ultra-shallow unconsolidated target reservoirs in the sea area according to the embodiments of the present invention;

[0065] Figure 3 It is a schematic flow chart of the method for calculating the porosity of the target reservoir according to the logging curve data of the target reservoir according to the embodiments of the present invention;

[0066] Figure 4 It is the method for calculating the permeability of the target reservoir according to the porosity of the target reservoir according to the embodiments of the present invention

[0067] Figure 5 It is a structural block diagram of the system for classifying, interpreting, and evaluating the fluid saturation of ultra-shallow unconsolidated reservoirs in the sea area according to the embodiments of the present invention;

[0068] Figure 6 It is a schematic diagram of the measurement results of the porosity and permeability of artificial cores conforming to the characteristics of ultra-shallow unconsolidated natural gas reservoirs in the sea area according to the embodiments of the present invention;

[0069] Figure 7 It is a schematic diagram of the measurement results of the water saturation and resistivity increase factor of artificial cores conforming to the characteristics of ultra-shallow unconsolidated natural gas reservoirs in the sea area according to the embodiments of the present invention;

[0070] Figure 8Schematic diagram of the measurement results of the porosity and formation factor of the artificial core conforming to the characteristics of the ultra-shallow unconsolidated natural gas reservoir in the sea area according to the embodiment of the present invention;

[0071] Figure 9 Nuclear magnetic resonance of the core according to the embodiment of the present invention Schematic diagram of the distribution spectrum;

[0072] Figure 10 Nuclear magnetic resonance of the core according to the embodiment of the present invention Schematic diagram of the classified results of the distribution spectrum;

[0073] Figure 11 Schematic diagram of the relationship and parameters between the resistivity increase factor and the water saturation re-established after classification according to the embodiment of the present invention;

[0074] Figure 12 Schematic diagram of the relationship and parameters between the porosity and the formation factor re-established after classification according to the embodiment of the present invention;

[0075] Figure 13 Schematic diagram of the parameters and classification results of Well X1 according to the embodiment of the present invention;

[0076] Figure 14 Schematic diagram of the saturation calculation results of Well X1 using unified parameters according to the embodiment of the present invention;

[0077] Figure 15 Schematic diagram of the saturation calculation results of Well X1 using classified calculation according to the embodiment of the present invention.

[0078] In the figure, 1. Data acquisition module, 2. Core classification module, 3. Division standard construction module, 4. Rock electrical parameter determination module, 5. Reservoir type determination module, 6. Saturation calculation module. Detailed implementation manners

[0079] Next, the present invention will be specifically described by way of exemplary embodiments in conjunction with the accompanying drawings. However, it should be understood that, without further elaboration, the elements, structures, and features in one embodiment can also be beneficially combined into other embodiments.

[0080] The present invention provides a method and system for classifying, interpreting, and evaluating the fluid saturation of an ultra-shallow unconsolidated reservoir in the sea area. Based on the experimental results of artificial cores conforming to the characteristics of the ultra-shallow unconsolidated natural gas reservoir in the sea area, and based on nuclear magnetic resonance The distribution spectrum classifies cores; calculates the fluid index based on the porosity and permeability of artificial cores, and establishes a core type classification standard based on the fluid index; based on the core classification results, re - establishes the fitting relationships between the resistivity increase factor and water saturation, and between the formation factor and the porosity of the target layer for different types of cores, obtains the petrophysical parameters corresponding to different types of cores, determines the type of the target reservoir based on the core type classification standard, and further determines the petrophysical parameters of the target reservoir; calculates the water saturation of the target reservoir according to the petrophysical parameters of the target reservoir, realizing the fine evaluation of the fluid saturation of ultra - shallow unconsolidated reservoirs in the sea area. The following will detail the above - mentioned method and system for classifying, interpreting, and evaluating the fluid saturation of ultra - shallow unconsolidated reservoirs in the sea area with reference to the accompanying drawings.

[0081] See Figure 1 , in the first - aspect embodiment of the present invention, a method for classifying, interpreting, and evaluating the fluid saturation of ultra - shallow unconsolidated reservoirs in the sea area is provided, and its steps are as follows:

[0082] S1. Data acquisition step: Obtain the petrophysical experiment results of artificial cores and the logging curve data of the target reservoir that conform to the characteristics of ultra - shallow unconsolidated target reservoirs in the sea area. The experiment results include nuclear magnetic resonance distribution spectrum, porosity, permeability, water saturation, resistivity increase factor, and formation factor.

