A method for predicting a formation drilling fluid leak-off zone using well logging data

Abstract

This invention discloses a method for predicting easily leaky formations in drilling fluid using well logging data, relating to the field of oil and gas exploration and development. Its key features include: conducting rock and mineral composition, lithology, fracture and pore morphology characteristics, and rock mechanics experiments on five or more adjacent wells of the target formation to reveal the tensile strength properties, leakage channels, and reservoir space characteristics of the target formation, obtaining rock mechanics parameters and in-situ stress; based on the fine subdivision of the target formation, the rock mechanics parameters, in-situ stress, and formation pressure data from the adjacent wells are thinned or interpolated, and the prediction weight is determined according to the distance between adjacent wells and the predicted well to achieve the prediction calculation of the target formation data for the predicted well; furthermore, the collapse pressure, leakage pressure, and fracture pressure of the target formation in the predicted well are calculated and corrected based on the mode to predict easily leaky formations in drilling fluid before drilling. This invention enables precise pre-drilling prediction of easily leaky formations, achieving improved drilling quality and efficiency in complex and easily leaky formations.

Description

Technical Field

[0001] This invention belongs to the field of oil and gas exploration and development, and specifically relates to a method for predicting easily leaking formations of drilling fluid using well logging data. Background Technology

[0002] Drilling fluid loss is a frequent and complex downhole accident in oil and gas drilling operations. Statistics show that global economic losses due to well leakage exceed US$2 billion annually. All time spent from the start of handling drilling fluid loss to its completion is considered non-productive time, accounting for 5% to 15% of the total time spent on oil and gas drilling in my country. Drilling fluid loss downhole accidents not only affect normal drilling efficiency and cause economic losses to enterprises, but if the problem is not properly resolved, it can also lead to other complex drilling safety accidents such as blowouts, collapses, and stuck wells. Therefore, predictive technology for identifying easily leaking formations in the intended drilling well will strongly support wellbore structure optimization and drilling parameter design, thereby significantly reducing drilling fluid loss. This is of paramount practical significance for reducing drilling costs, improving drilling efficiency, and ensuring drilling safety.

[0003] Drilling fluid loss is a complex result influenced by multiple factors, including geological conditions and drilling techniques. Seismic data contains a wealth of fracture-related information and is widely used for predicting the location of leaky formations. Currently, methods for identifying leaky formations using seismic data mainly include: coherence volume technique, shear wave splitting technique, P-wave AVO (Amplitude Various Offset) technique, and AVA (Amplitude Various Angle) technique. Although domestic scholars have attempted to predict the location of leaky formations using raw seismic data, this method can only identify large fault zones, such as faults and major faults. In practical applications of leaky formation prediction, this method still has significant limitations. Using logging and well logging data to evaluate drilling fluid leakage-prone formations involves measuring the physical properties of the wellbore, such as density and sonic velocity, using logging instruments. These physical properties are then converted into rock mechanics parameters using specific theoretical models. This method is fast and efficient. However, logging and well logging data only reflect local geological features around the wellbore and cannot accurately reflect the mechanical properties of the entire formation. Furthermore, this method is implemented during or after drilling, resulting in weak predictive power and limited significance for optimizing the wellbore structure and designing drilling parameters for new wells. In recent years, domestic and international scholars have explored the nonlinear correlation between geology and construction on well leakage risk using machine learning and neural networks. However, well leakage risk prediction based on machine learning and neural networks requires extensive geological data and field well leakage measurement data. A highly reliable predictive model can only be established after training with drilling fluid leakage data from multiple wells. Moreover, the established model is only applicable to the formations of the corresponding research well area, and its application in new well areas with relatively few development wells is still very limited.

[0004] To achieve safe, high-quality, and rapid drilling in complex formations, pre-drilling prediction of easily leaky formations is urgently needed. This invention presents a method for predicting easily leaky formations using drilling fluids based on well logging data. This method, based on laboratory core experiments and well logging interpretation, clarifies the mineral composition and natural fracture development characteristics, rock mechanics parameters, in-situ stress, and formation pressure characteristics of the drilled target formation. It then divides the formation into sub-layers and constructs a profile of the predicted well's rock mechanics parameters, in-situ stress, and formation pressure using thinning or interpolation mapping. Subsequently, it calculates formation leakage pressure, formation fracture pressure, and formation collapse pressure, and performs mode difference correction. Finally, it combines the characteristics of the target formation's leakage channels and reservoir space to achieve pre-drilling prediction of easily leaky formations for drilling fluids. The theoretical basis for this method of predicting easily leaky formations using drilling fluids based on well logging data is as follows:

[0005] 1. Formulas for calculating the dynamic elastic modulus and dynamic Poisson's ratio of rock based on the longitudinal and transverse wave velocities.

[0006] The formulas for calculating the longitudinal and transverse acoustic velocities of rocks are as follows:

[0007]

[0008] In the formula: V p V represents the longitudinal wave velocity of rock, in m / s; s t represents the transverse wave velocity of the rock, in m / s; L represents the length of the rock sample, in mm; p The time in milliseconds (ms) represents the termination time of the longitudinal acoustic wave propagation in the specimen; t represents the time in milliseconds (t). p0 Let Δt be the initial time (ms) of the longitudinal acoustic wave propagating in the specimen; Δt p The propagation time of the longitudinal acoustic wave in the specimen is expressed in milliseconds (ms); t s The time in milliseconds (ms) represents the termination time of the transverse acoustic wave propagation in the specimen; t represents the time in milliseconds (ms). s0 Δt represents the initial time (ms) of the transverse acoustic wave propagating in the specimen; s The propagation time of the transverse acoustic wave in the specimen is expressed in milliseconds (ms).

[0009] The dynamic elastic modulus and Poisson's ratio of the rock are calculated using the following formula:

[0010]

[0011] In the formula: E d The dynamic elastic modulus of rock is given in GPa and μ. d ρ is the dynamic Poisson's ratio of the rock; ρ is the bulk density of the rock, in g / cm³. 3 .

[0012] 2. Formula for calculating the tensile strength of rock

[0013] The tensile strength of rock refers to the maximum stress that a rock can withstand under tensile conditions. The Brazilian splitting method is a standard recommended method by the International Society for Rock Mechanics. Under a concentrated load P, a symmetrical disk specimen is subjected to the following stress state according to elasticity theory: At any point (x, y) on the loading diameter of the disk specimen, the stress state is as follows:

[0014]

[0015]

[0016] In the formula: σ x σ is the stress acting in the x-direction along the loading diameter of the disk specimen, in MPa; y y is the stress acting on the loading diameter of the disk specimen in the y direction, MPa; P is the load, kN; D is the specimen diameter, cm; π is pi, usually taken as 3.14.

[0017] The stress at the center of the specimen (y = 0) is:

[0018]

[0019] From equations (7) and (8), it can be seen that the compressive stress at the center of the disc specimen is three times the tensile stress. However, since the tensile strength of the rock is much lower than its compressive strength, the center will fail once the tensile stress reaches the tensile strength of the specimen. It is generally believed that the tensile stress plays a dominant role in the fracture. Therefore, formula (7) can be used to calculate the tensile strength of the rock.

