A quantitative prediction method for favorable areas of clastic rock dissolution

Abstract

The present invention relates to a quantitative prediction method for favorable areas for clastic rock dissolution, including: source-sink coupled ore determination analysis, reservoir research causal analysis and thermal / dynamic positioning. The types and distribution of soluble minerals are obtained through source-sink coupled ore determination analysis, the formation mechanism of favorable reservoirs is obtained through reservoir research causal analysis, and the distribution of thermal / dynamic parameters is obtained through thermal / dynamic positioning, wherein the thermal / dynamic positioning includes: thermodynamic positioning of soluble minerals, temperature-pressure field analysis, prediction of soluble areas, soluble mineral dynamics, organic acid excretion concentration and prediction of favorable areas for dissolution. The plane distribution of favorable reservoirs is predicted based on the obtained types and distribution of soluble minerals, favorable reservoir formation mechanism and thermal / dynamic parameter distribution. The method can more effectively predict favorable areas for dissolution and improve exploration efficiency.

Description

Technical Field

[0001] The invention relates to the technical field of reservoir prediction, and in particular to a method for quantitatively predicting favorable areas of clastic rock dissolution based on thermal / dynamic analysis. Background Art

[0002] Traditionally, favorable reservoir prediction is a qualitative method, which is based on sedimentary phase, rock phase, diagenetic phase and the temperature and pressure field of the reservoir to qualitatively evaluate the quality of the reservoir, and cannot effectively predict the favorable area for dissolution. Therefore, this patent conducts quantitative prediction for deep favorable reservoirs dominated by dissolution pores. Summary of the invention

[0003] In view of the above problems, the purpose of the present invention is to try to use a quantitative-semi-quantitative method to predict the distribution of deep favorable reservoirs. That is, the three-step approach of "source determination-cause determination-positioning" is adopted. First, the source is determined by quantitative coupling of source-channel-sink to clarify the provenance area and parent rock type; secondly, reservoir research is used to determine the cause, determine the type of soluble minerals, divide the diagenetic stage and diagenetic phase, and determine the diagenetic reservoir mechanism; finally, a thermal / kinetic method is used to first determine the solubility range of soluble minerals by calculating thermodynamic parameters, and then predict the planar distribution of soluble areas of different minerals by combining the fitting relationship between measured physical properties and thermodynamic parameters; then the kinetic parameters of soluble minerals are calculated, that is, the dissolution rate reflects the area with the fastest dissolution rate of soluble minerals, and finally the prediction of Class I and Class II favorable dissolution areas is achieved. Through the study of a certain target in the Bohai Sea area, very good results have been achieved.

[0004] To achieve the above object, the present invention adopts the following technical solutions:

[0005] A quantitative prediction method for favorable areas of clastic rock dissolution, comprising:

[0006] Source-sink coupling ore determination analysis to obtain the types and distribution of soluble minerals. Source-sink coupling ore determination analysis includes: source area lithology identification, transportation channel analysis, sedimentary facies characterization and source-channel-sink quantitative coupling;

[0007] Reservoir research and causal analysis to obtain favorable reservoir formation mechanisms, including petrological characteristics analysis, physical property characteristics analysis, authigenic mineral characteristics analysis, inclusion temperature measurement, diagenesis analysis, pore evolution characteristics and reservoir formation mechanism analysis;

[0008] Thermal / dynamic positioning to obtain the distribution of thermal / dynamic parameters, including: thermodynamic positioning of soluble minerals, temperature and pressure field analysis, prediction of soluble areas, soluble mineral dynamics, organic acid concentration and prediction of favorable dissolution areas;

[0009] The plane distribution of favorable reservoirs is predicted based on the obtained soluble mineral types and distribution, favorable reservoir formation mechanism and thermal / dynamic parameter distribution.

[0010] Source area lithology identification includes:

[0011] Determine the provenance of the target layer in the study area. The provenance includes regional provenance outside the basin and local provenance within the basin. From the perspectives of tectonic evolution, sedimentary filling, etc., combined with the characteristics of light and heavy minerals, petrological characteristics, common and trace elements, etc., conduct research to determine the direction and location of the provenance area;

[0012] The identification of parent rock lithology is divided into the following steps: identification of present bedrock, that is, through the basement lithology encountered in drilling in the provenance area, the lithology is identified by using core and thin section identification, logging and other data, and through well-seismic calibration, the seismic reflection characteristics of different bedrock lithologies are summarized, and the seismic reflection characteristics are used to identify and characterize the lithology type and distribution of the bedrock in the provenance area; restoration of the parent rock area, using the stratigraphic analysis method to restore the amount of erosion and reconstruct the paleo-geomorphology of the study area before erosion, and then determine the provenance area, transportation channel area, and sedimentary area according to the paleo-geomorphology characteristics and stratigraphic contacts of the target layer; water system analysis, on the basis of paleo-geomorphology analysis, the main watershed and secondary watershed are calibrated respectively, and paleo-water systems of different levels are divided.