[0083] In an embodiment of the present application, see Figure 2 , the method for obtaining the petrophysical experiment results of artificial cores that conform to the characteristics of ultra - shallow unconsolidated target reservoirs in the sea area is as follows:

[0084] S11. Fabricate artificial cores that conform to the characteristics of ultra - shallow unconsolidated target reservoirs in the sea area.

[0085] It should be noted that when fabricating artificial cores, parameters such as the porosity distribution range and permeability distribution range of the artificial cores need to be consistent with the undisturbed formation and conform to the characteristics of ultra - shallow unconsolidated target reservoirs in the sea area.

[0086] S12. Measure the porosity and permeability of the artificial cores under set temperature conditions.

[0087] S13. Saturate the artificial cores with brine of set salinity.

[0088] S14. Put the saturated artificial cores into a nuclear magnetic resonance imaging system, set the echo spacing time, waiting time, number of echo trains to be collected, and number of scans, and then measure the nuclear magnetic resonance distribution spectrum.

[0089] S15. Under formation conditions, measure the core resistivity and water saturation under different water saturation conditions through displacement experiments, and calculate the resistivity increase factor and formation factor according to the core resistivity.

[0090] It should be noted that during experimental testing and analysis, the measurement conditions must be consistent with the original formation, including formation temperature, formation pressure, formation water mineralization, etc.

[0091] Specifically, in one embodiment of the present application, the resistivity increase coefficient is calculated according to the core resistivity by using the resistivity increase coefficient calculation formula;

[0092]

[0093] In the formula, is the core resistivity enhancement factor, is the core resistivity after displacement, is the core resistivity at saturation.

[0094] Specifically, in one embodiment of the present application, the formation factor is calculated according to the core resistivity using a formation factor calculation formula;

[0095]

[0096] In the formula, is the formation factor of the core, is the core resistivity at saturation, is the resistivity of the saturated solution.

[0097] S2. Core classification steps: According to nuclear magnetic resonance The cores are classified according to the different distribution ranges of the distribution spectrum.

[0098] It should be noted that nuclear magnetic resonance The size of the distribution spectrum can characterize the pore size. The distribution spectrum morphology is obviously different, and the nuclear magnetic resonance The overall distribution spectrum is consistent. It is mainly single-peaked. The NMR of different types of cores Distribution spectrum is all about peak size and NMR There are differences in the distribution spectrum. Therefore, according to the nuclear magnetic resonance The different distribution ranges of the distribution spectrum can effectively classify the cores.

[0099] S3. Steps for constructing the classification standard: select cores of the same type according to the core classification results, calculate the fluid index of each core according to the porosity and permeability of each core, and establish the core type classification standard according to the fluid index.

[0100] Specifically, in one embodiment of the present application, the fluid index of the core is calculated by a fluid index calculation formula according to the porosity and permeability of the core;

[0101]

[0102] In the formula, is the fluid index of the core, is the permeability of the core, is the porosity of the core.

[0103] By comprehensively calculating the fluid index from porosity and permeability and constructing a classification criterion for multi-parameter coupling, the classification deviation problem caused by traditional methods relying only on porosity or permeability is solved.

[0104] It should be noted that for cores of the same type, their values are concentrated within a certain range. The larger the value, the better the porosity structure of the reservoir, the larger proportion of larger connected pores, and the better the pore-throat relationship. Statistically determine the upper and lower limits of the values for cores of the same type, and the interval distribution of values for different types of cores, and the cores can be divided into different types. For example: Class I cores, Class II cores, Class III cores. Among them, Class I cores correspond to higher values, have higher permeability, good core permeability, and better porosity structure; Class II cores correspond to medium values, between Class I cores and Class III cores, and the physical properties of the cores are medium; Class III cores correspond to lower

[0105] S4. Steps for determining petrophysical parameters: For cores of the same type, establish the fitting relationships between the resistivity increase factor and water saturation, and between the formation factor and porosity, and obtain the corresponding petrophysical parameters for cores of the same type according to the fitting relationships.