[0020] 3. Formula for calculating the compressive strength of rock

[0021] In the triaxial test of rock, according to the "Test Procedure for Physical and Mechanical Properties of Rock Part 20: Triaxial Compressive Strength Test of Rock" (DZ / T 0276.20-2015), the axial stress under different confining pressures is calculated using the following formula:

[0022]

[0023] In the formula: σ p A is the axial stress at specimen failure, in MPa; A is the cross-sectional area of ​​the specimen, in cm². 2 Under uniaxial test conditions, the axial stress at specimen failure calculated is the uniaxial compressive strength of the rock. Triaxial compressive strength is often expressed using differential stress S. c This means, that is:

[0024] S c =σ p -σ c (10)

[0025] In the formula: σ c The confining pressure is MPa.

[0026] 4. Formulas for calculating the static elastic modulus and static Poisson's ratio of rock

[0027] The static elastic modulus of rock is the ratio of the axial stress increment to the axial strain increment during the elastic deformation stage of the stress-strain curve obtained from a triaxial compression test of the rock specimen, i.e.:

[0028]

[0029] In the formula: ΔP is the axial load increment during the elastic deformation stage, MPa; ΔL is the axial deformation increment during the elastic deformation stage, mm.

[0030] The static Poisson's ratio of rock is the ratio of the radial strain increment to the axial strain increment in the elastic deformation stage of the stress-strain curve obtained from a triaxial compression test of a rock specimen. Under conventional triaxial compression test conditions, it is usually calculated by substituting the circumferential deformation increment in the elastic deformation stage for the radial strain increment, as shown in the following formula:

[0031]

[0032] In the formula: ΔC is the circumferential deformation increment during the elastic deformation stage, in mm.

[0033] 5. Formula for calculating ground stress in rock acoustic emission test

[0034] The Kaiser effect of rocks can be used to measure the triaxial stress values ​​of rocks within strata. Based on the analysis and acquisition of test stresses in each direction, and according to the spatial relationship of stress components, the magnitude and direction of the horizontal stress at the test point can be calculated from the stress vectors in the three directions through appropriate transformations. The formulas for calculating vertical stress, maximum horizontal stress, and minimum horizontal stress are as follows:

[0035]

[0036] In the formula: σ v For vertical ground stress, MPa; σ H The maximum horizontal ground stress is expressed in MPa; σ h Minimum horizontal ground stress, MPa; σ 丄 P represents the stress value at the Kaiser effect point in the vertical direction of the core, in MPa. P Formation pressure, MPa; σ0°, σ 45 °、σ 90 ° represents the stress values ​​at the Kaiser effect points in the core sample at three horizontal directions: 0°, 45°, and 90°, in MPa; φ represents the angle between the rock sample axis and the direction of the maximum horizontal principal stress, in °.

[0037] 6. Mohr-Coulomb strength criterion

[0038] Rock failure is primarily shear failure. The force resisting failure on the shear surface is the rock's shear strength, which equals the rock's cohesive force resisting shear failure plus the frictional force generated by the normal force on the shear surface. The shear strength criterion in a plane is:

[0039]

[0040] In the formula: τ is the shear strength of the rock, MPa; C is the cohesion of the rock, MPa; σ is the normal stress, MPa; Let be the internal friction angle of the rock, in °.

[0041] The Mohr-Coulomb strength criterion for rocks under triaxial stress conditions, expressed using the maximum and minimum principal stresses, is as follows:

[0042]

[0043] In the formula: σ1 represents the maximum principal stress, MPa; σ3 represents the minimum principal stress, MPa.

[0044] Considering formation pressure P P When, formula (18) is expressed in terms of effective stress:

[0045]

[0046] In the formula: α is the effective stress coefficient, 0<α<1. For mudstone and shale formations, α can be taken as 0.5~0.6, for sandstone α = 0.7~0.9, and for high-permeability formations α = 1.

[0047] 7. Formulas for calculating dynamic mechanical parameters of rocks

[0048] The formula for calculating the dynamic uniaxial compressive strength of rock is as follows:

[0049] S c =0.0026×E d ×(1-V sh )+0.008×E×V sh (20)

[0050] In the formula: S c The dynamic uniaxial compressive strength of the rock sample is given in MPa; Va sh The mud content of the rock sample is %.

[0051] The formula for calculating the dynamic shear strength of rock is as follows:

[0052]

[0053] In the formula: S s denoted as the dynamic shear strength of the rock sample, in MPa.

[0054] The formula for calculating the dynamic tensile strength of rock is as follows:

[0055] S t =1.263 + 0.386 × S s (twenty two)

[0056] In the formula: S t denoted as the dynamic tensile strength of the rock sample, in MPa.

[0057] 8. Formation pressure calculation model

[0058] The Eaton method is a method for evaluating formation pressure using layer velocity, the Dc index, sonic logging, resistivity logging, density logging, and shale density. Its principle is that the relationship between the ratio of the actual value to the normal trend value of compaction parameters and formation pressure is determined by the change in the overlying pressure gradient. The general calculation model for the Eaton method is as follows:

[0059] P P =P0-(P0-P W (Q / Q′) c (twenty three)

[0060] Where: P0 is the overlying formation pressure, MPa; P W The hydrostatic pressure of the formation water column (generally ρ) w =1g / cm 3 ~1.07g / cm 3 Freshwater concentration is 1 g / cm³ 3 The saline solution concentration was 1.05 g / cm³. 3 ), MPa; c is the compaction index; Q and Q' are the selected logging or drilling parameters, which are sonic transit time, resistivity, formation velocity, and Dc exponent, respectively, and satisfy L / L'<1. When the selected parameters increase with depth, Q / Q' represents the ratio of the measured value to the standard value, and vice versa. Therefore, when using sonic transit time logging data, since the sonic transit time gradually decreases with depth, Q / Q' represents the ratio of the standard sonic transit time to the measured sonic transit time, and thus:

[0061] P P =P0-(P0-P W )(Δt n / Δt c ) c (twenty four)

[0062] Where: Δt c Δt represents the measured values ​​from acoustic transit time logging, in μs / ft; n The sonic transit time value is shown on the normal compaction trend line, in μs / ft.

[0063] The key to calculating formation pressure using the Eaton method based on acoustic transit time lies in constructing the normal compaction trend line and the compaction index c. However, the compaction index c varies depending on the formation conditions in different regions, so directly using this empirical coefficient will inevitably lead to significant errors in the prediction results. Therefore, it is necessary to recalculate the value of c, which is calculated as follows:

[0064]

[0065] 9. Dynamic geostress calculation model

[0066] The formula for calculating dynamic vertical ground stress is as follows:

[0067]

[0068] In the formula: H is the formation depth, m; ρ(z) is the formation density at depth z, g / cm³. 3 g is the acceleration due to gravity, m / s² 2 Generally, it goes to 9.8 m / s 2 .

[0069] The formula for calculating dynamic horizontal ground stress is as follows:

[0070]

[0071] Where: ε h ε H These are the two orthogonal principal strain components of the rock element in the horizontal direction, which are dimensionless.

