Formation pressure prediction method and device based on mineral analysis

Abstract

The invention discloses a formation pressure prediction method and device based on mineral analysis. The method comprises the following steps: predicting the formation pressure of a prediction point in a to-be-measured well under a normal compaction condition according to acquired logging information of the to-be-measured well in a well site; determining the formation porosity of the prediction point in the to-be-measured well according to the rock chemical component analysis data of the prediction point in the to-be-measured well under the under-compaction condition; according to the formation porosity, the formation pressure addition amount of the prediction point under the under-compaction condition is determined; according to the formation pressure of the prediction point under the normal compaction condition and the formation pressure additional amount of the prediction point under the compaction condition, the formation pressure of the prediction point in the to-be-measured well under the under-compaction condition is predicted. On the basis of logging information, the influence of the under-compaction effect on the formation pressure is considered, the formation pressure predicted under the normal compaction condition is adjusted, the accuracy of formation pressure prediction is improved under the condition of not depending on seismic data, and more effective technical support is provided for drilling work of petroleum and natural gas.

Description

Technical Field

[0001] The present invention relates to the field of oil and gas drilling engineering, and particularly to a formation pressure prediction method and device based on mineral analysis. Background Art

[0002] During the process of oil and gas drilling, formation pressure is a very important parameter. The accurate prediction of formation pressure is the basis for safe drilling and wellbore structure design. As oil and gas exploration progresses deeper, the frequency of encountering abnormal pressure formations is increasing. Accurately identifying abnormal formation pressure is the key to reducing drilling accidents.

[0003] At present, there are some methods for predicting formation pressure. For example, Chinese Patent with application number CN201910373439.1 discloses a method for predicting pore pressure of non-undercompacted formations, Chinese Patent with application number CN202110292026.8 discloses a method, device and equipment for predicting formation pressure coefficient using seismic data, and Chinese Patent with application number CN201910648700.4 discloses a method and system for determining formation pressure by combining well and seismic data. Summary of the Invention

[0004] Most of the existing formation pressure prediction methods rely heavily on seismic data. However, due to the insufficient accuracy of seismic data, there are large errors in the formation pressure prediction results. Moreover, in the case of high temperature and high pressure or complex well conditions, the use of logging-while-drilling tools is also restricted to a certain extent, which also leads to inaccurate prediction of formation pressure. In addition, the existing methods do not consider establishing a formation pressure prediction model from the aspect of formation undercompaction. The formation pressure calculated without considering formation undercompaction is usually lower than the measured value of formation pressure. Therefore, the formation pressure prediction model that does not consider the influence of formation undercompaction has poor accuracy in predicting formation pressure, cannot accurately predict the pressure of abnormal pressure formations, and cannot provide accurate data support for oil and gas exploration.

[0005] In view of the above problems, the present invention is proposed to provide an abnormal formation pressure prediction method and device that overcome or at least partially solve the above problems.

[0006] In a first aspect, an embodiment of the present invention provides a formation pressure prediction method based on mineral analysis, including:

[0007] Predicting the formation pressure of a prediction point in a well to be measured under normal compaction conditions according to the logging data of the well to be measured collected at the well site;

[0008] Determining the formation porosity of a prediction point in the well to be measured according to the rock chemical composition analysis data of the prediction point in the well to be measured under undercompaction conditions;

[0009] Determine the formation pressure increment of the prediction point under undercompaction conditions based on the formation porosity of the prediction point;

[0010] Based on the formation pressure of the prediction point under normal compaction conditions and the formation pressure increment of the prediction point under undercompaction conditions, predict the formation pressure of the prediction point in the well to be measured under undercompaction conditions.

[0011] In some alternative embodiments, predicting the formation pressure of the prediction point in the well to be measured under normal compaction conditions based on the well logging data of the well to be measured collected at the well site includes:

[0012] Determine the Eaton index of the well site based on the measured formation pressure of at least one well that has been logged at the well site, the overburden pressure data, natural gamma data, and oil and gas related parameters at the corresponding depth of the measured point of the well that has been logged; the natural gamma data includes the natural gamma on the normal compaction trend line of the well that has been logged and the natural gamma included in the well logging data of the well that has been logged;

[0013] Predict the formation pressure of the prediction point in the well to be measured under normal compaction conditions based on the natural gamma data, overburden pressure data, oil and gas related parameters, and Eaton index of the prediction point in the well to be measured.

[0014] In some alternative embodiments, construct the normal compaction trend line of the well that has been logged according to the following formula: lnGR' n =a - Cd 1 , where GR' n is the natural gamma on the normal compaction trend line, a is the natural gamma at zero depth, C is the compaction coefficient, and d 1 is the depth of the measured point.

[0015] In some alternative embodiments, determine the overburden pressure P' of the well that has been logged at the corresponding depth of the measured point according to the following formula v :

[0016] where H is the formation depth; ρ is the formation density, and T is the formation temperature.

[0017] In some alternative embodiments, determining the Eaton index of the well site includes:

[0018] Determine the Eaton index N' of at least one well that has been logged at the well site;

[0019] Perform weighted averaging on the Eaton index N' of the well that has been logged to determine the Eaton index N of the well site.