[0106] Specifically, in an embodiment of the present application, the fitting relationship between the resistivity increase factor and water saturation is expressed as:

[0107]

[0108] In the formula, is the resistivity increase factor of the core, is the lithology parameter, is the water saturation of the core, is the saturation index;

[0109] Specifically, in an embodiment of the present application, the fitting relationship between the formation factor and porosity:

[0110]

[0111] In the formula, is the formation factor of the core, is the lithology parameter, is the porosity of the core, is the cementation exponent.

[0112] It should be noted that based on the core experiment results, the fitting relationships between the resistivity increase factor and the water saturation of different types of cores, and between the formation factor and the porosity are established, and the correlation coefficients are significantly improved, which can better reflect the saturation of reservoirs with different pore-permeability relationships.

[0113] S5. Steps for determining the reservoir type: Calculate the porosity of the target reservoir according to the logging curve data of the target reservoir, calculate the permeability of the target reservoir according to the porosity of the target reservoir, calculate the fluid index of the target reservoir according to the porosity and permeability of the target reservoir, and determine the type of the target reservoir based on the fluid index and the core type classification standard.

[0114] Specifically, in an embodiment of the present application, referring to Figure 3 , the method for calculating the porosity of the target reservoir according to the logging curve data of the target reservoir is as follows:

[0115] S511. Calculate the relative value of natural gamma;

[0116]

[0117] In the formula, is the relative value of natural gamma; is the natural gamma logging value of the target layer, unit: API; is the natural gamma logging value of the pure lithology formation, unit: API; is the natural gamma logging value of the pure shale formation, unit: API.

[0118] S512. Calculate the shale content of the reservoir according to the relative value of natural gamma;

[0119]

[0120] In the formula, is the shale content of the reservoir, is the empirical coefficient related to the formation age. When the target reservoir is a new formation (i.e., Neogene, Recent), take = 3.7. When the target reservoir is an old formation, take = 2.0.

[0121] S513. Calculate the density porosity after shale correction and the neutron porosity after shale correction respectively according to the shale content of the reservoir;

[0122]

[0123]

[0124] Wherein, is the density porosity after shale correction, unit: decimal; is the neutron porosity after shale correction, unit: decimal; is the density value of the rock skeleton, unit: g / cm 3 ; is the density value of the formation fluid, unit: g / cm 3 ; is the density value of the shale, unit: g / cm 3 ; is the density log value of the target layer, unit: g / cm 3 ; is the neutron value of the rock skeleton, unit: %; is the neutron value of the formation fluid, unit: %; is the neutron value of the shale, unit: %; is the neutron log value of the target layer, unit: %; is the shale content of the reservoir, unit: decimal;

[0125] S514. Calculate the porosity of the target reservoir according to the density porosity after shale correction and the neutron porosity after shale correction;

[0126]

[0127] Wherein, is the porosity of the target reservoir.

[0128] It should be noted that due to the characteristics of high formation water salinity, high shale content, and sand-shale heterogeneity in the ultra-shallow unconsolidated reservoir in the sea area, neutron and density logging are not affected by the shale distribution and compaction degree, but are sensitive to the influence of shale. Therefore, the neutron-density crossplot method is used to calculate the porosity of the target reservoir. During the calculation process of the porosity of the target reservoir, shale correction is carried out simultaneously, and the calculated porosity of the target reservoir has high accuracy.

[0129] Specifically, in an embodiment of the present application, referring to Figure 4 , the method for calculating the permeability of the target reservoir according to the porosity of the target reservoir is as follows:

[0130] S521. Establish a porosity-permeability fitting relationship according to the porosity and permeability of the artificial core in the data acquisition step;

[0131] S522. Calculate the permeability of the target reservoir through the porosity-permeability fitting relationship according to the porosity of the target reservoir.

[0132] S6. Saturation calculation step: Determine the petrophysical parameters corresponding to the target reservoir according to the reservoir type to which the target reservoir belongs, and calculate the water saturation of the target reservoir according to the petrophysical parameters of the target reservoir.

[0133] Specifically, in an embodiment of the present application, the water saturation of the target reservoir is calculated by the Archie formula based on the determined petrophysical parameters.

[0134]

[0135] In the formula, is the water saturation of the target reservoir, is the lithology parameter, is the cementation exponent, is the saturation exponent, is the porosity of the target reservoir, is the formation water resistivity, is the resistivity log value of the target reservoir.