[0072] 10. Calculation model for formation collapse pressure

[0073] When the hydraulic pressure inside the wellbore is lower than the formation collapse pressure, the wellbore rock will undergo shear failure. If the rock is ductile, it will undergo plastic flow into the well, leading to borehole narrowing; brittle rock will cause collapse and spalling, resulting in borehole enlargement and stuck pipe. When the hydraulic pressure inside the wellbore is greater than the formation collapse pressure, the combined effect of in-situ stress and the hydraulic pressure creates stress conditions below the rock's shear strength, preventing wellbore rock failure and maintaining wellbore stability.

[0074] According to the theory of elasticity, under triaxial geostress, the wellbore stress in cylindrical coordinates is expressed as:

[0075]

[0076] In the formula: σ r σ represents the radial stress of the wellbore in cylindrical coordinates, in MPa; θ σ represents the circumferential stress of the wellbore in cylindrical coordinates, in MPa; z P represents the axial stress on the wellbore in cylindrical coordinates, in MPa. m The value is the drilling fluid column pressure, expressed in MPa.

[0077] When the fluid column pressure inside the wellbore equals the formation collapse pressure, substituting formula (28) into formula (19) yields the following formula for calculating the formation collapse pressure:

[0078]

[0079] In the formula: P b Where is the formation collapse pressure, MPa; η is the nonlinear stress correction factor for the wellbore rock, typically taken as 0.95; the formula for calculating K is as follows:

[0080]

[0081] 11. Formation fracture pressure calculation model

[0082] Currently, there are many methods for calculating formation fracture pressure using well logging data. The improved Tan model method, which comprehensively considers formation pressure, overlying strata pressure, and rock tensile strength, is widely used. Its expression is as follows:

[0083]

[0084] In the formula: P f Formation fracture pressure, MPa; μ b S is the structural stress coefficient; μ is Poisson's ratio; S t denoted as the tensile strength of the rock, in MPa.

[0085] 12. Formation Leakage Pressure Calculation Model

[0086] When the formation is a fractured or porous formation, the drilling fluid flow into the formation no longer requires tensile failure of the rock, that is, the formation leakage pressure does not need to consider the tensile strength of the rock. Therefore, the formation leakage pressure calculation model is obtained according to formula (31):

[0087] Summary of the Invention

[0088] The purpose of this invention is to solve the problem of the difficulty in effectively predicting the easily leaking formations of drilling fluid before drilling. To this end, a method for predicting easily leaking formations of drilling fluid using well logging data is proposed.

[0089] The technical solution adopted in this invention is as follows:

[0090] Step 1.1: Based on the interpretation of logging data from 5 or more adjacent wells of the target formation, construct logging interpretation profiles for corrected rock mechanical parameters and corrected geostress values ​​of the target formation in the adjacent wells. Rock mechanical parameters include tensile strength, uniaxial compressive strength, triaxial compressive strength, elastic modulus, and Poisson's ratio. Also, construct logging interpretation profiles for formation pressure, formation collapse pressure, formation leakage pressure, and formation fracture pressure of the target formation in 5 or more adjacent wells of the target formation.

[0091] Step 1.2: Based on the analysis of rock and mineral composition testing, electron microscopy, thin section identification and imaging logging of the target formation in 5 or more adjacent wells, clarify the lithology, fracture development and occurrence and pore development of the target formation in the adjacent wells. Reveal the tensile strength performance, formation leakage channels and reservoir space characteristics of the target formation in the adjacent wells from the perspective of rock lithology and structural characteristics.

[0092] Step 1.3: Based on the well logging interpretation profiles of the target formation with corrected rock mechanics parameters and corrected geostress values ​​from 5 or more adjacent wells, as well as the well logging interpretation profiles of formation pressure, formation collapse pressure, formation leakage pressure and formation fracture pressure, and combined with the natural gamma curve, resistivity curve and sonic curve of the target formation from the adjacent wells, the target formation is finely divided into sub-layers.

[0093] Step 1.4: Based on the results of the fine division of the target formation into smaller layers, use the rock mechanics parameter correction values, geostress correction values, and formation pressure data obtained from the interpretation of acoustic logging data of 5 or more adjacent wells of the target formation, and perform data thinning or interpolation.

[0094] Step 1.5: Based on the distance between 5 or more sample neighboring wells and the predicted well, obtain the prediction weight value of each sample neighboring well;

[0095] Step 1.6: Based on the prediction weight values ​​of 5 or more adjacent wells, use the corrected values ​​of rock mechanics parameters, geostress, and formation pressure of the target formation of the 5 or more adjacent wells to calculate the weighted average to obtain the rock mechanics parameters, geostress, and formation pressure of the target formation of the predicted well.

[0096] Step 1.7: Based on the rock mechanical parameters, geostress, and formation pressure of the target formation in the predicted well, construct well logging interpretation profiles for formation collapse pressure, formation leakage pressure, and formation fracture pressure of the target formation in the predicted well;

[0097] Step 1.8: Correct the logging interpretation profile of formation collapse pressure, formation leakage pressure and formation fracture pressure of the target formation in the predicted well using the mode difference;

[0098] Step 1.9: Based on the formation collapse pressure, formation leakage pressure and formation fracture pressure logging interpretation profiles of the target formation of the predicted well, and in combination with the leakage channels and reservoir space characteristics of the target formation, determine the drilling fluid leakage-prone layers of the target formation of the predicted well.

[0099] Furthermore, the specific steps of step 1.1 are as follows:

[0100] Step 1.1.5: Based on the interpretation of acoustic logging data of the target formation from 5 or more adjacent wells, calculate and obtain the dynamic rock mechanics parameters and dynamic geostress logging interpretation values ​​of the target formation from the adjacent wells. Based on the dynamic and static rock mechanics parameters and geostress conversion model of the target formation from the adjacent wells, correct the dynamic rock mechanics parameters and dynamic geostress logging interpretation values ​​of the target formation from the adjacent wells to obtain the corrected rock mechanics parameters and geostress logging interpretation profiles of the target formation from the adjacent wells.

[0101] Step 1.1.6: Using well logging interpretation profiles with corrected values ​​of rock mechanics parameters and geostress of the target formation from 5 or more adjacent wells, calculate and construct well logging interpretation profiles of formation pressure, formation collapse pressure, formation leakage pressure and formation fracture pressure of the target formation from the adjacent wells based on the calculation model of formation pressure, formation collapse pressure, formation leakage pressure and formation fracture pressure.

[0102] Furthermore, the specific steps of step 1.2 are as follows:

[0103] Step 1.2.1: Using an X-ray diffractometer, test downhole rock samples from 5 or more adjacent wells of the target formation, and determine the rock and mineral composition by observing the characteristic peak intensities in specific X-ray spectra of the rocks and minerals.

[0104] Step 1.2.2: Cut and obtain fresh cross-sections of rock samples from 5 or more adjacent wells of the target formation. Use scanning electron microscopy to observe and clarify the microscopic fracture and pore morphology characteristics of the fresh cross-sections of the rock samples.

[0105] Step 1.2.3: Prepare thin sections of downhole rock samples from 5 or more adjacent wells of the target formation. Use a polarizing microscope to identify the thin sections and clarify the rock lithology, microscopic fracture and pore morphology.