[0013] Transport channel analysis includes: analysis of transport distance and transport channel type.

[0014] Sedimentary facies characterization includes:

[0015] Conduct horizon tracing and establish a detailed sequence stratigraphic framework for the target layer;

[0016] Make stratigraphic slices, restore micro-paleomorphology, divide microfacies or complex lobes as sedimentary units based on drilling characteristics, and carry out detailed sedimentary unit carving of the target layer;

[0017] Analyze the spatial distribution and evolution laws of different secondary sedimentary units.

[0018] The reservoir formation mechanism analysis includes, based on the judgment of soluble mineral types, fluid types and diagenetic history, analyzing the key diagenetic reservoir formation mechanism according to the following relationship:

[0019]

[0020] in:

[0021] a, b, c, and d represent reaction coefficients;

[0022] A and B are reactants;

[0023] C and D are products.

[0024] Thermodynamic analysis of soluble minerals includes calculating the thermodynamic parameters of each reactant and product of the diagenetic and reservoir mechanism equation, then adding the Gibbs free energy of all products and subtracting the Gibbs free energy of all reactants to obtain the Gibbs free energy increment △G. When △G is less than 0, it indicates that the reaction is a spontaneous process; when △G is smaller, the dissolution reaction is easier to proceed. The △G of the dissolution reaction of soluble minerals is calculated. The △G of each soluble mineral at different temperatures T and pressures P is calculated according to the following relationship:

[0025] AG(T,P)=ΔG 0 (T,P)+RTlnQ a (2)

[0026] in:

[0027] △G is the Gibbs free energy increment;

[0028] △G 0 is the Gibbs free energy under standard conditions;

[0029] T is the temperature in Kelvin;

[0030] P is pressure;

[0031] Q a For the activity quotient.

[0032] The prediction of soluble zones is based on the fitting of the physical properties of the target layers in the study area and surrounding areas with △G to obtain the relationship between the physical properties and △G. The lower limit of the physical properties of the favorable reservoir is selected to select the corresponding △G, which is set as the lower limit of the favorable reservoir corresponding to the soluble mineral. With this △G as the boundary, the soluble zone of each soluble mineral is drawn. The soluble zone of each soluble mineral is then superimposed with the dominant phase of the sedimentary phase to obtain the soluble zone of the study area.

[0033] The kinetic analysis of soluble minerals includes: introducing the dissolution rate for analysis. The dissolution rate r is a parameter related to temperature T and pH value, and is calculated by the following relationship:

[0034]

[0035] Where:

[0036] r is the dissolution rate;

[0037] k is the rate constant related to temperature;

[0038] A is the reactive surface area per kilogram of water;

[0039] is the hydrogen ion activity;

[0040] ΔG 0is the Gibbs free energy increment of the reaction;

[0041] The exponents μ and v are two dimensionless empirical constants;

[0042] R is the gas constant.

[0043] Calculate k according to the following relationship:

[0044]

[0045] in:

[0046] k 25 is the reaction rate at 25°C;

[0047] Ea is the activation energy, unit is KJ / mol.

[0048] The analysis of organic acid expulsion concentration includes using the organic acid expulsion concentration in the burial diagenesis stage to characterize the pH value, that is, the greater the organic acid expulsion concentration, the smaller the pH value, and the faster the dissolution rate. According to the drainage thickness of the source rock in the target layer of the study area and the parameters of the organic acid expulsion experiment, the plane organic acid expulsion concentration is calculated according to the following relationship:

[0049]

[0050] in:

[0051] is the average organic acid concentration in the formation water discharged from a certain calculation unit formation;

[0052] H is the thickness of the mudstone formation in a certain calculation unit;

[0053] S is the area of ​​a certain computing unit;

[0054] C 有机 is the organic carbon content of a certain calculation unit;

[0055] Q 排酸 It is the average organic acid discharge per unit organic carbon in a certain calculation unit stratum;

[0056] ρ 岩 is the rock density of a certain calculation unit formation;

[0057] H 排水 is the discharge water height (m).

[0058] The present invention adopts the above technical solution, which has the following advantages:

[0059] The present invention first studies the source and sink, then analyzes the reservoir diagenesis mechanism, and then analyzes the thermal / dynamic analysis of soluble minerals, points out the soluble area of ​​each soluble mineral, and then divides the comprehensive soluble area in combination with the sedimentary phase plane distribution map; and further divides the favorable area for dissolution using the results of the dynamic analysis. This step can be used to predict the clastic reservoir from a quantitative and operational perspective. It is a relatively feasible technical method, which has a certain guiding significance for the exploration of areas with few wells, increases the exploration results, and saves costs. Studies have shown that this method can effectively predict the favorable area for dissolution and improve exploration efficiency. BRIEF DESCRIPTION OF THE DRAWINGS

[0060] Various other advantages and benefits will become apparent to those of ordinary skill in the art by reading the detailed description of the preferred embodiments below. The accompanying drawings are only for the purpose of illustrating the preferred embodiments and are not to be considered as limiting the present invention. Throughout the accompanying drawings, the same reference numerals are used to represent the same components. In the accompanying drawings:

[0061] Figure 1 It is a general framework for quantitative prediction of favorable areas for clastic rock dissolution based on thermal / dynamic analysis;

[0062] Figure 2 It is a quantitative coupling analysis diagram of “source, channel and sink”;

[0063] Figure 3 It is the relationship diagram between △G of soluble minerals and temperature T and pressure P;

[0064] Figure 4 is the △G distribution diagram of Gibbs free energy of potassium feldspar;

[0065] Figure 5 is the distribution diagram of Gibbs free energy △G of albite;

[0066] Figure 6 is the dolomite Gibbs free energy △G distribution diagram;

[0067] Figure 7 It is the soluble zone where the soluble mineral △G overlaps with the dominant phase;

[0068] Figure 8 It is the relationship diagram between the dissolution rate r of soluble minerals and temperature T and pH value;

[0069] Fig. 9 It is the planar distribution diagram of organic matter acid excretion;

[0070] Fig.10 It is the quantitative prediction result map of the favorable dissolution area;

[0071] Fig.11 It is to verify the physical characteristics of the well. DETAILED DESCRIPTION

[0072] The exemplary embodiments of the present invention will be described in more detail below with reference to the accompanying drawings. Although the exemplary embodiments of the present invention are shown in the accompanying drawings, it should be understood that the present invention can be implemented in various forms and should not be limited by the embodiments described herein. On the contrary, these embodiments are provided in order to enable a more thorough understanding of the present invention and to fully convey the scope of the present invention to those skilled in the art.

[0073] The invention relates to a method for quantitatively predicting favorable areas for clastic rock dissolution based on thermal / dynamic analysis, belonging to the technical field of reservoir prediction, and in particular to the technical field of quantitatively predicting favorable areas for clastic rock dissolution.

[0074] like Figure 1 As shown, the present invention provides a method for quantitatively predicting favorable areas of clastic rock dissolution based on thermal / dynamic analysis, comprising the following steps:

[0075] 1) Provenance analysis: First, determine the provenance of the target layer in the study area. The provenance generally includes regional provenance outside the basin and local provenance within the basin. From the perspectives of tectonic evolution, sedimentary filling, etc., combined with the characteristics of light and heavy minerals, petrological characteristics, common and trace elements, etc., to determine the direction and location of the provenance. Secondly, carry out parent rock lithology identification, which is divided into the following steps: ① Current bedrock identification, that is, through the basement lithology encountered by drilling in the provenance area, the lithology is identified using rock (wall) core and thin section identification, logging and other data, and through well seismic calibration , summarize the seismic reflection characteristics of different bedrock lithologies, and use seismic reflection characteristics to identify and characterize the bedrock lithology types and their distribution in the source area; ② Restoration of the parent rock area, using the stratigraphic (trend) analysis method to restore the amount of denudation, reconstruct the paleo-geomorphology map of the study area before denudation, and then determine the source area, transportation channel area, and deposition area based on the paleo-geomorphological characteristics and the stratigraphic contact of the target layer (overlap point, etc.); ③ Paleo-drainage system analysis, on the basis of paleo-geomorphological analysis, respectively calibrate the main watershed and secondary watershed, and divide the different levels of paleo-drainage systems (drainage units) ( Figure 2 ).

[0076] 2) Analysis of transport channels, including transport distance, transport channel type (divided into paleo-valleys, paleo-river channels, fault grooves, structural transition zones, etc.), slope, etc. Among them, paleo-valleys are the most important source channels. Due to the different downcutting strengths and branching degrees, paleo-valleys have a variety of seismic reflection structural characteristics on seismic profiles. Generally speaking, there are two main identification marks for paleo-valleys on seismic profiles: ① External morphological identification, for example, paleo-valleys often have V-shaped, W-shaped and U-shaped downcuts, and obvious interruptions in the phase axis at the boundary; ② Internal structure identification, the interior of the paleo-valley often has an internal structure of two-way filling and two-way onlap, which is lens-shaped as a whole, and the thickness of the middle strata is greater than that of the two sides ( Figure 2 ).

[0077] 3) Sedimentary facies characterization: First, conduct stratum tracing, establish a fine sequence stratigraphic framework for the target layer, further make stratigraphic slices, restore micro-paleomorphology, divide microfacies or composite lobes as sedimentary units based on drilling characteristics, carry out fine sedimentary unit carving for the target layer, and analyze the spatial distribution and evolution laws of different secondary sedimentary units ( Figure 2 ).

[0078] 4) Quantitative coupling evaluation of source-channel-sink: quantitatively analyze the volume of various parent rock types, the scale of valley transport channels, and the scale of sedimentary bodies in different water-collecting units in the provenance area. According to the principle of material conservation, fit the erosion volume and transport channels of the provenance area and the sediment volume of the sedimentary area to further determine the reliability of the source-channel-sink. Figure 2 ).