[0020] In some alternative embodiments, determine the Eaton index N' of a well that has been logged according to the following formula:

[0021] where P p ' is the measured formation pressure value of the logged formation, P v ' is the overburden pressure of the logged formation, ρ w is the density of water, ρ p is the density of oil or gas, h 1 is the thickness of the oil and gas column below the depth of the measured point, d 1 is the depth of the measured point; ρ is the formation density, GR' n is the natural gamma on the normal compaction trend line of the logged well, and GR' is the natural gamma in the logging data of the logged well;

[0022] In some alternative embodiments, based on the natural gamma data, overburden pressure data, oil and gas related parameters, and Eaton index of the prediction point in the well to be logged, predict the formation pressure of the prediction point in the well to be logged under normal compaction conditions, including:

[0023] Combining the natural gamma data, overburden pressure data, oil and gas related parameters, and Eaton index of the prediction point in the well to be logged, predict the formation pressure P of the prediction point in the well to be logged under normal compaction conditions according to the following formula p : where P v is the overburden pressure, ρ w is the density of water, ρ p is the density of oil or gas, h is the thickness of the oil and gas column below the depth of the prediction point, d is the depth of the prediction point, ρ is the formation density, GR n is the natural gamma on the normal compaction trend line of the well to be logged, GR is the natural gamma in the logging data of the well to be logged, and N is the Eaton index of the well site.

[0024] In some alternative embodiments, the natural gamma on the normal compaction trend line of the well to be logged is obtained by the following method:

[0025] According to the logging data of the well to be logged, select the natural gamma under normal compaction conditions, and construct the normal compaction trend line of the well to be logged according to the following formula: lnGR n = a - Cd, where GR n is the natural gamma on the normal compaction trend line, a is the natural gamma at zero depth, C is the compaction coefficient, and d is the depth of the prediction point;

[0026] The overburden pressure is obtained by the following method:

[0027] According to the obtained logging data of the well to be logged, determine the overburden pressure P at the corresponding depth of the well to be logged according to the following formula v : where H is the formation depth, ρ is the formation density, and T is the formation temperature;

[0028] In some alternative embodiments, determining the formation porosity of a prediction point in a well to be measured according to the rock chemical composition analysis data of the prediction point in the well to be measured under undercompaction conditions includes:

[0029] Determining the relative molecular mass M of the rock and the rock density ρ according to the rock chemical composition analysis data of the prediction point in the well to be measured under undercompaction conditions; the relative molecular mass of the rock is determined according to the relative molecular masses and mass fractions of the components in the rock; the rock density is calculated according to the volumes and densities of the components in the rock;

[0030] Determining the formation porosity of the prediction point in the well to be measured according to the relative molecular mass M of the rock and the density ρ of the rock.

[0031] In some alternative embodiments, determining the relative molecular mass M of the rock according to the relative molecular masses and mass fractions of the components in the rock includes:

[0032] Determining the relative molecular mass of the rock according to the following formula: where M 0 (i) is the relative molecular mass of the i-th component in the rock, and w(i) is the mass fraction of the i-th component in the rock;

[0033] Calculating the rock density ρ according to the volumes and densities of the components in the rock includes:

[0034] Determining the density of the rock according to the following formula: where V i is the volume of the i-th component in the rock, V is the rock volume, and ρ i is the density of the i-th component in the rock;

[0035] Determining the formation porosity of the prediction point in the well to be measured according to the relative molecular mass M of the rock and the density ρ of the rock includes:

[0036] Determining the formation porosity of the prediction point in the well to be measured according to the following formula where M is the relative molecular mass of the rock and ρ is the rock density.

[0037] In some alternative embodiments, determining the formation pressure increment of a prediction point under undercompaction conditions according to the formation porosity includes:

[0038] Determining the formation pressure increment of the prediction point under undercompaction conditions according to the maximum porosity of the formation where the prediction point is located, the minimum porosity of the formation where the prediction point is located, the depth of the prediction point, the porosity of the prediction point, and the formation density

[0039] In some alternative embodiments, determining the formation pressure increment E of the prediction point under undercompaction conditions according to the following formula: where η is the correction exponent, is the formation porosity at the prediction point, is the maximum porosity of the formation where the prediction point is located, is the minimum porosity of the formation where the prediction point is located, ρ is the formation density, and d is the depth of the prediction point.

[0040] In some alternative embodiments, predicting the formation pressure at the prediction point in the undercompacted condition in the well to be measured according to the formation pressure at the prediction point under normal compaction conditions and the formation pressure increment at the prediction point under undercompacted conditions includes:

[0041] Combining the formation pressure at the prediction point under normal compaction conditions and the formation pressure increment at the prediction point under undercompacted conditions, predicting the formation pressure P at the prediction point in the undercompacted condition in the well to be measured according to the following formula:

[0042] P = P p + E, where P p is the formation pressure at the prediction point under normal compaction conditions, and E is the formation pressure increment at the prediction point under undercompacted conditions.

[0043] In a second aspect, an embodiment of the present invention provides a formation pressure prediction device based on mineral analysis, including:

[0044] A data acquisition module for acquiring well logging data of the well to be measured at the well site;

[0045] A data processing module for determining the formation porosity at the prediction point in the well to be measured according to the rock chemical composition analysis data at the prediction point under undercompacted conditions; and determining the formation pressure increment at the prediction point under undercompacted conditions according to the formation porosity;

[0046] A pressure prediction module for predicting the formation pressure at the prediction point in the well to be measured under normal compaction conditions according to the acquired well logging data of the well to be measured at the well site; and predicting the formation pressure at the prediction point in the well to be measured under undercompacted conditions according to the formation pressure at the prediction point under normal compaction conditions and the formation pressure increment at the prediction point under undercompacted conditions.

[0047] An embodiment of the present invention provides a computer storage medium, in which computer-executable instructions are stored, and when the computer-executable instructions are executed by a processor, the above-mentioned formation pressure prediction method based on mineral analysis is implemented.