[0106] Step 1.2.4: Use acoustic imaging logging technology to obtain high-resolution imaging logging interpretation images of the target formation in 5 or more adjacent wells, and reveal the development characteristics of natural fractures and dissolution cavities and specific stratigraphic positions based on the imaging logging interpretation images;

[0107] Step 1.2.5: Based on the rock mineral composition, microscale fracture and pore morphology, rock lithology, microscale fracture and pore morphology, development characteristics of natural fractures and dissolution cavities, and specific stratigraphic positions, reveal the tensile strength properties, leakage channels, and reservoir space characteristics of the target strata rocks.

[0108] Furthermore, the specific steps of step 1.3 are as follows:

[0109] Step 1.3.1: Based on the well logging interpretation profiles of corrected rock mechanical parameters and corrected geostress values ​​of the target formation from 5 or more adjacent wells, and the well logging interpretation profiles of formation pressure, perform preliminary stratification of the target formation;

[0110] Step 1.3.2: Analyze the target formation logging curve data from 5 or more adjacent wells, extract abrupt change characteristic points from the natural gamma logging curves to determine the lithological interface; identify the oil-water interface and gas-bearing show zones through resistivity logging curve morphology analysis to determine fluid properties; use sonic transit time logging data to determine lithology and porosity changes by comparing the sonic transit time range of standard lithology; identify pressure anomaly zones and determine pressure characteristic changes based on the logging interpretation profiles of formation collapse pressure, formation leakage pressure, and formation fracture pressure; further, based on the preliminary stratification of the target formation, perform fine sub-layer division of the target formation.

[0111] Furthermore, the specific steps of step 1.4 are as follows:

[0112] Step 1.4.1: Based on the target formation thickness of 5 or more adjacent wells and the original data sampling interval, calculate the corrected values ​​of rock mechanics parameters, geostress, and formation pressure data for each sub-layer of the target formation in the adjacent wells. The formula is as follows:

[0113]

[0114] Where: n sl H represents the corrected values ​​for rock mechanics parameters, geostress, and formation pressure in the l-th sub-layer of the target formation adjacent to the sample well, where l is an integer; sl The thickness of the l-th layer is m; N is the original data sampling interval, m, typically 0.125 m.

[0115] Step 1.4.2: Calculate the corrected values ​​of rock mechanics parameters, geostress, and total formation pressure data of the target formation from 5 or more adjacent wells. The formula is as follows:

[0116]

[0117] Where: n s The total amount of data for corrected rock mechanical parameters, corrected geostress, and formation pressure of the target formation in adjacent wells is an integer; L is the total number of layers, an integer.

[0118] Step 1.4.3: Calculate the thickness H of each sub-layer of the target formation in the predicted well. tl Thickness H of each sub-layer of the target formation adjacent to 5 or more sample wells sl ratio m l The formula is as follows:

[0119]

[0120] Step 1.4.4, when m l When the value is less than 1, the corrected values ​​of rock mechanics parameters, geostress, and formation pressure data of the corresponding sub-layers in adjacent wells are thinned out, and the number of data extraction intervals is calculated using the following formula:

[0121]

[0122] In the formula: k rl For the number of extraction intervals of rock mechanics parameter correction values, geostress correction values, and formation pressure data, an integer;

[0123] Corrected values ​​for rock mechanics parameters, in-situ stress, and formation pressure data of the target formation in adjacent wells at k intervals. rl One data point is extracted for each sample, and the extracted data is the corrected value of the rock mechanical parameters, the corrected value of the in-situ stress, and the formation pressure data of the corresponding sub-layer of the predicted well mapped by the adjacent well of that sample.

[0124] Step 1.4.5: When m>1, interpolate the corrected values ​​of rock mechanics parameters, geostress, and formation pressure data of the corresponding sublayers in the adjacent wells of the sample, and calculate the number of interpolations between adjacent data. The formula is as follows:

[0125] k il =round(m l -1)

[0126] In the formula: k il The number of interpolations between adjacent data points, an integer;

[0127] k-values ​​of corrected rock mechanics parameters, corrected geostress values, and formation pressures for each sub-layer of the target formation in adjacent wells were analyzed. il Linear interpolation of the data yields the corrected values ​​of rock mechanics parameters, geostress, and formation pressure of the adjacent wells in the corresponding sub-layers of the predicted well.

[0128] Furthermore, the specific steps of step 1.5 are as follows:

[0129] Step 1.5.1: Based on the layout diagram of adjacent wells and predicted wells of 5 or more samples, calculate the distance between adjacent wells and predicted wells;

[0130] Step 1.5.2: Based on the distances between five or more adjacent wells and the predicted well, calculate the prediction weight value for each adjacent well, using the following formula:

[0131]

[0132] In the formula: q k x represents the predicted weight value of the adjacent wells in the k-th sample, which is dimensionless; k The distance between the sample well and the predicted well, in meters;

[0133] Step 1.5.3: Normalize the prediction weight values ​​of adjacent wells for samples of 5 or more, using the following formula:

[0134]

[0135] In the formula: p k is the predicted weight value after normalization of the neighboring wells of the k-th sample, and is dimensionless.

[0136] Furthermore, the specific steps of step 1.6 are as follows:

[0137] Step 1.6.1: Based on the corrected values ​​of rock mechanics parameters, in-situ stress, and formation pressure of 5 or more adjacent wells mapped to the corresponding sub-layers of the prediction well, and using the normalized prediction weight values ​​of each adjacent well, calculate the prediction components of the target formation rock mechanics parameters, in-situ stress, and formation pressure of each adjacent well for the prediction well. The formula is as follows:

[0138] w k =s k p k

[0139] In the formula: w k s refers to the predicted components of the rock mechanical parameters, in-situ stress, and formation pressure of the target formation in the k-th sample well for the predicted well; k This refers to the rock mechanical parameters, geostress, and formation pressure of the target formation adjacent to the k-th sample well.

[0140] Step 1.6.2: Based on the predicted components of the target formation rock mechanical parameters, in-situ stress, and formation pressure of the predicted well from 5 or more adjacent wells, sum and calculate the target formation rock mechanical parameters, in-situ stress, and formation pressure of the predicted well, as shown in the following formula:

[0141] s=∑w k

[0142] In the formula: s represents the rock mechanical parameters, geostress, and formation pressure of the target formation in the predicted well.

[0143] Furthermore, the specific steps of step 1.7 are as follows:

[0144] Step 1.7.1: Based on the predicted formation stress and formation pressure of the target formation in the well, perform stress coordinate axis transformation, establish a wellbore cylindrical coordinate stress distribution model centered on the wellbore axis, and obtain the maximum principal stress and minimum principal stress of the wellbore cylindrical coordinate system;

[0145] Step 1.7.2: Based on the rock mechanics parameters of the target formation in the predicted well, formation pressure, and the maximum and minimum principal stresses in the wellbore cylindrical coordinate system, calculate and construct the well logging interpretation profile of the formation collapse pressure, formation leakage pressure, and formation fracture pressure of the target formation in the predicted well, based on the calculation model of formation collapse pressure, formation leakage pressure, and formation fracture pressure.