[0079] 5) Analysis of petrological characteristics: Combined with rock (wall) core observation, the results of thin section identification are statistically analyzed to analyze the petrological type of the target layer, including skeleton minerals (quartz, feldspar and rock fragments), matrix, and the type and content of cement, sorting, roundness and other characteristics.

[0080] 6) Analysis of physical property characteristics, including planar characteristics and vertical characteristics. In the plane, the focus is on the relationship between physical properties and rock type, grain size, microfacies, hydrodynamic conditions, etc.; in the vertical direction, the focus is on the relationship between physical properties and depth to identify the layers with developed sweet spots in deep reservoirs.

[0081] 7) Analysis of the characteristics of authigenic minerals: by observing the type, occurrence, structure and content of authigenic minerals through casting thin sections, scanning electron microscopy, cathode luminescence, electron probe and other microscopic data, the formation time of authigenic minerals and their impact on reservoir properties can be determined.

[0082] 8) Inclusion temperature analysis: By measuring the temperature of brine inclusions during the same period of oil and gas filling, we can analyze the ancient temperature during oil and gas migration and filling. Combined with the burial history and temperature history analysis, we can determine the ancient temperature at the critical moment of flow rock reaction.

[0083] 9) Diagenesis analysis: According to the paleo-geothermal history, organic matter thermal evolution history (Ro) and the types, occurrence and sequence of authigenic minerals in sandstone, the diagenetic evolution characteristics are judged. Based on the reservoir physical property evolution characteristics, the diagenetic phases are divided into early compaction phase, early cementation phase, early dissolution phase, mid-term dissolution phase, mid-term cementation phase, etc., and the diagenetic phase experienced by the target layer is judged.

[0084] 10) Analysis of pore evolution characteristics: According to the burial history and diagenetic history of the sediments, on the basis of quantitative analysis of the contents of various cements and dissolution pores, the pore evolution history is quantitatively inverted using the layer stripping method.

[0085] 11) Analysis of reservoir formation mechanism: Based on the determination of soluble mineral types, fluid types and diagenetic history, key diagenetic reservoir formation mechanisms (equations) are analyzed:

[0086]

[0087] In the formula: a, b, c, d represent reaction coefficients, which are constants; A and B are reactants; C and D are products.

[0088] 12) Thermodynamic analysis of soluble minerals. Calculate the thermodynamic parameters (Gibbs free energy) of each reactant and product in the above diagenetic and reservoir mechanism equation, then add the Gibbs free energy of all products and subtract the Gibbs free energy of all reactants to get the Gibbs free energy increment △G. When △G is less than 0, it indicates that the reaction is a spontaneous process; the smaller △G is, the easier the dissolution reaction is. Then, we calculate the △G of the dissolution reaction of soluble minerals, and calculate the △G of each soluble mineral at different temperatures T and pressures P. The results show that △G changes little with pressure P and is mainly affected by temperature T ( Figure 3 ).

[0089] AG(T,p)=ΔG 0 (T,P)+RTlnQ a (2)

[0090] Where: △G is the Gibbs free energy increment; △G 0 is the Gibbs free energy under standard conditions (25°C, 1 standard atmosphere), T is the Kelvin temperature; P is the pressure; Q a For the activity quotient.

[0091] 13) Temperature and pressure field analysis: According to the measured temperature of the drilling, the temperature and depth are fitted to obtain the relationship between temperature and depth. Then the depth of the target layer interpreted by seismic is converted into temperature to obtain a plane diagram of the temperature field.

[0092] 14) Prediction of soluble zone: By fitting the physical properties of the target layer in the study area and the surrounding area with △G, we can know the relationship between the physical properties and △G. We can select the corresponding △G by selecting the lower limit of the physical properties of the favorable reservoir, which is the lower limit of the favorable reservoir corresponding to the soluble mineral. With this △G as the boundary, draw the soluble zone of each soluble mineral ( Figure 4-6 Then, the soluble zone of each soluble mineral is superimposed with the dominant phase of the sedimentary phase to obtain the soluble zone of the study area ( Figure 7 ).

[0093] 15) Kinetic analysis of soluble minerals: whether all minerals in the soluble zone can form a favorable zone depends on the dissolution rate of the soluble minerals, that is, the area with a fast dissolution rate is more likely to form a favorable zone. Therefore, the kinetic parameter (dissolution rate r) is introduced for analysis. The dissolution rate r is a parameter related to temperature T and pH value. Through calculation, it is found that the dissolution rate r of soluble minerals has little correlation with temperature and is mainly affected by pH value ( Figure 8 ).

[0094]

[0095] Where: r is the dissolution rate; k is the rate constant related to temperature (mol / m 2 / s), A is the reaction surface area per kilogram of water (cm 2 ); is the hydrogen ion activity (mol / L); ΔG 0 is the Gibbs free energy increment of the reaction (kJ / mol); the exponents μ and v are two dimensionless empirical constants (μ = 1, v = 2 (Hellevang et al., 2013; Shen et al., 2018)); R is the gas constant (8.314472 J / (mol·K)).