[0136] Based on the clear difference in pore permeability types of different reservoirs leading to complex petrophysical relationships, the above-mentioned method for classifying, interpreting and evaluating the fluid saturation of ultra-shallow unconsolidated reservoirs in the sea area of the present invention constructs a classification standard for core types according to the core type classification results, and reconstructs the fitting relationships between the resistivity increase factor and the water saturation, and between the formation factor and the porosity of the target layer. According to the fitting relationships, the petrophysical parameters corresponding to different core types are obtained, the classification indicators are quantified, and the standards are unified, realizing the fine evaluation of the fluid saturation of ultra-shallow unconsolidated reservoirs in the sea area, which has important guiding significance for the fine calculation of the saturation of ultra-shallow unconsolidated reservoirs in the sea area and the subsequent reserve general survey.

[0137] Referring to Figure 5 , in the second aspect embodiment of the present invention, a system for classifying, interpreting and evaluating the fluid saturation of ultra-shallow unconsolidated reservoirs in the sea area is provided, which is used to implement the method for classifying, interpreting and evaluating the fluid saturation of ultra-shallow unconsolidated reservoirs in the sea area described in the first aspect of the present invention, and includes:

[0138] A data acquisition module 1, which is used to acquire the results of artificial core rock physics experiments and the logging curve data of the target reservoir that conform to the characteristics of ultra-shallow unconsolidated reservoirs in the sea area;

[0139] A core classification module 2, which classifies the cores according to different intervals of the nuclear magnetic resonance distribution spectrum;

[0140] A classification standard construction module 3, which screens the cores that conform to the same type according to the core classification results, calculates the fluid index of each core according to the porosity and permeability of each core, and establishes a core type classification standard based on the fluid index;

[0141] A petrophysical parameter determination module 4, which establishes the fitting relationships between the resistivity increase factor and the water saturation, and between the formation factor and the porosity of the target layer for the cores of the same type, and obtains the petrophysical parameters corresponding to the cores of the same type according to the fitting relationships;

[0142] The reservoir type determination 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 and permeability of the target reservoir, and determines the type of the target reservoir based on the core type classification standard according to the fluid index;

[0143] The saturation calculation module 6 calculates the water saturation of the target reservoir according to the determined rock-electric parameters.

[0144] Based on the understanding that the complexity of the rock-electric relationship is caused by the differences in the pore-permeability types of different reservoirs, the above-mentioned fluid saturation classification interpretation and evaluation system for ultra-shallow unconsolidated reservoirs in the sea area of the present invention constructs a core type classification standard according to the core type classification results, and reconstructs the fitting relationships between the resistivity increase factor and the water saturation, and between the formation factor and the porosity of the target layer. According to the fitting relationships, the rock-electric parameters corresponding to different core types are obtained, the classification indicators are quantified, and the standards are unified, realizing the fine evaluation of the fluid saturation of ultra-shallow unconsolidated reservoirs in the sea area, which has important guiding significance for the fine calculation of the saturation of ultra-shallow unconsolidated reservoirs in the sea area and the subsequent reserve general survey.

[0145] To verify the effectiveness of the above-mentioned fluid saturation classification interpretation and evaluation method and system for ultra-shallow unconsolidated reservoirs in the sea area of the present invention, the following specific embodiments are described for illustration.

[0146] Embodiment: The target reservoir is the Ledong Formation in the Lingshui 36-1 block of the ultra-deep and ultra-shallow water area in the Qiongdongnan Basin.

[0147] S1. According to the statistical analysis results of the Lingshui 36-1 block in the ultra-deep and ultra-shallow water area of the Qiongdongnan Basin, a batch of plug core samples were prepared to simulate the petrophysical characteristics of extra-high pore-permeability of unconsolidated and extremely fine-grained sediments in the shallow sea. Its characteristic parameters conform to the characteristics of high formation water salinity, high shale content, and sand-shale heterogeneity of ultra-shallow unconsolidated natural gas-bearing reservoirs in the sea area. According to the national standards of the People's Republic of China, "Method for Determining Porosity and Permeability of Rocks under Overburden Pressure" SY / T6385-2016 and "Laboratory Measurement and Calculation Method for Rock Resistivity Parameters" SY / T 5385-2007, experimental research was carried out. At a designed temperature of 18°C, the porosity and permeability of 120 artificial cores were measured, as Figure 6 shown. Using a saturated solution with a salinity of 35000 ppm, the cores were saturated with a vacuum-pressurized saturation device. Under formation conditions, an array-type capillary pressure resistivity joint measurement system was used to measure the resistivity of the cores under different water saturation conditions, obtaining the water saturation, resistivity increase factor, and formation factor. The porosity-formation factor and water saturation-resistivity increase factor were fitted, and a power function relationship was established to determine the rock-electric parameters 、 、 , , such as Figure 7 and Figure 8 shown. Obtain