[0048] An embodiment of the present invention provides a computer device, including: a memory, a processor, and a computer program stored on the memory and executable on the processor, and when the processor executes the program, the above-mentioned formation pressure prediction method based on mineral analysis is implemented.

[0049] The beneficial effects of the above technical solutions provided by the embodiments of the present invention at least include:

[0050] The formation pressure measured by traditional methods without considering formation undercompaction is often less than the formation pressure. To improve the deficiencies of traditional formation pressure prediction methods, the method provided by the present invention predicts the formation pressure of a prediction point in a well to be measured under normal compaction conditions based on the well logging data of the well to be measured collected at the well site. When predicting, considering that undercompaction will affect the accuracy of formation pressure, after determining the formation pressure under normal compaction conditions, according to the rock chemical composition analysis data of the prediction point in the well to be measured under undercompaction conditions, determine the formation porosity of the prediction point in the well to be measured; according to the formation porosity, determine the formation pressure increment of the prediction point under undercompaction conditions; according to the formation pressure of the prediction point under normal compaction conditions and the formation pressure increment of the prediction point under undercompaction conditions, predict the formation pressure of the prediction point in the well to be measured under undercompaction conditions. Starting from the aspect of the influence of undercompaction on formation pressure, predicting the formation pressure will be closer to the actual formation pressure, solving the problem of inaccurate formation pressure prediction in the prior art. Moreover, the method for predicting formation pressure does not rely on seismic data, but predicts the formation pressure based on the well logging data of the well to be measured, which can improve the accuracy of formation pressure prediction and provide more effective technical support for oil and gas drilling work.

[0051] Other features and advantages of the present invention will be described in the following specification, and, in part, will be obvious from the specification, or will be understood by implementing the present invention. The objectives and other advantages of the present invention can be achieved and obtained by the structures specifically pointed out in the written specification, claims, and drawings.

[0052] The following will further describe the technical solutions of the present invention in detail through the drawings and embodiments. Description of the Drawings

[0053] The drawings are used to provide a further understanding of the present invention, and constitute a part of the specification. Together with the embodiments of the present invention, they are used to explain the present invention and do not constitute a limitation to the present invention. In the drawings:

[0054] Figure 1 is a flowchart of the formation pressure prediction method based on mineral analysis in the embodiment of the present invention;

[0055] Figure 2 is an example diagram of the measured value and predicted value of porosity in the embodiment of the present invention;

[0056] Figure 3 is an example diagram of the formation density of Well LH2 in the embodiment of the present invention;

[0057] Figure 4An example diagram of the natural gamma of Well LH2 in the embodiments of the present invention;

[0058] Figure 5 An example diagram of the formation pressure prediction result of Well LH2 under normal compaction conditions in the embodiments of the present invention;

[0059] Figure 6 A schematic diagram of the relative molecular mass structure of rocks in Well LH2 in the embodiments of the present invention;

[0060] Figure 7 A schematic diagram of the rock density in Well LH2 in the embodiments of the present invention;

[0061] Figure 8 A schematic diagram of the formation porosity in Well LH2 in the embodiments of the present invention;

[0062] Figure 9 An example diagram of the formation pressure prediction result of Well LH2 under undercompaction conditions in the embodiments of the present invention;

[0063] Figure 10 A schematic diagram of the comparison result of predicting the formation pressure of Well LH2 by three methods in the embodiments of the present invention;

[0064] Figure 11 A structural diagram of the formation pressure prediction device based on mineral analysis in the embodiments of the present invention. Detailed implementation manners

[0065] Hereinafter, exemplary embodiments of the present disclosure will be described in more detail with reference to the accompanying drawings. Although the exemplary embodiments of the present disclosure are shown in the drawings, it should be understood that the present disclosure can be implemented in various forms and should not be limited by the embodiments set forth herein. On the contrary, these embodiments are provided so that the present disclosure can be more thoroughly understood and the scope of the present disclosure can be fully conveyed to those skilled in the art.

[0066] Formation undercompaction is the main cause of abnormal formation pressure. When the formation is in an undercompacted state, the rock porosity will be higher than that of a normally compacted formation, thus affecting the formation pressure. The formation pressure under undercompaction is the sum of the formation pressure under normal compaction and the formation pressure increment caused by undercompaction. The formation pressure calculated considering formation undercompaction is more consistent with the true formation pressure.

[0067] Existing methods do not consider establishing a formation pressure prediction model from the aspect of formation undercompaction. The formation pressure calculated without considering formation undercompaction is usually lower than the measured value of the formation pressure. Therefore, the formation pressure predicted by a formation pressure prediction model that does not consider the influence of formation undercompaction has relatively poor accuracy, cannot accurately predict the pressure of an abnormally pressured formation, and cannot provide accurate data support for oil and gas exploration.

[0068] To solve the problem of inaccurate formation pressure prediction in the prior art, an embodiment of the present invention provides a formation pressure prediction method based on mineral analysis, which can predict the formation pressure under undercompaction conditions, and the predicted formation pressure is more accurate, which can provide accurate data support for oil and gas exploration.

[0069] An embodiment of the present invention provides a formation pressure prediction method based on mineral analysis, and its process is as Figure 1 shown, including the following steps:

[0070] Step S101: According to the logging data of the well to be measured collected at the well site, predict the formation pressure of the prediction point in the well to be measured under normal compaction conditions;

[0071] Step S102: Determine the formation porosity of the prediction point in the well to be measured according to the rock chemical composition analysis data of the prediction point in the well to be measured under undercompaction conditions;

[0072] Step S103: Determine the formation pressure increment of the prediction point under undercompaction conditions according to the formation porosity of the prediction point;

[0073] Step S104: Predict the formation pressure of the prediction point in the well to be measured under undercompaction conditions according to the formation pressure of the prediction point under normal compaction conditions and the formation pressure increment of the prediction point under undercompaction conditions.