[0096]

[0097] Where: k 25 is the reaction rate (mol / m 2 / s).

[0098] 16) Analysis of organic matter acid excretion concentration. It is difficult for us to measure the pH value in the diagenesis stage, but we can use the organic matter acid excretion concentration in the burial diagenesis stage to characterize the pH value. That is, the greater the organic matter acid excretion concentration, the smaller the pH value and the faster the dissolution rate. Using the empirical formula of predecessors, according to the drainage thickness of the source rock in the target layer of the study area, TOC, and the parameters of the previous organic matter generation and acid excretion experiments, these parameters were substituted into the empirical formula to calculate the planar organic matter acid excretion concentration. The results show that the high-value area of ​​organic matter acid excretion concentration in the target layer of the study area is located in the middle of the study area ( Fig. 9 ).

[0099]

[0100] Where: is the average organic acid concentration in the formation water discharged from a certain calculation unit (kg / t); H is the thickness of the mudstone formation in a certain calculation unit (m); S is the area of ​​a certain calculation unit (m 2 );C 有机 is the organic carbon content of a certain calculation unit (%); Q 排酸is the average organic acid discharge per unit organic carbon in a certain calculation unit stratum (kg / t); ρ 岩 is the rock density of a certain calculation unit (t / m 3 );H 排水 is the discharge water height (m).

[0101] 17) Quantitative prediction of favorable dissolution zones. Combining thermodynamics, kinetics and phase zones, the favorable dissolution zones of the target layer are predicted. Based on the organic acid concentration (e.g. 15), the easily soluble zones are preliminarily divided into Class I and Class II favorable dissolution zones. Fig.10 ).

[0102] 18) Verification of prediction results: The prediction results need to be verified by using wells that are not involved in the dissolution favorable area and are not deep-fitted to observe the variation characteristics of their physical properties with depth. If there is a secondary dissolution zone in the target layer, it indicates that this method has good reliability ( Fig.11 ). At the same time, the paleo-geothermal temperature of the target layers of these wells is within the geothermal range corresponding to the soluble zone, which also reflects the effectiveness of this method.

[0103] A method for quantitatively predicting favorable areas for clastic rock dissolution according to an embodiment of the present application includes:

[0104] The first step is provenance analysis. First, determine the provenance area of ​​the target layer in the study area. The provenance area generally includes regional provenance outside the basin and local provenance within the basin. From the perspectives of tectonic evolution, sedimentary filling, etc., combined with the characteristics of light and heavy minerals, petrological characteristics, common and trace elements, etc., conduct research to determine the direction and location of the provenance area; secondly, carry out parent rock lithology identification, which is divided into the following steps: ① Current bedrock identification, that is, through the basement lithology encountered by drilling in the provenance area, use rock (wall) core and thin section identification, logging and other data to identify the lithology, and through well seismic markers ① Determination, summarize the seismic reflection characteristics of different bedrock lithologies, and use the seismic reflection characteristics to identify and characterize the bedrock lithology types and their distribution in the source area; ② Restoration of the parent rock area, use the stratigraphic (trend) analysis method to restore the erosion amount, reconstruct the paleo-geomorphology of the study area before erosion, and then determine the source area, transportation channel area, and depositional area according to the paleo-geomorphology characteristics and the stratigraphic contact of the target layer (overlap point, etc.); ③ Paleo-drainage system analysis, on the basis of paleo-geomorphology analysis, mark the main watershed and secondary watershed respectively, and divide the paleo-drainage systems (drainage units) of different levels.

[0105] The second step is to analyze the transport channel, including transport distance, transport channel type (divided into paleo-valley, paleo-river channel, fault trough, structural conversion zone, etc.), slope, etc. Among them, paleo-valley is the most important source channel. Due to the different downcutting strength and branching degree, paleo-valley has a variety of seismic reflection structure characteristics on the seismic profile. Generally speaking, there are two main identification marks of paleo-valley on the seismic profile: ① external morphological identification, for example, paleo-valleys often have V-shaped, W-shaped and U-shaped downcuts, and the phase axis at the boundary has obvious interruption; ② internal structure identification, the interior of the paleo-valley often has an internal structure of two-way filling and two-way overburden, which is lens-shaped as a whole, and the thickness of the middle stratum is greater than that of the two sides.

[0106] The third step is sedimentary facies characterization. First, stratigraphic tracing is carried out to establish a detailed sequence stratigraphic framework for the target layer. Further stratigraphic slices are made to restore micro-paleomorphology. Microfacies or composite lobes are divided as sedimentary units based on drilling characteristics. Detailed sedimentary unit carving is carried out on the target layer, and the spatial distribution and evolution laws of different secondary sedimentary units are analyzed.