[0148] The relationship between the resistivity increase factor and the water saturation:

[0149] The relationship between the formation factor and the porosity:

[0150] The rock nuclear magnetic resonance experiment measures the nuclear magnetic resonance signals of the hydrogen nuclei in the pore fluid of the plug rock sample, and determines the transverse relaxation time distribution, which is closely related to the change of signal intensity and pore structure, providing an important basis for evaluating the pore structure of the rock. Due to the relatively high porosity of the core and the wide distribution of the size of the void space in the rock sample, in order to prevent signal loss and maintain the stability of the instrument during the test, a MicroMR02-040V nuclear magnetic resonance imaging system is used, and the echo spacing time is set to 0.3 ms, the number of echo trains collected NECH is 15,000, the waiting time is 5000 ms, and the number of scans is 16 times. The nuclear magnetic resonance distribution spectra of 120 cores are as shown in Figure 9 .

[0151] S2. According to the core experiment results in step S1, based on the nuclear magnetic resonance distribution spectrum, the cores are classified according to the different intervals of the nuclear magnetic resonance distribution spectrum. From the perspective of the distribution range of the nuclear magnetic resonance distribution spectrum, the main distribution range of type I samples is 100 - 300 ms, and the peak is mainly concentrated around 150 ms; the main distribution range of type II samples is 30 - 100 ms, and the peak is mainly concentrated around 50 ms; the main distribution range of type III samples is 6 - 30 ms, and the peak is mainly concentrated around 20 ms. The core classification results are as shown in Figure 10 .

[0152] S3. Screen the cores that meet the same type according to the core classification results, calculate the fluid index of each core according to the porosity and permeability of each core, and establish the core type classification standard according to the fluid index.

[0153] For the cores corresponding to the same type, their values are concentrated in a certain range, statistically determine the upper and lower limits of the values of the cores of the same type, and the interval distribution of the values of the cores of different types. Type I cores correspond to relatively high values, ≥15, with relatively high permeability, good core seepage ability, and relatively good porosity structure; Class II cores correspond to medium values, 15 > > 12, between Class I and Class III, with medium core physical properties; Class III cores correspond to lower FI values, 12 ≤ , with relatively low permeability, generally relatively high shale content, and poor pore connectivity.

[0154] S4. According to the three-category classification results, all 120 cores are classified, also divided into corresponding Class I, II, and III categories, and the resistivity increase factor and water saturation relationship is re-established. Its correlation coefficient becomes significantly better, and it can better reflect the relationship between the resistivity increase factor and water saturation . As Figure 11 shown, after classification, it is as follows:

[0155] Class I:

[0156] Class II:

[0157] Class III:

[0158] The relationship between the formation factor and porosity is re-established. Its correlation coefficient becomes significantly better, and it can better reflect the relationship between the formation factor and porosity . As Figure 12 shown, after classification, it is as follows:

[0159] Class I:

[0160] Class II:

[0161] Class III:

[0162] After classifying the cores, the correlation relationship among resistivity, saturation, and porosity becomes better. Based on the above analysis results, the classification criteria for different types and the selected rock electrical parameters are shown in Table 1.

[0163] Table 1

[0164]

[0165] S5. Calculate the porosity of the target reservoir based on the logging curve data of the target reservoir, calculate the permeability of the target reservoir based on the porosity of the target reservoir, calculate the fluid index of the target reservoir based on the porosity and permeability of the target reservoir, and determine the type of the target reservoir according to the fluid index based on the core type classification standard.

[0166] In this embodiment, the ultra-shallow unconsolidated gas-bearing reservoir in the Lingshui 36-1 block has the characteristics of high formation water salinity, high shale content, and sand-shale heterogeneity. Neutron and density logging are not affected by the shale distribution and compaction degree, but are sensitive to the influence of shale. Therefore, the neutron-density crossplot method is used to calculate the porosity of the target reservoir, and corresponding shale corrections are carried out.

[0167] When calculating the porosity of the target reservoir, since the ultra-shallow unconsolidated gas-bearing reservoir in the Lingshui 36-1 block in this embodiment is a new reservoir, take = 3.7.