[0074] Preferably, the above step S101 realizes the prediction of the formation pressure under normal compaction conditions. Among them, according to the logging data of the well to be measured collected at the well site, predicting the formation pressure of the prediction point in the well to be measured under normal compaction conditions includes: determining the Eaton index of the well site according to the measured formation pressure of at least one well that has been logged in the well site, the overburden pressure data, the natural gamma data, and the oil and gas related parameters at the corresponding depth of the measured point of the well that has been logged; predicting the formation pressure of the prediction point in the well to be measured under normal compaction conditions according to the natural gamma data, the overburden pressure data, the oil and gas related parameters, and the Eaton index of the prediction point in the well to be measured. Among them, the natural gamma data includes the natural gamma on the normal compaction trend line of the well that has been logged and the natural gamma included in the logging data of the well that has been logged.

[0075] Preferably, the process of predicting the formation pressure under normal compaction conditions may include:

[0076] 1) Establish the normal compaction trend line of the well that has been logged.

[0077] Construct the normal compaction trend line of the well that has been logged according to the following formula: lnGR' n =a - Cd 1 , where GR' n is the natural gamma on the normal compaction trend line, a is the natural gamma at zero depth, C is the compaction coefficient, d1 is the depth of the measured point.

[0078] 2) Calculate the overburden pressure at different depths of the logged wells.

[0079] Determine the overburden pressure P' at the depth corresponding to the measured point of the logged well according to the following formula v :

[0080] where H is the formation depth; ρ is the formation density, and T is the formation temperature.

[0081] 3) Obtain the Eaton index of the well site.

[0082] The Eaton index of the well site can be determined based on the measured data of n wells in the well site. Determining the Eaton index of the well site includes: determining the Eaton index N' of at least one logged well in the well site; performing a weighted average on the Eaton index N' of the logged well to determine the Eaton index N of the well site.

[0083] When determining the Eaton index of a well, the measured formation pressure, overburden pressure data, natural gamma data, and oil and gas related parameters at the measured point of the well can be considered. Among them, the oil and gas related parameters can consider one or more of the parameters such as water density, oil density, gas density, gas column thickness, and formation density.

[0084] Optionally, determine the Eaton index N' of a logged well according to the following formula:

[0085] where P p ' is the measured value of the formation pressure of the logged well, P v ' is the overburden pressure of the logged well, ρ w is the density of water, ρ p is the density of oil or gas, h 1 is the thickness of the oil and gas column below the depth of the measured point, d 1 is the depth of the measured point; ρ is the formation density, GR' n is the natural gamma on the normal compaction trend line of the logged well, and GR' is the natural gamma in the logging data of the logged well.

[0086] 4) Prediction of formation pressure of the well to be logged under normal compaction conditions.

[0087] When predicting the formation pore pressure under normal compaction conditions of a well to be measured, the formation pressure at different prediction points can be predicted based on the depth of the prediction points. Before making the prediction, a normal compaction trend line of the well to be measured can be established in advance, and the overburden pressure at different depths of the well to be measured can be calculated. Then, based on the natural gamma data, overburden pressure data, oil and gas related parameters, and Eaton index at the prediction points in the well to be measured, the formation pressure at the prediction points in the well to be measured under normal compaction conditions is predicted, including:

[0088] Combining the natural gamma data, overburden pressure data, oil and gas related parameters, and Eaton index at the prediction points in the well to be measured, the formation pressure P at the prediction points in the well to be measured under normal compaction conditions is predicted according to the following formula p :

[0089]

[0090] where P v is the overburden pressure, ρ w is the density of water, ρ p is the density of oil or gas, h is the thickness of the oil and gas column below the depth of the prediction point, d is the depth of the prediction point, ρ is the formation density, GR n is the natural gamma on the normal compaction trend line of the well to be measured, GR is the natural gamma in the well logging data of the well to be measured, and N is the Eaton index of the well site.

[0091] The formation pressure predicted by the Eaton method under normal compaction conditions is often lower than the true formation pressure. Therefore, the formation pressure determined by this method is not accurate enough, resulting in slow and less refined exploration work. Therefore, in order to make the predicted formation pressure more accurate, provide more accurate data for exploration work, and improve work efficiency, on the basis of predicting the formation pressure under normal compaction conditions, the influence of undercompaction is further considered, and the predicted formation pressure under normal compaction conditions is adjusted.

[0092] For the establishment of the normal compaction trend line, refer to the relevant description in 1) above. The natural gamma on the normal compaction trend line of the well to be measured is obtained through the following method:

[0093] According to the well logging data of the well to be measured, select the natural gamma under normal compaction conditions, and construct the normal compaction trend line of the well to be measured according to the following formula: lnGR n = a - Cd, where GR n is the natural gamma on the normal compaction trend line, a is the natural gamma at zero depth, C is the compaction coefficient, and d is the depth of the prediction point;

[0094] For calculating the overlying formation pressure, refer to the relevant description in 2) above. The overlying formation pressure is obtained by the following method:

[0095] According to the logging data of the well to be measured obtained, the overlying formation pressure P at the corresponding depth of the well to be measured is determined according to the following formula v : where H is the formation depth, ρ is the formation density, and T is the formation temperature.