[0107] The fourth step is the quantitative coupling evaluation of the source, channel and sink, which quantitatively analyzes the volume of various parent rock lithologies, the scale of gully transport channels, and the scale of sedimentary bodies in different catchment units in the source area. According to the principle of conservation of matter, the erosion amount and transport channels of the source area and the volume of sediments in the sedimentary area are fitted to further determine the reliability of the source, channel and sink.

[0108] The fifth step is the petrological characteristics analysis. Combined with the observation of rock (wall) cores, the thin section identification results are statistically analyzed to analyze the petrological type of the target layer, including framework minerals (quartz, feldspar and rock fragments), matrix, and the type and content of cement, sorting, roundness and other characteristics.

[0109] The sixth step is the analysis of physical property characteristics, including planar characteristics and vertical characteristics. In the plane, the focus is on the relationship between physical properties and rock type, grain size, microfacies, hydrodynamic conditions, etc.; in the vertical direction, the focus is on the relationship between physical properties and depth to identify the layers where sweet spots are developed in deep reservoirs.

[0110] The seventh step is the analysis of the characteristics of authigenic minerals. By observing the type, occurrence, structure and content of authigenic minerals through microscopic data such as cast thin sections, scanning electron microscopy, cathode luminescence, and electron probe, the formation time of authigenic minerals and their impact on reservoir properties can be determined.

[0111] The eighth step is the temperature measurement analysis of inclusions. By measuring the temperature of the brine inclusions during the same period of oil and gas filling, we can analyze the ancient temperature during oil and gas migration and filling. Combined with the burial history and temperature history analysis, we can determine the ancient temperature at the critical moment of the flow rock reaction.

[0112] The ninth step is diagenesis analysis. According to the paleo-geothermal history, organic matter thermal evolution history (Ro) and the types, occurrences and sequences of authigenic minerals in sandstones, the diagenetic evolution characteristics are determined. Based on the reservoir physical property evolution characteristics, the diagenetic phases are divided into early compaction phase, early cementation phase, early dissolution phase, mid-term dissolution phase, mid-term cementation phase, etc., to determine the diagenetic phase experienced by the target layer.

[0113] The tenth step is to analyze the pore evolution characteristics. According to the burial history and diagenetic history of the sediments, on the basis of quantitative analysis of the contents of various cements and dissolution pores, the layer stripping method is used to quantitatively invert the pore evolution history.

[0114] The 11th step is the reservoir formation mechanism analysis. Based on the judgment of soluble mineral types, fluid types and diagenetic history, the key diagenetic reservoir formation mechanism (equation) is analyzed.

[0115] The 12th step is the thermodynamic analysis of soluble minerals. The thermodynamic parameters (Gibbs free energy) of each reactant and product of the above diagenetic and reservoir mechanism equation are calculated, and then the Gibbs free energy of all products is added, and the Gibbs free energy of all reactants is subtracted to obtain the Gibbs free energy increment △G. When △G is less than 0, it indicates that the reaction is a spontaneous process; when △G is smaller, the dissolution reaction is easier to proceed. Then, we calculate the △G of the dissolution reaction of soluble minerals, and calculate the △G of each soluble mineral at different temperatures T and pressures P. The results show that △G changes little with pressure P and is mainly affected by temperature T.

[0116] The 13th step is the temperature and pressure field analysis. According to the measured temperature of the drilling, the temperature and depth are fitted to obtain the relationship between the temperature and depth. Then the depth of the target layer interpreted by the seismic is converted into temperature to obtain a plane diagram of the temperature field.

[0117] The 14th step is to predict the soluble zone. By fitting the physical properties of the target layer in the study area and the surrounding area with △G, we can know the relationship between the physical properties and △G. We can select the lower limit of the physical properties of the favorable reservoir to select the corresponding △G, which is the lower limit of the favorable reservoir corresponding to the soluble mineral. With this △G as the boundary, draw the soluble zone of each soluble mineral. Then, the soluble zone of each soluble mineral is superimposed with the dominant phase of the sedimentary phase to obtain the soluble zone of the study area.

[0118] The 15th step is the kinetic analysis of soluble minerals. Whether all minerals in the soluble zone can form a favorable zone depends on the dissolution rate of the soluble minerals, that is, the area with a fast dissolution rate is more likely to form a favorable zone. Therefore, the kinetic parameter (dissolution rate r) is introduced for analysis. The dissolution rate r is a parameter related to temperature T and pH value. Through calculation, it is found that the dissolution rate r of soluble minerals has little correlation with temperature and is mainly affected by pH value.

[0119] The 16th step is the analysis of the concentration of organic acid excretion. It is difficult for us to measure the pH value in the diagenesis stage, but we can use the concentration of organic acid excretion in the burial diagenesis stage to characterize the pH value, that is, the greater the concentration of organic acid excretion, the smaller the pH value, and the faster the dissolution rate. Using the empirical formula of predecessors, according to the drainage thickness of the source rock of the first and second members of the Shahe Formation in the study area, TOC, and the experimental parameters of the previous organic acid excretion, these parameters were put into the empirical formula to calculate the planar organic acid excretion concentration. The results show that the high-value area of ​​organic acid excretion concentration in the first and second members of the Shahe Formation is located in the middle of the study area.