[0168] Use the core porosity-permeability fitting formula to calculate the reservoir permeability. According to the porosity and permeability parameters measured from the artificial cores that conform to the characteristics of the ultra-shallow unconsolidated gas-bearing reservoir in the sea area in step S1, establish a porosity-permeability relationship curve, and calculate the formation permeability based on the fitting curve. The permeability is obtained according to the porosity-permeability relationship fitting formula.

[0169]

[0170] Specifically, the calculated parameters such as porosity and permeability and the classification results of Well X1 in the Lingshui 36-1 block are shown in Figure 13. The first track in the figure is the depth track. The ultra-shallow unconsolidated gas-bearing reservoir in the sea area is usually within 500 m below the seabed, and the depth in the figure is the sea level depth; the second track is the natural GR curve; the third track is the deep and shallow resistivity curves; the fourth track is the neutron porosity logging curve and density porosity logging curve; the fifth track is the permeability curve calculated according to the porosity-permeability relationship fitting formula; the sixth track is the porosity curve and lithology profile curve calculated according to the target reservoir porosity calculation formula; the seventh track is the different reservoir types obtained by calculation and classification.

[0171] S6. Calculate the gas saturation of this type of reservoir by combining the Archie formula based on the reservoir classification results and petrophysical parameters in step S5.

[0172] Specifically, according to the Waxman-Smits model, the conductivity of shaly sandstone is regarded as the result of the combined action of the conduction of free formation water in the rock pores and the conduction of cation exchange related to clay. Under the condition of low salinity equilibrium solution, the formation conductivity will be affected by both shale and formation water at the same time, and the conductivity of shaly sandstone shows non-linearity. When the solution salinity exceeds 20,200 ppm, the cation exchange mobility will reach a constant (maximum value), the conductivity of formation water increases, the proportion of additional conductive contribution of shale decreases, and the conductivity of shaly sandstone shows linearity and is parallel to the pure sandstone line. At this time, Archie's formula is still applicable to shaly sandstone reservoirs. According to the analysis and test data of the target layer water in the Lingshui 36-1 block, the salinity of the formation water in the ultra-shallow unconsolidated gas-bearing reservoir in the South China Sea is 35,000 ppm. Therefore, Archie's formula can be used for saturation evaluation.

[0173] Specifically, the petrophysical parameters determined according to the porosity-formation factor and water saturation-resistivity increase factor relationships obtained from the experiments in step S1 = 1.0, = 1.0, = 1.51, = 2.17. The Archie formula and Simandoux formula with unified parameters are respectively used to calculate the saturation of the entire well section of Well X1, and the calculation results are as Figure 14 shown. The first to sixth traces in the figure are consistent with Figure 9 those, and the seventh trace is the water saturation curve of the entire well section of Well X1 calculated by using the petrophysical parameters obtained by the Simandoux formula, Archie formula, and sealed coring; the eighth trace is the logging interpretation conclusion.

[0174] The calculation results show that the petrophysical parameters determined based on the experimental results of artificial rock samples: m = 1.511, n = 2.17, have a greater impact on heterogeneous sand-shale reservoirs. For low-resistivity reservoir sections, the traditional Archie formula calculates a relatively high water saturation; although the Simandoux formula can eliminate the influence of additional conductive effect of shale on formation resistivity to a certain extent through shale correction, in the actual application process, due to reasons such as model assumptions and parameter selection, the accuracy of saturation calculation is limited: on the one hand, the Simandoux formula assumes that shale contains oil, gas, and water like pure sandstone, regards the pore-bound water as free water, and subtracts this part of water after shale correction, resulting in a relatively low calculated water saturation; on the other hand, the petrophysical parameters often use empirical values or values directly obtained from petrophysical experiments, rather than petrophysical parameter values that have eliminated the influence of shale conductivity.