[0096] Preferably, in the above step S102, according to the rock chemical composition analysis data of the prediction point in the well to be measured under the undercompaction condition, the formation porosity of the prediction point in the well to be measured is determined, including:

[0097] According to the rock chemical composition analysis data of the prediction point in the well to be measured under the undercompaction condition, the relative molecular mass M of the rock and the rock density ρ are determined; the relative molecular mass of the rock is determined according to the relative molecular masses and mass fractions of the components in the rock; the rock density is calculated according to the volumes and densities of the components in the rock;

[0098] According to the relative molecular mass M of the rock and the rock density ρ, the formation porosity of the prediction point in the well to be measured is determined.

[0099] Preferably, determining the relative molecular mass M of the rock according to the relative molecular masses and mass fractions of the components in the rock includes:

[0100] Determine the relative molecular mass of the rock according to the following formula: where M 0 (i) is the relative molecular mass of the i-th component in the rock, and w(i) is the mass fraction of the i-th component in the rock;

[0101] Calculating the rock density ρ according to the volumes and densities of the components in the rock includes:

[0102] Determine the density of the rock according to the following formula: where V i is the volume of the i-th component in the rock, V is the rock volume, and ρ i is the density of the i-th component in the rock;

[0103] Determining the formation porosity of the prediction point in the well to be measured according to the relative molecular mass M of the rock and the rock density ρ includes:

[0104] Determine the formation porosity of the prediction point in the well to be measured according to the following formula where M is the relative molecular mass of the rock and ρ is the rock density.

[0105] The chemical composition analysis method of rocks can be realized by XRD mineral analysis. Using the results, the rock skeleton volume can be calculated, which indirectly reflects the porosity of formation rocks. According to the analysis results and the relationship between porosity and the relative molecular mass and density of rocks, the porosity of formation rocks can be determined.

[0106] In this embodiment, the method for determining porosity in step S102 above is used to verify the porosity of the formation at 3500m - 3700m of Well LH2 in the LZ block. According to the actual measurement of core porosity experiment, the measured porosity values of the cores at depths of 3500m, 3600m, and 3700m in the formation where Well LH2 is located are 16.83%, 21.94%, and 15.93% respectively. The predicted porosity values of Well LH2 at depths of 3500m, 3600m, and 3700m are 18.13%, 23.45%, and 16.82% respectively through the above porosity determination method. Figure 2 It is a comparison example diagram of the measured value and predicted value of porosity. The average error between the measured value and the predicted value is 6.7%, and the error is within 10%, indicating that the proposed method can meet the on-site engineering requirements.

[0107] Preferably, in step S103 above, according to the formation porosity, determining the formation pressure additional amount at the prediction point under the undercompaction condition includes:

[0108] Determining the formation pressure additional amount at the prediction point under the undercompaction condition according to the maximum porosity of the formation where the prediction point is located, the minimum porosity of the formation where the prediction point is located, the depth of the prediction point, the porosity of the prediction point, and the formation density

[0109] Preferably, the formation pressure additional amount E at the prediction point under the undercompaction condition is determined according to the following formula:

[0110] where η is the correction index. For example, in this embodiment, the correction index takes 0.1 - 0.2, and other thresholds can also be set according to requirements. is the formation porosity of the prediction point. is the maximum porosity of the formation where the prediction point is located. is the minimum porosity of the formation where the prediction point is located, ρ is the formation density, and d is the depth of the prediction point.

[0111] Preferably, in step S104 above, according to the formation pressure of the prediction point under the normal compaction condition and the formation pressure additional amount of the prediction point under the undercompaction condition, predicting the formation pressure of the prediction point in the well to be measured under the undercompaction condition includes:

[0112] Combining the formation pressure of the prediction point under the normal compaction condition and the formation pressure additional amount of the prediction point under the undercompaction condition, predicting the formation pressure P of the prediction point in the well to be measured under the undercompaction condition according to the following formula:

[0113] P = P p + E, where P p is the formation pressure at the prediction point under normal compaction conditions, and E is the additional formation pressure at the prediction point under undercompaction conditions.

[0114] The calculation formula for the formation pressure under undercompaction conditions can also be expressed as:

[0115] where P is the formation pressure, P v is the overlying formation pressure, ρ is the formation density, ρ w is the density of water, ρ p is the density of oil or gas, h is the thickness of the oil and gas column below the depth of the prediction point, d is the depth of the prediction point, GR n is the natural gamma on the normal compaction trend line, GR is the natural gamma in the logging data, N is the Eaton index, η is the correction index, which is taken as 0.1 - 0.2 in this example and can also be set according to the actual situation. is the porosity, d is the depth, is the maximum porosity of the formation where the prediction point is located, is the minimum porosity of the formation where the prediction point is located.

[0116] Since the formation pressure predicted under normal compaction conditions is lower than the actual formation pressure, adding the additional formation pressure under undercompaction conditions on the basis of the formation pressure predicted under normal compaction conditions, the finally predicted formation pressure will be closer to the true formation pressure, providing an accurate data basis for exploration work.

[0117] To verify the practical value of this method, the formation pressure at a formation depth of 3500m - 3700m in Well LH2 in the LZ block is predicted using this method.

[0118] The basic parameters for predicting the formation pore pressure of Well LH2 come from logging data, including formation density, natural gamma. Figure 3 is an example diagram of formation density. Figure 4 is an example diagram of the natural gamma at the corresponding formation depth in the logging data. The normal compaction trend line equation of Well LH2 constructed based on the natural gamma under normal compaction conditions is lnGR = 0.0008h + 2.5236; before drilling Well LH2, according to the measured formation pressure data of Well SY3 in the well site, the overlying formation pressure data, natural gamma data, and oil and gas related parameters at the corresponding depth of the measured points, the Eaton index of the well site is determined, and the Eaton index of this well site is obtained as 1.3; according to the formation pressure determination formula, the formation pressure under normal compaction conditions of Well LH2 is obtained. The predicted formation pressure results under normal compaction conditions are shown in Figure 5 as shown.