[0120] The 17th step is to quantitatively predict the favorable dissolution zone. Combining thermodynamics, kinetics and phase zones, the favorable dissolution zone of the target layer is predicted. Based on the organic acid concentration (such as 15), the easily soluble zone is preliminarily divided into Class I dissolution favorable zone and Class II dissolution favorable zone.

[0121] The 18th step is to verify the prediction results. The prediction results need to be verified by using wells that are not involved in the dissolution favorable area and the depth fitting to observe the change characteristics of their physical properties with depth. If there is a secondary dissolution zone in the target layer, it shows that the method has good reliability. At the same time, the paleo-geothermal temperature of the target layers of these wells is within the geothermal range corresponding to the soluble zone, which can also reflect the effectiveness of the method.

[0122] The present invention uses a (semi-)quantitative research approach to analyze the planar distribution law of favorable reservoirs, which is simple, efficient, and extensible, and has application value in oil and gas geological exploration and mineral survey research.

[0123] The technologies involved in the present invention include source-sink quantitative coupling analysis technology, soluble mineral thermodynamic analysis technology, soluble mineral kinetic analysis technology, etc.

[0124] The source-channel-sink quantitative coupling analysis technology is to quantitatively analyze the volume of various parent rock types, the scale of gully transportation channels, and the scale of sedimentary bodies in different catchment units in the source area. According to the principle of conservation of matter, the erosion amount and transportation channel of the source area and the volume of sediments in the sedimentary area are fitted to further determine the reliability of the source-channel-sink.

[0125] Thermodynamic analysis technology of soluble minerals, that is, using the fitting of the physical properties of the target layer in the study area and the surrounding area with △G, we can know the relationship between the physical properties and the corresponding △G and the physical properties, select the lower limit of the physical properties of the favorable reservoir to select the corresponding △G, that is, the lower limit of the favorable reservoir corresponding to the soluble mineral, and use the △G as the boundary to draw the soluble zone of each soluble mineral. Then, the soluble zone of each soluble mineral is superimposed with the dominant phase of the sedimentary phase to obtain the soluble zone of the study area.

[0126] The kinetic analysis technology of soluble minerals, which combines thermodynamics, kinetics and phase zones, predicts the favorable dissolution areas of the target layer. Based on the organic acid concentration (such as 15), the soluble areas are preliminarily divided into Type I dissolution favorable areas and Type II dissolution favorable areas.

[0127] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention, rather than to limit it. Although the present invention has been described in detail with reference to the aforementioned embodiments, those skilled in the art should understand that they can still modify the technical solutions described in the aforementioned embodiments, or make equivalent replacements for some of the technical features therein. However, these modifications or replacements do not deviate the essence of the corresponding technical solutions from the spirit and scope of the technical solutions of the embodiments of the present invention.

Claims

1. A quantitative prediction method for favorable areas of clastic rock dissolution, characterized in that: include: First, the source and sink are studied, and then the reservoir diagenesis mechanism is analyzed, and then the thermal / dynamic analysis of soluble minerals is carried out to point out the soluble area of ​​each soluble mineral, and then the comprehensive soluble area is divided according to the sedimentary phase plane distribution map; and the favorable dissolution area is further divided by using the dynamic analysis results, and the clastic reservoir is predicted from a quantitative and operational perspective; Conduct source-sink coupled ore determination analysis to obtain the types and distribution of soluble minerals, including: source area lithology identification, transport channel analysis, sedimentary facies characterization and source-channel-sink quantitative coupling; Conducting reservoir research and causal analysis to obtain favorable reservoir formation mechanisms, including petrological characteristics analysis, physical property characteristics analysis, authigenic mineral characteristics analysis, inclusion temperature measurement, diagenesis analysis, pore evolution characteristics and reservoir formation mechanism analysis; Performing thermal / dynamic positioning to obtain thermal / dynamic parameter distribution, the thermal / dynamic positioning includes: thermodynamic positioning of soluble minerals, temperature and pressure field analysis, prediction of soluble areas, soluble mineral dynamics, organic acid concentration and prediction of favorable dissolution areas; The plane distribution of favorable reservoirs is predicted based on the obtained soluble mineral types and distribution, favorable reservoir formation mechanism and thermal / dynamic parameter distribution.

2. The quantitative prediction method for favorable areas of clastic rock karstification according to claim 1 is characterized in that: The source area lithology identification includes: Determine the provenance of the target layer in the study area. The provenance includes regional provenance outside the basin and local provenance within the basin. Based on tectonic evolution and sedimentary filling, combined with the characteristics of light and heavy minerals, petrological characteristics and common and trace elements, conduct research to determine the direction and location of the provenance area. The identification of parent rock lithology is divided into the following steps: identification of present bedrock, that is, through the basement lithology encountered in the provenance area drilling, the lithology is identified by core and thin section identification and logging data, and the seismic reflection characteristics of different bedrock lithologies are summarized through well-seismic calibration, and the lithology type and distribution of the bedrock in the provenance area are identified and described by the seismic reflection characteristics; restoration of the parent rock area, using the stratigraphic analysis method to restore the amount of erosion and reconstruct the paleo-geomorphology of the study area before erosion, and then according to the paleo-geomorphology characteristics and the stratigraphic contact of the target layer, the provenance area, transportation channel area and deposition area are determined; water system analysis, on the basis of the paleo-geomorphology analysis, the main watershed and secondary watershed are calibrated respectively, and the paleo-water systems of different levels are divided.