[0175] Specifically, the saturation calculation results of Well X1 are as Figure 15 shown. The first to seventh traces in the figure are consistent with Figure 14Consistent, the eighth trace is the water saturation curve calculated by the method and system of the present application and the saturation curve calculated from the experimental results obtained by sealed coring; the ninth trace is the difference between the results of the two saturation calculation methods; the tenth trace is the logging interpretation conclusion. By comparing the calculation results of different reservoir sections, it can be obtained that compared with the sealed coring results, the calculated water saturation of Class I reservoirs is lower, the calculated water saturation of Class II reservoirs is comparable to it, and the calculated water saturation of Class III reservoirs is higher. The method and system of the present application improve the gas saturation of Class I high-quality reservoirs and reduce the saturation of Class III relatively low-quality reservoirs. Comparing the saturation calculation results with the actual formation test results, Class I reservoirs have the best pore-permeability relationship, better pore connectivity, are easy to be filled with gas, and have higher gas saturation. The method and system of the present application achieve a fine interpretation and evaluation of the gas saturation of ultra-shallow unconsolidated reservoirs in the sea area by finely classifying the reservoirs, obtaining the rock-electric parameters of different reservoir types, and calculating the saturation based on Archie's formula.

[0176] The above embodiments are used to explain the present invention rather than limit the present invention. Any modifications and changes made to the present invention within the spirit and scope of the claims of the present invention fall within the protection scope of the present invention.

Claims

1. A classification interpretation and evaluation method for fluid saturation in ultra-shallow unconsolidated reservoirs in the sea area, characterized in that, The steps are as follows: Data acquisition steps: Obtain the petrophysical experimental results of artificial cores and the logging curve data of the target reservoir that conform to the characteristics of the ultra-shallow unconsolidated target reservoir in the sea area; the experimental results include nuclear magnetic resonance distribution spectrum, porosity, permeability, water saturation, resistivity increase factor, formation factor; Core classification steps: Classify cores according to the different intervals of the nuclear magnetic resonance distribution spectrum; Steps for constructing classification criteria: Screen cores that meet the same type according to the core classification results, calculate the fluid index of each core based on the porosity and permeability of each core, and establish the core type classification criteria according to the fluid index; calculate the fluid index of the core through the fluid index calculation formula based on the porosity and permeability of the core. In the formula, is the fluid index of the core, is the permeability of the core, is the porosity of the core; Steps for determining petrophysical parameters: For cores of the same type, establish the fitting relationships between the resistivity increase factor and the water saturation, and between the formation factor and the porosity, and obtain the corresponding petrophysical parameters for cores of the same type according to the fitting relationships. Steps for determining reservoir type: Calculate the porosity of the target reservoir according to the logging curve data of the target reservoir, calculate the permeability of the target reservoir according to the porosity of the target reservoir, calculate the fluid index of the target reservoir according to the porosity and permeability of the target reservoir, and determine the type of the target reservoir based on the core type classification criteria according to the fluid index. Steps for calculating saturation: Determine the petrophysical parameters corresponding to the target reservoir according to the reservoir type to which the target reservoir belongs, and calculate the water saturation of the target reservoir according to the petrophysical parameters of the target reservoir.

2. The method for classifying, interpreting and evaluating the fluid saturation of ultra-shallow unconsolidated reservoirs in the sea area according to claim 1, wherein, In the data acquisition step, the method for obtaining the petrophysical experiment results of artificial cores with the characteristics of ultra-shallow unconsolidated target reservoirs in the sea area is as follows: Fabricate artificial cores that conform to the characteristics of ultra-shallow unconsolidated target reservoirs in the sea area. Measure the porosity and permeability of the artificial cores under the set temperature conditions. Saturate the artificial cores with brine of the set salinity. Put the saturated artificial core into a nuclear magnetic resonance imaging system. After setting the echo spacing time, waiting time, number of acquired echo trains, and number of scans, measure the nuclear magnetic resonance distribution spectrum; Under formation conditions, measure the core resistivity and water saturation under different water saturation conditions through displacement experiments, and calculate the resistivity increase factor and formation factor according to the core resistivity.

3. The method for classifying, interpreting and evaluating the fluid saturation of ultra-shallow unconsolidated reservoirs in the sea area according to claim 2, wherein, Calculate the resistivity increase factor according to the core resistivity through the resistivity increase factor calculation formula. In the formula, is the resistivity increase factor of the core, is the resistivity of the core after displacement, is the resistivity of the core at saturation.

4. The method for classifying, interpreting and evaluating the fluid saturation of ultra-shallow unconsolidated reservoirs in the sea area according to claim 2, wherein, Calculate the formation factor according to the core resistivity through the formation factor calculation formula. Wherein, is the formation factor of the core, is the resistivity of the core when saturated, is the resistivity of the saturated solution.