[0119] Based on the analysis data of the rock chemical composition at the prediction points in Well LH2 under the undercompaction condition, the relative molecular mass of the rock in Well LH2 within the depth range of 3500m - 3700m is obtained. See Figure 6 as shown; the rock density in Well LH2 within the depth range of 3500m - 3700m is obtained. See Figure 7 as shown; the formation porosity at the prediction points in Well LH2 is determined according to the relative molecular mass of the rock and the rock density within 3500m - 3700m. See Figure 8 as shown; finally, based on the formation pressure at the prediction points under normal compaction conditions and the additional amount of formation pressure at the prediction points under undercompaction conditions, the formation pressure at the prediction points in Well LH2 under undercompaction conditions is predicted. See the prediction result diagram Figure 9 as shown.

[0120] Through the oil testing method, the formation pressures at the prediction points in Well LH2 at depths of 3500m, 3550m, 3600m, 3650m, and 3700m are 35.1MPa, 35.7MPa, 36.3MPa, 36.8MPa, and 37.4MPa respectively. The formation pressures at the prediction points at the above corresponding depths calculated by the method proposed in this embodiment are 36.4MPa, 36.9MPa, 37.3MPa, 37.8MPa, and 38.7MPa respectively; comparing the measured values of the formation pressure, the predicted values of the method proposed in this embodiment, and the predicted values of the conventional Eaton method, see the comparison result Figure 10 as shown. The average error between this method and the measured formation pressure is 3.2%, and the error is within 5%, indicating that the proposed method can meet the on-site engineering requirements. The average error between the predicted values of the traditional Eaton method and the measured values is 9.5%. Therefore, the accuracy of the method proposed in the present invention is improved by 6.3% compared with the traditional Eaton method, and this method has practical value.

[0121] Based on the same inventive concept, an embodiment of the present invention also provides a formation pressure prediction device based on mineral analysis. This device can be set in a device capable of processing computer instructions. The structure of this device is as Figure 11 shown, and it includes:

[0122] A data acquisition module 11, which is used to acquire the logging data of the well to be measured in the well site;

[0123] A data processing module 12, which is used to determine the formation porosity at the prediction points in the well to be measured according to the analysis data of the rock chemical composition at the prediction points in the well to be measured under the undercompaction condition; and determine the additional amount of formation pressure at the prediction points under the undercompaction condition according to the formation porosity;

[0124] A pressure prediction module 13 is configured to predict the formation pressure of a prediction point in a well to be measured in a well site under normal compaction conditions according to the well logging data of the well to be measured in the well site; and predict the formation pressure of the prediction point in the well to be measured under undercompaction conditions according to the formation pressure of the prediction point under normal compaction conditions and the formation pressure increment of the prediction point under undercompaction conditions.

[0125] Regarding the formation pressure prediction device based on mineral analysis in the above embodiments, the specific manners in which each module performs operations have been described in detail in the embodiments related to the method, and will not be elaborated herein.

[0126] In the above method and device of the embodiments of the present invention, the formation pressure of a prediction point in a well to be measured is predicted according to the well logging data of the well to be measured in the well site. This method takes into account that undercompaction will affect the accuracy of the formation pressure; therefore, after determining the formation pressure under normal compaction conditions, the formation porosity of the prediction point in the well to be measured under undercompaction conditions is determined according to the rock chemical composition analysis data of the prediction point in the well to be measured under undercompaction conditions; according to the formation porosity, the formation pressure increment of the prediction point under undercompaction conditions is determined; and the formation pressure of the prediction point in the well to be measured under undercompaction conditions is predicted according to the formation pressure of the prediction point under normal compaction conditions and the formation pressure increment of the prediction point under undercompaction conditions. Starting from the aspect of the influence of undercompaction on the formation pressure, the formation pressure is predicted, and the predicted formation pressure will be closer to the actual formation pressure, solving the problem of inaccurate prediction of formation pressure in the prior art. Moreover, the method for predicting the formation pressure of this method does not rely on seismic data, but predicts the formation pressure according to the well logging data of the well to be measured, which can improve the accuracy of formation pressure prediction and provide more effective technical support for the drilling work of oil and gas.

[0127] The embodiments of the present invention further provide a computer storage medium, in which computer-executable instructions are stored, and when the computer-executable instructions are executed by a processor, the above-mentioned formation pressure prediction method based on mineral analysis is implemented.

[0128] The embodiments of the present invention provide a computer device, including: a memory, a processor, and a computer program stored on the memory and executable on the processor, and when the processor executes the program, the above-mentioned formation pressure prediction method based on mineral analysis is implemented.

[0129] Unless otherwise specifically stated, terms such as processing, computing, calculating, determining, displaying, etc. can refer to the actions and / or processes of one or more processing or computing systems, or similar devices, which operate on and transform data represented as a physical (such as electronic) quantity within the registers or memories of the processing system into other data similarly represented as a physical quantity within the memories, registers, or other such information storage, transmission, or display devices of the processing system. Information and signals can be represented using any of a variety of different technologies and methods. For example, the data, instructions, commands, information, signals, bits, symbols, and chips mentioned throughout the above description can be represented by voltages, currents, electromagnetic waves, magnetic fields or particles, optical fields or particles, or any combination thereof.