[0146] Furthermore, the specific steps of step 1.8 are as follows:

[0147] Step 1.8.1: Perform a weighted average of the mode of formation collapse pressure, formation leakage, and formation fracture pressure for the target formation in 5 or more adjacent wells, using the following formula:

[0148] z s =∑z k p k

[0149] In the formula: z s The z represents the mode of formation collapse pressure, formation leakage pressure, and formation fracturing pressure in the target formation after weighted average processing, in MPa; k The mode of formation collapse pressure, formation leakage pressure, and formation fracture pressure of the target formation in the adjacent well of the k-th sample, in MPa;

[0150] Step 1.8.2: Using the weighted average processed mode of formation collapse pressure, formation leakage pressure, and formation fracture pressure of the target formation, calculate and construct the corrected value profiles of formation collapse pressure, formation leakage pressure, and formation fracture pressure of the target formation in the predicted well, based on the well logging interpretation profile data of the formation collapse pressure, formation leakage pressure, and formation fracture pressure of the target formation in the predicted well. The formula is as follows:

[0151] Df jz =Df+(z s -z)

[0152] In the formula: Df jz The corrected values ​​for formation collapse pressure, formation leakage pressure, and formation fracture pressure of the target formation in the predicted well are represented in MPa; Df represents the well logging interpretation value of formation collapse pressure, formation leakage pressure, or formation fracture pressure of the target formation in the predicted well, in MPa; z is the mode of formation collapse pressure, formation leakage pressure, and formation fracture pressure of the target formation in the predicted well.

[0153] Furthermore, the specific steps of step 1.9 are as follows:

[0154] Step 1.9.1: Based on the profile of formation pressure, formation collapse pressure, formation leakage pressure and formation fracture pressure correction values ​​of the target formation of the predicted well, find the low value areas of formation leakage pressure and formation fracture pressure of the target formation of the predicted well, as well as the areas where the difference between formation pressure and formation collapse pressure and formation leakage pressure and formation fracture pressure is small.

[0155] Step 1.9.2: Based on the characteristics of the target formation leakage channels and reservoir space, in areas with low formation leakage pressure and formation fracture pressure in the target formation of the predicted well, and in areas where the difference between formation pressure and formation collapse pressure and formation leakage pressure and formation fracture pressure is small, determine whether formation leakage channels and reservoir space are developed. If formation leakage channels and reservoir space are developed, they are identified as fractured leakage risk formations. If formation fracture pressure is low but formation leakage channels and reservoir space are not developed, they are identified as fractured leakage risk formations.

[0156] In summary, due to the adoption of the above technical solution, the beneficial effects of the present invention are:

[0157] 1. In this invention, the calculation of formation collapse pressure, formation leakage pressure and formation fracture pressure of the target formation of the predicted well adopts a series of optimization calculation and correction methods, including proportional mapping of small layer thickness, proportional conversion of inter-well distance, weighted average calculation of basic parameter distance and mode difference correction, which improves the accuracy of the calculation of formation collapse pressure, formation leakage pressure and formation fracture pressure of the target formation of the predicted well.

[0158] 2. This invention fully considers the characteristics of formation leakage channels and reservoir space, and combines accurate prediction of formation collapse pressure, formation leakage pressure and formation fracture pressure, which can accurately determine the type of drilling fluid leakage, providing a reliable basis for the prevention and control of formation drilling fluid leakage.

[0159] 3. In this invention, by utilizing logging data from 5 or more adjacent wells and combining it with rock physics and mechanics experimental results, it is possible to predict the drilling fluid leakage zones in the target formation of a new well before drilling. This provides guidance for proactive prevention of formation drilling fluid loss before drilling. Compared with traditional post-drilling evaluation and treatment methods, this invention transforms post-drilling formation drilling fluid loss treatment into pre-drilling prevention, which can better reduce the risk of drilling fluid loss in oil and gas drilling and achieve improved quality and efficiency in new well drilling. Attached Figure Description

[0160] Figure 1 Flowchart of a method for predicting easily leaking formations using well logging data

[0161] Figure 2 Data map of the Maokou Formation sub-layers in the case well area

[0162] Figure 3 A schematic diagram of the sub-layer division of the Maokou Formation in the case well area.

[0163] Figure 4 A comparison chart of predicted and interpreted rock mechanical parameters of the Maokou Formation in an example well.

[0164] Figure 5 Example: Concordance rate curve between predicted and interpreted rock mechanical parameters of the Maokou Formation in well Maokou.

[0165] Figure 6 This is a comparison chart of predicted and interpreted values ​​of formation collapse pressure, formation leakage pressure, and formation fracture pressure in the Maokou Formation of an example well.

[0166] Figure 7 Example well: Concordance rate curves between predicted and interpreted values ​​of formation collapse pressure, formation leakage pressure, and formation fracture pressure in the Maokou Formation.

[0167] Figure 8 A comparison chart of predicted and corrected values ​​and well logging interpretation values ​​for formation collapse pressure, formation leakage pressure, and formation fracture pressure in the Maokou Formation of an example well.

[0168] Figure 9 Example well Maokou Formation formation collapse pressure, formation leakage pressure, and formation fracture pressure prediction correction values ​​and well logging interpretation values ​​consistency curves

[0169] Figure 10 Example well: Final prediction results and leakage risk analysis diagram of formation collapse pressure, formation leakage pressure, and formation fracture pressure in the Maokou Formation. Detailed Implementation

[0170] 1. Based on the interpretation of target formation logging data from 5 or more adjacent wells, construct the target formation of the adjacent wells.

[0171] Well logging interpretation profiles for corrected rock mechanical parameters and in-situ stress of the formation were constructed. Rock mechanical parameters included tensile strength, uniaxial compressive strength, triaxial compressive strength, elastic modulus, and Poisson's ratio. Well logging interpretation profiles for formation pressure, formation collapse pressure, formation loss pressure, and formation fracture pressure of the target formation were also constructed from five or more adjacent wells. The specific process is as follows:

[0172] (1) The rock sample was tested according to the experimental procedure for acoustic wave transit time. The core length (L) and the termination time (t) of the longitudinal wave propagation in the specimen were obtained from the test. p The termination time (t) of transverse acoustic wave propagation in the specimen. s The initial time (t) of longitudinal acoustic wave propagation in the specimen. p0 ) and the initial time (t) of the propagation of the transverse acoustic wave in the specimen. s0 The longitudinal and transverse acoustic velocities of rock samples from five or more adjacent wells are calculated using formulas (1) and (2).

[0173] (2) By conducting rock tensile strength tests, rock uniaxial compressive strength tests, and rock triaxial compressive strength tests, rock mechanical parameters of downhole rock samples from five or more adjacent wells were obtained. The rock mechanical parameters include tensile strength, uniaxial compressive strength, triaxial compressive strength, elastic modulus, and Poisson's ratio. The calculation formulas are shown in formulas (7), (9), (10), (11), and (12), respectively.

[0174] (3) Obtain the in-situ stress values ​​of downhole rock samples from five or more adjacent wells of the target formation through rock acoustic emission in-situ stress testing experiments. The calculation formulas are shown in formulas (13), (14) and (15).