5. The method for classifying, interpreting and evaluating the fluid saturation of ultra-shallow unconsolidated reservoirs in the sea area according to claim 1, wherein In the step of determining the petrophysical parameters, the fitting relationship between the resistivity increase factor and the water saturation is expressed as: In the formula, is the resistivity increase factor of the core, is the lithology parameter, is the water saturation of the core, is the saturation index; The fitting relationship between the formation factor and the porosity is expressed as: Wherein, is the formation factor of the core, is the lithology parameter, is the porosity of the core, is the cementation exponent.

6. The method for classifying, interpreting and evaluating the fluid saturation of ultra-shallow unconsolidated reservoirs in the sea area according to claim 1, wherein In the step of determining the reservoir type, the method for calculating the porosity of the target reservoir according to the logging curve data of the target reservoir is as follows: Calculate the relative value of natural gamma. Wherein, is the relative value of natural gamma; is the natural gamma log value of the target layer, unit: API; is the natural gamma log value of the pure lithologic formation, unit: API; is the natural gamma log value of the pure shale formation, unit: API; Calculate the shale content of the reservoir according to the relative value of natural gamma. In the formula, is the shale content of the reservoir, is the empirical coefficient related to the formation age; Calculate the density porosity after shale correction and the neutron porosity after shale correction respectively according to the shale content of the reservoir. Wherein, is the density porosity after shale correction, unit: decimal; is the neutron porosity after shale correction, unit: decimal; is the density value of the rock matrix, unit: g / cm 3 ; is the density value of the formation fluid, unit: g / cm 3 ; is the density value of the shale, unit: g / cm 3 ; is the density log value of the target layer, unit: g / cm 3 ; is the neutron value of the rock matrix, unit: %; is the neutron value of the formation fluid, unit: %; is the neutron value of the shale, unit: %; is the neutron log value of the target layer, unit: %; is the shale content of the reservoir, unit: decimal; Calculate the porosity of the target reservoir according to the density porosity after shale correction and the neutron porosity after shale correction. In the formula, is the porosity of the target reservoir.

7. The method for classifying, interpreting and evaluating the fluid saturation of ultra-shallow unconsolidated reservoirs in the sea area as described in claim 1, characterized in that In the step of determining the reservoir type, the method for calculating the permeability of the target reservoir according to the porosity of the target reservoir is as follows: Establish the porosity-permeability fitting relationship according to the porosity and permeability of the artificial cores in the data acquisition step. Calculate the permeability of the target reservoir according to the porosity of the target reservoir through the porosity-permeability fitting relationship.

8. The method for classifying, interpreting and evaluating the fluid saturation of ultra-shallow unconsolidated reservoirs in the sea area according to claim 1, wherein In the step of calculating the saturation, calculate the water saturation of the target reservoir through Archie's formula according to the determined petrophysical parameters. Wherein, is the water saturation of the target reservoir, is the lithology parameter, is the cementation exponent, is the saturation exponent, is the porosity of the target reservoir, is the resistivity of formation water, is the resistivity log value of the target reservoir.

9. A classification interpretation and evaluation system for fluid saturation in ultra-shallow unconsolidated reservoirs in the sea area, which is used to implement the classification interpretation and evaluation method for fluid saturation in ultra-shallow unconsolidated reservoirs in the sea area described in any one of claims 1 to 8, characterized in that, It includes: A data acquisition module for obtaining the petrophysical experiment results of artificial cores with the characteristics of ultra-shallow unconsolidated target reservoirs in the sea area and the logging curve data of the target reservoir. Core classification module, classifying cores according to different intervals of the nuclear magnetic resonance distribution spectrum; The division standard construction module screens cores that meet the same type according to the core classification results, calculates the fluid index of each core based on the porosity and permeability of each core, and establishes the core type division standard according to the fluid index; The petrophysical parameter determination module establishes the fitting relationships between the resistivity increase factor and the water saturation, and between the formation factor and the porosity of the target layer for cores of the same type, and obtains the petrophysical parameters corresponding to cores of the same type according to the fitting relationships; The reservoir type determination module 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 and permeability of the target reservoir, and determines the type of the target reservoir based on the core type division standard according to the fluid index; The saturation calculation module determines the petrophysical parameters corresponding to the target reservoir according to the reservoir type to which the target reservoir belongs, and calculates the water saturation of the target reservoir according to the petrophysical parameters of the target reservoir.

Images