[0130] It should be understood that the specific order or hierarchy of steps in the disclosed processes is an example of an exemplary method. Based on design preferences, it should be understood that the specific order or hierarchy of steps in a process can be rearranged without departing from the scope of the present disclosure. The appended method claims present the elements of the various steps in an exemplary order and are not intended to be limited to the specific order or hierarchy recited.

[0131] In the above detailed description, various features are combined in a single embodiment to simplify the present disclosure. This method of disclosure should not be interpreted as reflecting an intention that the embodiments of the claimed subject matter require more features than are expressly recited in each claim. On the contrary, as reflected in the appended claims, the invention lies in less than all of the features of a single disclosed embodiment. Accordingly, the appended claims are hereby expressly incorporated into the detailed description, with each claim standing alone as a separate preferred embodiment of the invention.

[0132] Those skilled in the art should also understand that the various illustrative logical blocks, modules, circuits, and algorithmic steps described in connection with the embodiments herein can be implemented as electronic hardware, computer software, or combinations thereof. To clearly illustrate the interchangeability of hardware and software, the above description of various illustrative components, blocks, modules, circuits, and steps has been generally described in terms of their functionality. Whether such functionality is implemented as hardware or software depends upon the particular application and the design constraints imposed on the overall system. Skilled artisans may implement the described functionality in a flexible manner for each particular application, but such implementation decisions should not be interpreted as departing from the scope of the present disclosure.

[0133] The steps of the methods or algorithms described in connection with the embodiments of this specification may be embodied directly in hardware, in a software module executed by a processor, or in a combination thereof. The software module may be located in a RAM memory, a flash memory, a ROM memory, an EPROM memory, an EEPROM memory, a register, a hard disk, a removable disk, a CD-ROM, or any other form of storage medium well known in the art. An exemplary storage medium is coupled to the processor such that the processor can read information from, and write information to, the storage medium. Of course, the storage medium may also be an integral part of the processor. The processor and the storage medium may be located in an ASIC. The ASIC may be located in a user terminal. Of course, the processor and the storage medium may also exist as discrete components in the user terminal.

[0134] For a software implementation, the techniques described in this application can be implemented using modules (e.g., procedures, functions, etc.) that perform the functions described in this application. These software codes can be stored in a memory unit and executed by a processor. The memory unit may be implemented within the processor or outside the processor, and in the latter case, it is communicatively coupled to the processor by various means, which are well known in the art.

[0135] The above description includes examples of one or more embodiments. Of course, it is not possible to describe all possible combinations of components or methods for the purpose of describing the above embodiments, but those of ordinary skill in the art should recognize that each embodiment can be further combined and arranged. Therefore, the embodiments described herein are intended to cover all such changes, modifications, and variations that fall within the scope of the appended claims. In addition, with respect to the term "comprising" used in the specification or claims, this term is inclusive in a manner similar to the term "including" as interpreted when used as a transitional word in a claim. In addition, any use of the term "or" in the claims or specification is to mean "non-exclusive or".

Claims

1. A method for predicting formation pressure based on mineral analysis, characterized in that, it includes: Predict the formation pressure of the prediction point in the well to be measured under normal compaction conditions according to the logging data of the well to be measured collected at the well site; Determine the formation porosity of the prediction point in the well to be measured according to the rock chemical composition analysis data of the prediction point in the well to be measured under undercompaction conditions; Determine the formation pressure increment of the prediction point under undercompaction conditions according to the formation porosity; Predict the formation pressure of the prediction point in the well to be measured under undercompaction conditions according to the formation pressure of the prediction point under normal compaction conditions and the formation pressure increment of the prediction point under undercompaction conditions.

2. The method according to claim 1, characterized in that, The predicting the formation pressure of the prediction point in the well to be measured under normal compaction conditions according to the logging data of the well to be measured collected at the well site includes: Determine the Eaton index of the well site according to the measured formation pressure of at least one well that has been logged in the well site, the overburden pressure data, natural gamma data, and oil and gas related parameters at the corresponding depth of the measured point of the well that has been logged; the natural gamma data includes the natural gamma on the normal compaction trend line of the well that has been logged and the natural gamma included in the logging data of the well that has been logged; Predict the formation pressure of the prediction point in the well to be measured under normal compaction conditions according to the natural gamma data, overburden pressure data, oil and gas related parameters of the prediction point in the well to be measured and the Eaton index.

3. The method according to claim 2, characterized in that, Construct the measured normal compaction trend line according to the following formula: lnGR' n = a - Cd 1 , where GR' n is the natural gamma ray on the normal compaction trend line, a is the natural gamma ray at zero depth, C is the compaction coefficient, and d 1 is the depth of the measured point.

4. The method according to claim 2, characterized in that, Determine the overburden pressure P' of the logged well at the depth corresponding to the measured point according to the following formula v :[[]]END]] Where H is the formation depth; ρ is the formation density, and T is the formation temperature.

5. The method according to claim 2, characterized in that, The determining the Eaton index of the well site includes: Determine the Eaton index N' of at least one well that has been logged in the well site; Perform weighted averaging on the Eaton index N' of the well that has been logged to determine the Eaton index N of the well site.

6. The method according to claim 5, characterized in that, Determine the Eaton index N' of a well that has been logged according to the following formula: Among them, P p ' is the measured value of the formation pressure of the logged well, and P v ' is the overburden pressure of the logged well, ρ w is the density of water, ρ p is the density of oil or gas, h 1 is the thickness of the oil and gas column below the depth of the measured point, d 1 is the depth of the measured point; ρ is the formation density, GR' n is the natural gamma on the normal compaction trend line of the logged well, and GR' is the natural gamma in the logging data of the logged well.