[0175] (4) Based on the rock acoustic velocity of the target formation downhole rock samples from 5 or more adjacent wells, calculate the dynamic uniaxial compressive strength, dynamic shear strength, dynamic tensile strength, dynamic elastic modulus, dynamic Poisson's ratio, and dynamic geostress of the target formation downhole rock in the adjacent wells. The calculation formulas are shown in formulas (20), (21), (22), (3), (4), (26), and (27), respectively. Combined with the experimental values ​​of rock mechanical parameters and geostress obtained from the experimental test, construct the dynamic and static rock mechanical parameters and geostress conversion model of the target formation in the adjacent wells.

[0176] (5) Based on the interpretation of acoustic logging data of the target formation in 5 or more adjacent wells, calculate the dynamic uniaxial compressive strength, dynamic shear strength, dynamic tensile strength, dynamic elastic modulus, dynamic Poisson's ratio, and dynamic geostress logging interpretation values ​​of the target formation in the adjacent wells. Based on the dynamic and static rock mechanics parameters and geostress conversion model of the target formation in the adjacent wells, correct the dynamic rock mechanics parameters and dynamic geostress logging interpretation values ​​of the target formation in the adjacent wells to obtain the logging interpretation profile of the corrected rock mechanics parameters and geostress values ​​of the target formation in the adjacent wells.

[0177] (6) Using the corrected values ​​of rock mechanics parameters and geostress of the target formation in five or more adjacent wells, the well logging interpretation profiles of formation pressure, formation collapse pressure, formation leakage pressure and formation fracture pressure are calculated based on the calculation model of formation pressure, formation collapse pressure, formation leakage pressure and formation fracture pressure, see formula (24), formula (29), formula (32) and formula (31), and the well logging interpretation profiles of formation pressure, formation collapse pressure, formation leakage pressure and formation fracture pressure of the target formation in the adjacent wells are constructed.

[0178] 2. Based on the analysis of rock and mineral composition testing, electron microscopy, thin section identification, and imaging logging of the target formation from five or more adjacent wells, clarify the lithology, fracture development and occurrence, and pore development of the target formation in the adjacent wells. Reveal the tensile strength, formation loss channels, and reservoir space characteristics of the target formation from the perspective of rock lithology and structural features. Specific methods are as follows:

[0179] (1) Using an X-ray diffractometer, test downhole rock samples from 5 or more adjacent wells of the target formation, and determine the rock and mineral composition by observing the characteristic peak intensity in the specific X-ray spectrum of the rock and mineral.

[0180] (2) Fresh cross sections of rock samples from five or more adjacent wells were obtained by cutting. The fresh cross sections of the rock samples were observed by scanning electron microscopy using a FEI Quanta650FEG field emission scanning electron microscope to obtain the microscopic fracture and pore morphology characteristics of the fresh cross sections.

[0181] (3) Select rock samples from 5 or more adjacent wells of the target formation with obvious surface structural features and well-developed pores, cavities, and fractures for slicing. The diameter of the sliced ​​rock samples should not exceed 25 mm, and the thickness should be between 2 mm and 3.5 mm. Use a polarizing microscope to identify the cast thin sections to clarify the rock lithology and the morphological characteristics of fractures and pores at the microscale.

[0182] (4) Use acoustic imaging logging technology to obtain high-resolution imaging logging interpretation images of the target formation of 5 or more adjacent wells, and reveal the development characteristics of natural fractures and dissolution cavities and specific strata based on the imaging logging interpretation images.

[0183] (5) Based on the rock mineral composition, microscale fracture and pore morphology, rock lithology, microscale fracture and pore morphology, natural fracture and dissolution cavity development characteristics and specific stratigraphic position, reveal the tensile strength performance, leakage channels and reservoir space characteristics of the target strata rocks.

[0184] 3. Based on the well logging interpretation profiles of corrected rock mechanics parameters and geostress values ​​of the target formation from 5 or more adjacent wells, as well as well logging interpretation profiles of formation pressure, formation collapse pressure, formation leakage pressure, and formation fracture pressure, and combined with the natural gamma ray curves, resistivity curves, and sonic curves of the target formation from adjacent wells, the target formation is finely divided into sub-layers. The specific method is as follows:

[0185] (1) Based on the well logging interpretation profiles of corrected rock mechanical parameters and corrected geostress values ​​of the target formation from 5 or more adjacent wells, and well logging interpretation profiles of formation pressure, the target formation is initially stratified.

[0186] (2) Analyze the logging curve data of the target formation from 5 or more adjacent wells, extract the abrupt change feature points of the natural gamma logging curve to determine the lithological interface; identify the oil-water interface and gas-bearing show intervals through resistivity logging curve morphology analysis to determine the fluid properties; use sonic transit time logging data to determine the lithology and porosity changes by comparing the sonic transit time range of standard lithology; identify pressure anomaly zones and determine pressure characteristic changes based on the logging interpretation profiles of formation collapse pressure, formation leakage pressure and formation fracture pressure; further, on the basis of the preliminary stratification of the target formation, carry out fine sub-division of the target formation.

[0187] 4. Based on the detailed sub-layer division results of the target formation, and using the rock mechanics parameter correction values, geostress correction values, and formation pressure data obtained from interpreting sonic logging data from 5 or more adjacent wells, perform data thinning or interpolation. The specific methods are as follows:

[0188] (1) Based on the target formation thickness of 5 or more adjacent wells and the original data sampling interval, calculate the corrected values ​​of rock mechanics parameters, geostress, and formation pressure data for each sub-layer of the target formation in the adjacent wells. The formula is as follows:

[0189]

[0190] Where: n sl H represents the corrected values ​​for rock mechanics parameters, geostress, and formation pressure in the l-th sub-layer of the target formation adjacent to the sample well, where l is an integer; sl The thickness of the l-th layer is m; N is the original data sampling interval, m, typically 0.125 m.

[0191] (2) Calculate the corrected values ​​of rock mechanics parameters, geostress, and total formation pressure data of the target formation from 5 or more adjacent wells using the following formula:

[0192]

[0193] Where: n s The total amount of data for corrected rock mechanics parameters, corrected geostress, and formation pressure of the target formation in the adjacent wells is an integer; L is the total number of layers, an integer.

[0194] (3) Calculate the thickness H of each sub-layer of the target formation in the predicted well. tl Thickness H of each sub-layer of the target formation adjacent to 5 or more sample wells sl ratio m l The formula is as follows:

[0195]

[0196] (4) When m lWhen the value is less than 1, the corrected values ​​of rock mechanics parameters, geostress, and formation pressure data of the corresponding sub-layers in adjacent wells are thinned out, and the number of data extraction intervals is calculated using the following formula:

[0197]

[0198] In the formula: k rl This is the number of intervals for extracting rock mechanics parameter corrections, geostress corrections, and formation pressure data; it is an integer.

[0199] Corrected values ​​for rock mechanics parameters, in-situ stress, and formation pressure data of the target formation in adjacent wells at k intervals. rl One data point is extracted for each sample well. The extracted data represents the corrected values ​​of rock mechanics parameters, geostress, and formation pressure of the corresponding sub-layer of the predicted well, which are mapped from the adjacent wells of that sample.