3. The quantitative prediction method for favorable areas of clastic rock karstification according to claim 1 is characterized in that: The transport channel analysis includes: analyzing the transport distance and the transport channel type.

4. The quantitative prediction method for favorable areas of clastic rock karstification according to claim 1 is characterized in that: The sedimentary facies characterization includes: Conduct horizon tracing and establish a detailed sequence stratigraphic framework for the target layer; Make stratigraphic slices, restore micro-paleomorphology, divide microfacies or complex lobes as sedimentary units based on drilling characteristics, and carry out detailed sedimentary unit carving of the target layer; Analyze the spatial distribution and evolution laws of different secondary sedimentary units.

5. The quantitative prediction method for favorable areas of clastic rock karstification according to claim 1 is characterized in that: The reservoir formation mechanism analysis includes: on the basis of judging the type of soluble minerals, fluid type and diagenetic history, analyzing the key diagenetic reservoir formation mechanism according to the following relationship: in: a, b, c, and d represent reaction coefficients; A and B are reactants; C and D are products.

6. The quantitative prediction method for favorable areas of clastic rock karstification according to claim 5 is characterized in that: The thermodynamic analysis of soluble minerals includes: calculating the thermodynamic parameters of each reactant and product of the diagenetic and reservoir mechanism equation, then adding the Gibbs free energy of all products and subtracting the Gibbs free energy of all reactants to obtain the Gibbs free energy increment △G. When △G is less than 0, it indicates that the reaction is a spontaneous process; when △G is smaller, the dissolution reaction is easier to proceed. The △G of the dissolution reaction of soluble minerals is calculated, and the △G of each soluble mineral at different temperatures T and pressures P is calculated according to the following relationship: ΔG(T,P)=ΔG 0 (T,P)+RTlnQ a (2) in: △G is the Gibbs free energy increment; ΔG 0 is the Gibbs free energy under standard conditions; T is the temperature in Kelvin; P is pressure; R is the gas constant; Q a For the activity quotient.

7. The quantitative prediction method for favorable areas of clastic rock karstification according to claim 6 is characterized in that: The prediction of the soluble zone utilizes the fitting of the physical properties of the target layers in the study area and the surrounding area with △G to obtain the relationship between the physical properties and the corresponding △G. The lower limit of the physical properties of the favorable reservoir is selected to select the corresponding △G, which is set as the lower limit of the favorable reservoir corresponding to the soluble mineral. With the △G as the boundary, the soluble zone of each soluble mineral is drawn. The soluble zone of each soluble mineral is then superimposed with the dominant phase of the sedimentary phase to obtain the soluble zone of the study area.

8. The quantitative prediction method for favorable areas of clastic rock karstification according to claim 1 is characterized in that: The kinetic analysis of soluble minerals includes: introducing the dissolution rate for analysis, the dissolution rate r is a parameter related to the temperature T and the pH value, and is calculated by the following relationship: Where: r is the dissolution rate; k is the rate constant related to temperature; A is the reactive surface area per kilogram of water; is the hydrogen ion activity; ΔG 0 is the Gibbs free energy under standard conditions; The exponents μ and v are dimensionless empirical constants; R is the gas constant; T is the temperature in Kelvin.

9. The quantitative prediction method for favorable areas of clastic rock karstification according to claim 8 is characterized in that: The rate constant k was calculated according to the following relationship: in: k 25 is the reaction rate at 25°C; E a is the activation energy.

10. The quantitative prediction method for favorable areas of clastic rock karstification according to claim 1 is characterized in that: The analysis of organic acid expulsion concentration includes using the organic acid expulsion concentration in the burial diagenesis stage to characterize the pH value, that is, the greater the organic acid expulsion concentration, the smaller the pH value, and the faster the dissolution rate. According to the drainage thickness of the source rock in the target layer of the study area and the parameters of the organic acid expulsion experiment, the plane organic acid expulsion concentration is calculated according to the following relationship: in: is the average organic acid concentration in the formation water discharged from a certain calculation unit formation; H is the thickness of the mudstone formation in a certain calculation unit; S is the area of ​​a certain computing unit; C 有机 is the organic carbon content of a certain calculation unit; Q 排酸 It is the average organic acid discharge per unit organic carbon in a certain calculation unit stratum; ρ 岩 is the rock density of a certain calculation unit formation; V 水 is the volume of water; H 排水 is the discharge water height.

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