7. The method according to claim 2, characterized in that, The predicting the formation pressure of the prediction point in the well to be measured under normal compaction conditions according to the natural gamma data, overburden pressure data, oil and gas related parameters of the prediction point in the well to be measured and the Eaton index includes: Predict the formation pressure P at the prediction point in the well to be measured under normal compaction conditions according to the following formula by combining the natural gamma data, overlying formation pressure data, oil and gas related parameters and the Eaton index at the prediction point in the well to be measured p : where P v is the overlying formation pressure, ρ w is the density of water, ρ p is the density of oil or gas, h is the thickness of the oil and gas column below the depth of the prediction point, d is the depth of the prediction point, ρ is the formation density, GR n is the natural gamma on the normal compaction trend line of the well to be measured, GR is the natural gamma in the logging data of the well to be measured, and N is the Eaton index of the well site.

8. For the method according to claim 7, the natural gamma on the normal compaction trend line of the well to be measured is obtained by the following method: According to the logging data of the well to be measured, select the natural gamma under normal compaction conditions, and construct the normal compaction trend line of the well to be measured according to the following formula: lnGR n = a - Cd, wherein, GR n GR is the gamma ray on the normal compaction trend line, a is the gamma ray at zero depth, C is the compaction coefficient, and d is the depth of the prediction point; The overburden pressure is obtained by the following method: According to the logging data of the well to be measured obtained, determine the overlying formation pressure P at the corresponding depth of the well to be measured according to the following formula v : where H is the formation depth, ρ is the formation density, and T is the formation temperature.

9. The method according to claim 1, characterized in that, The determining the formation porosity of the prediction point in the well to be measured according to the rock chemical composition analysis data of the prediction point in the well to be measured under undercompaction conditions includes: Determine the relative molecular mass M of the rock and the rock density ρ according to the rock chemical composition analysis data of the prediction point in the well to be measured under undercompaction conditions; the relative molecular mass of the rock is determined according to the relative molecular masses and mass fractions of the components in the rock; the rock density is calculated according to the volumes and densities of the components in the rock; Determine the formation porosity of the prediction point in the well to be measured according to the relative molecular mass M of the rock and the density ρ of the rock.

10. The method according to claim 9, wherein, determining the relative molecular mass M of the rock according to the relative molecular masses and mass fractions of the components in the rock includes: Determine the relative molecular mass of the rock according to the following formula: where M 0 (i) is the relative molecular mass of the i-th component in the rock, and w(i) is the mass fraction of the i-th component in the rock; calculating the density ρ of the rock according to the volumes and densities of the components in the rock includes: Determine the density of the rock according to the following formula: where V i is the volume of the i-th component in the rock, V is the volume of the rock, and ρ i is the density of the i-th component in the rock; determining the formation porosity of the prediction point in the well to be measured according to the relative molecular mass M of the rock and the density ρ of the rock includes: Determine the formation porosity of the prediction point in the well to be measured according to the following formula where M is the relative molecular mass of the rock and ρ is the rock density.

11. The method according to claim 1, wherein, determining the additional formation pressure at the prediction point under the undercompaction condition according to the formation porosity includes: determining the additional formation pressure at the prediction point under the undercompaction condition according to the maximum porosity of the formation where the prediction point is located, the minimum porosity of the formation where the prediction point is located, the depth of the prediction point, the porosity of the prediction point, and the formation density.

12. The method according to claim 1, wherein, Determine the additional formation pressure E at the prediction point under undercompaction conditions according to the following formula: where η is the correction exponent, is the formation porosity of the prediction point, is the maximum porosity of the formation where the prediction point is located, is the minimum porosity of the formation where the prediction point is located, ρ is the formation density, and d is the depth of the prediction point.

13. The method according to any one of claim 1, wherein, predicting the formation pressure of the prediction point in the well to be measured under the undercompaction condition according to the formation pressure of the prediction point under the normal compaction condition and the additional formation pressure at the prediction point under the undercompaction condition includes: combining the formation pressure of the prediction point under the normal compaction condition and the additional formation pressure at the prediction point under the undercompaction condition, and predicting the formation pressure P of the prediction point in the well to be measured under the undercompaction condition according to the following formula: P = P p + E, where P p is the formation pressure at the prediction point under normal compaction conditions, and E is the additional formation pressure at the prediction point under undercompaction conditions.

14. A formation pressure prediction device based on mineral analysis, wherein, comprising: a data acquisition module for acquiring well logging data of the well to be measured at the well site; a data processing module for determining the formation porosity of the prediction point in the well to be measured according to the rock chemical composition analysis data of the prediction point in the well to be measured under the undercompaction condition; and determining the additional formation pressure at the prediction point under the undercompaction condition according to the formation porosity; a pressure prediction module for predicting the formation pressure of the prediction point in the well to be measured under the normal compaction condition according to the well logging data of the well to be measured acquired at the well site; and predicting the formation pressure of the prediction point in the well to be measured under the undercompaction condition according to the formation pressure of the prediction point under the normal compaction condition and the additional formation pressure at the prediction point under the undercompaction condition.

15. A computer storage medium, wherein, computer-executable instructions are stored in the computer storage medium, and when the computer-executable instructions are executed by a processor, the formation pressure prediction method based on mineral analysis according to any one of claims 1-13 is implemented.

16. A computer device, wherein, comprising: a memory, a processor, and a computer program stored on the memory and executable on the processor, and when the processor executes the program, the formation pressure prediction method based on mineral analysis according to any one of claims 1-13 is implemented.

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