[0200] (5) When m>1, interpolate the corrected values ​​of rock mechanics parameters, geostress, and formation pressure data of the corresponding sub-layers of the adjacent wells, and calculate the number of interpolations between adjacent data. The formula is as follows:

[0201] k il =round(m l -1) (37)

[0202] In the formula: k il The number of interpolations between adjacent data points, an integer;

[0203] k-values ​​of corrected rock mechanics parameters, corrected geostress values, and formation pressures for each sub-layer of the target formation in adjacent wells were analyzed. il Linear interpolation of the data yields the corrected values ​​of rock mechanics parameters, geostress, and formation pressure of the adjacent wells in the corresponding sub-layers of the predicted well.

[0204] 5. Based on the distances between five or more adjacent wells and the predicted well, obtain the prediction weight value for each adjacent well. The specific method is as follows:

[0205] (1) Calculate the distance between the sample neighboring wells and the predicted wells based on the layout diagram of 5 or more sample neighboring wells and the predicted wells.

[0206] (2) Calculate the prediction weight value of each sample well based on the distance between the adjacent wells of 5 or more samples and the predicted well, using the following formula:

[0207]

[0208] In the formula: q k x represents the predicted weight value of the adjacent wells in the k-th sample, which is dimensionless; k Let m be the distance between the sample well and the predicted well.

[0209] (3) The prediction weight values ​​of adjacent wells for samples of 5 or more wells are normalized using the following formula:

[0210]

[0211] In the formula: p k is the predicted weight value after normalization of the neighboring wells of the k-th sample, and is dimensionless.

[0212] 6. Based on the prediction weight values ​​of 5 or more adjacent wells, and using the corrected values ​​of rock mechanics parameters, in-situ stress, and formation pressure of the target formation from the 5 or more adjacent wells, a weighted average calculation is performed to obtain the rock mechanics parameters, in-situ stress, and formation pressure of the target formation in the predicted well. The specific method is as follows:

[0213] (1) Based on the corrected values ​​of rock mechanics parameters, geostress, and formation pressure of five or more adjacent wells mapped to the corresponding sub-layers of the prediction well, and using the normalized prediction weight values ​​of each adjacent well, calculate the prediction components of the target formation rock mechanics parameters, geostress, and formation pressure of each adjacent well for the prediction well. The formula is as follows:

[0214] w k =s k p k (40)

[0215] In the formula: w k s refers to the predicted components of the rock mechanical parameters, in-situ stress, and formation pressure of the target formation in the k-th sample well for the predicted well; k This refers to the rock mechanical parameters, geostress, and formation pressure of the target formation adjacent to the k-th sample well.

[0216] (2) Based on the predicted components of the target formation rock mechanical parameters, in-situ stress, and formation pressure of the predicted well from 5 or more adjacent sample wells, the predicted formation rock mechanical parameters, in-situ stress, and formation pressure of the predicted well are summed and calculated using the following formula:

[0217] s=∑w k (41)

[0218] In the formula: s represents the rock mechanical parameters, geostress, and formation pressure of the target formation in the predicted well.

[0219] 7. Based on the rock mechanics parameters, in-situ stress, and formation pressure of the target formation in the predicted well, construct well logging interpretation profiles for formation collapse pressure, formation loss pressure, and formation fracture pressure of the target formation in the predicted well. The specific method is as follows:

[0220] (1) Based on the predicted formation stress and formation pressure of the target formation in the well, stress coordinate axis transformation is performed to establish a wellbore column coordinate stress distribution model centered on the wellbore axis, and the maximum principal stress and minimum principal stress of the wellbore column coordinate system are obtained.

[0221] (2) Based on the rock mechanics parameters of the target formation of the predicted well, formation pressure, maximum principal stress and minimum principal stress in the wellbore cylindrical coordinate system, and based on the calculation model of formation collapse pressure, formation leakage pressure and formation fracture pressure, calculate and construct the well logging interpretation profile of formation collapse pressure, formation leakage pressure and formation fracture pressure of the target formation of the predicted well.

[0222] 8. Utilize mode differences to correct the logging interpretation profiles of formation collapse pressure, formation leakage pressure, and formation fracture pressure in the target formation of the predicted well. The specific method is as follows:

[0223] (1) The mode of formation collapse pressure, formation leakage, and formation fracture pressure of the target formation in adjacent wells of 5 or more samples are weighted and averaged, and the formula is as follows:

[0224] z s =∑z k p k (42)

[0225] In the formula: z s The z represents the mode of formation collapse pressure, formation leakage pressure, and formation fracturing pressure in the target formation after weighted average processing, in MPa; k The mode of formation collapse pressure, formation leakage pressure, and formation fracture pressure of the target formation in the adjacent well of the k-th sample is given in MPa.

[0226] (2) Using the weighted average processed mode of formation collapse pressure, formation leakage pressure, and formation fracture pressure of the target formation, and based on the well logging interpretation profile data of formation collapse pressure, formation leakage pressure, and formation fracture pressure of the target formation in the predicted well, calculate and construct the corrected value profile of formation collapse pressure, formation leakage pressure, and formation fracture pressure of the target formation in the predicted well. The formula is as follows:

[0227] Df jz =Df+(z s -z) (43)

[0228] In the formula: Df jz The corrected values ​​for formation collapse pressure, formation leakage pressure, and formation fracture pressure of the target formation in the predicted well are represented in MPa; Df represents the well logging interpretation value of formation collapse pressure, formation leakage pressure, or formation fracture pressure of the target formation in the predicted well, in MPa; z is the mode of formation collapse pressure, formation leakage pressure, and formation fracture pressure of the target formation in the predicted well.

[0229] 9. Based on the well logging interpretation profiles of the formation collapse pressure, formation loss pressure, and formation fracture pressure corrected for the target formation in the predicted well, and combined with the characteristics of the loss channels and reservoir space in the target formation, determine the drilling fluid-prone areas in the target formation of the predicted well. The specific method is as follows:

[0230] (1) Based on the profile of formation pressure, formation collapse pressure, formation leakage pressure and formation fracture pressure correction values ​​of the target formation of the predicted well, find the low value areas of formation leakage pressure and formation fracture pressure of the target formation of the predicted well, as well as the areas where the difference between formation pressure and formation collapse pressure and formation leakage pressure and formation fracture pressure is small.

[0231] (2) Based on the characteristics of the target formation leakage channels and reservoir space, in the low value areas of formation leakage pressure and formation fracture pressure of the target formation of the predicted well, and in the areas where the difference between formation pressure and formation collapse pressure and formation leakage pressure and formation fracture pressure is small, it is determined whether the formation leakage channels and reservoir space are developed. If the formation leakage channels and reservoir space are developed, it is determined to be a fractured leakage formation risk level. If the formation fracture pressure is low and the formation leakage channels and reservoir space are not developed, it is determined to be a fractured leakage formation risk level.

[0232] Implementation Cases

[0233] This example predicts the formation to be the Maokou Formation in a well area of ​​the Sichuan Basin. The selected well is PS16 in this well area, and the adjacent wells are PS21, PY1, PS7, PS9, PS17, and PS8. The specific implementation steps are as follows:

[0234] Step 1: Collect complete well logging data from the prediction well and adjacent sample wells, along with 75 downhole Maokou Formation rock samples. Through well logging data interpretation, obtain dynamic rock mechanics parameters and dynamic geostress data for the Maokou Formation in wells PS21, PY1, PS7, PS9, PS17, and PS8. Using a static rock mechanics parameter and geostress dynamic conversion model constructed from rock experimental results, correct the dynamic rock mechanics parameters and dynamic geostress to obtain corrected values ​​for the Maokou Formation rock mechanics parameters and geostress in each well, resulting in well logging interpretation profiles. Furthermore, using the corrected values ​​for the dynamic rock mechanics parameters and dynamic geostress in each well, calculate the formation pressure, formation collapse pressure, formation leakage pressure, and formation fracture pressure profiles for the Maokou Formation in each well.

[0235] Step 2: Rock samples from the Maokou Formation in wells PS21, PY1, PS7, PS9, PS17 and PS8 were subjected to rock mineral composition testing, electron microscopy scanning, thin section identification of cast bodies, and interpretation and analysis of formation fracture development characteristics using imaging logging data, in order to reveal the tensile strength properties of the Maokou Formation rocks, formation leakage channels and reservoir space characteristics.

[0236] Step 3: Using the corrected values ​​of rock mechanics parameters and geostress of the Maokou Formation from wells PS21, PY1, PS7, PS9, PS17, and PS8, as well as the formation pressure, formation collapse pressure, formation leakage pressure, and formation fracture pressure profiles of the Maokou Formation, and combining these with the natural gamma curves, resistivity curves, and sonic curves of the Maokou Formation from these six wells, the Maokou Formation was divided into seven sub-layers. The division results are shown in […]. Figure 2 and Figure 3 .

[0237] Step 4: Based on the seven sub-layers of the Maokou Formation in wells PS21, PY1, PS7, PS9, PS17, and PS8, the rock mechanics parameter correction values, geostress correction values, and formation pressure data obtained from the interpretation of sonic logging data of the Maokou Formation in these six wells are subjected to data thinning or interpolation.

[0238] Step 5: Based on the distances from wells PS21, PY1, PS7, PS9, PS17, and PS8 to well PS16, the distance ratios of these wells to well PS16 are obtained as follows: 1:1.3:1.4:1.5:2.3:3.2. Therefore, the predicted weights for these six sample wells are 0.2308, 0.1776, 0.1649, 0.1539, 0.1004, and 0.072, respectively.

[0239] Step 6: Based on the predicted weight values ​​from wells PS21, PY1, PS7, PS9, PS17, and PS8, and using the corrected values ​​of rock mechanics parameters and in-situ stress from their target formations, well logging interpretation profiles, and formation pressure profiles, a weighted average calculation is performed to obtain the rock mechanics parameters, in-situ stress, and formation pressure of the Maokou Formation in well PS16. A comparison of the predicted and interpreted values ​​of the rock mechanics parameters of the Maokou Formation in well PS16 is shown below. Figure 4 The curve showing the agreement rate between the predicted and interpreted values ​​of the rock mechanical parameters of the Maokou Formation in well PS16 is shown below. Figure 5 .from Figure 4 and Figure 5 As can be seen from the data, the average consistency rate between the predicted values ​​of various rock mechanical parameters of the Maokou Formation obtained by weighted average calculation and the well logging interpretation values ​​is greater than 92%, indicating that the method has a good effect on the prediction results of rock mechanical parameters of the target formation.

[0240] Step 7: Using the rock mechanics parameters, in-situ stress, and formation pressure of the Maokou Formation in Well PS16, and combining the calculation models for formation collapse pressure, formation leakage pressure, and formation fracture pressure, a profile of formation collapse pressure, formation leakage pressure, and formation fracture pressure in the Maokou Formation of Well PS16 is constructed. A comparison of the predicted values ​​and well logging interpretation values ​​for formation collapse pressure, formation leakage pressure, and formation fracture pressure in the Maokou Formation of Well PS16 is shown below. Figure 6 The curves showing the consistency rate between the predicted values ​​and the interpreted values ​​of formation collapse pressure, formation leakage pressure, and formation fracture pressure in the Maokou Formation of well PS16 are shown below. Figure 7 .from Figure 6 and Figure 7 It can be seen that the average consistency rate between the predicted formation collapse pressure, formation leakage pressure and formation fracture pressure of the Maokou Formation in well PS16 and the well logging interpretation values ​​is greater than 84%. Overall, the consistency rate of each value is relatively stable.

[0241] Step 8: Weighted averages were applied to the modes of formation collapse pressure, formation leakage pressure, and formation fracture pressure in the Maokou Formation of wells PS21, PY1, PS7, PS9, PS17, and PS8 to calculate the weighted average modes of these parameters. Then, based on the mode differences, the predicted and corrected values ​​for formation collapse pressure, formation leakage pressure, and formation fracture pressure in the Maokou Formation of well PS16 were obtained. A comparison between the predicted and corrected values ​​of formation collapse pressure, formation leakage pressure, and formation fracture pressure in the Maokou Formation of well PS16 and the well logging interpretation values ​​is shown below. Figure 8 The curves showing the consistency rate between the predicted and corrected values ​​of formation collapse pressure, formation leakage pressure, and formation fracture pressure in the Maokou Formation of well PS16 and the well logging interpretation values ​​are shown below. Figure 9 .from Figure 8 and Figure 9 As can be seen from the data, the average consistency rate between the predicted and corrected values ​​of formation collapse pressure, formation leakage pressure, and formation fracture pressure in the Maokou Formation of well PS16 and the interpreted values ​​of the logging data has increased to 97%, and the overall prediction results are in high agreement with the actual logging calculation values.

[0242] Step 9: Based on the corrected formation collapse pressure, formation leakage pressure, and formation fracture pressure profiles of the Maokou Formation in well PS16, and combined with the characteristics of the leakage channels and reservoir space in the Maokou Formation of well PS16, the leakage strata were predicted before drilling. The results are shown in […]. Figure 10 .analyze Figure 10 It was found that there is one significant leakage risk point in the Maokou Formation of well PS16, located at 6050.75m, with a predicted fracture pressure equivalent density of 2.37 g / cm³. 3 Based on actual logging data from the site, the equivalent density at the bottom of the well at a depth of 6050.75m exceeds 2.39 g / cm³. 3This leads to leakage. The actual leakage point matches the leakage risk layer predicted using the method of this invention, indicating that the method of this invention has high reliability in predicting formation drilling fluid leakage-prone layers.

[0243] The above description is merely a preferred embodiment of the present invention and is not intended to limit the present invention. Any modifications, equivalent substitutions, and improvements made within the spirit and principles of the present invention should be included within the scope of protection of the present invention.

Claims

1. A method for predicting easily leaky formations of drilling fluid using well logging data, characterized in that, The method includes the following steps: Step 1.1: Based on the interpretation of logging data from 5 or more adjacent wells of the target formation, construct logging interpretation profiles for corrected rock mechanical parameters and corrected geostress values ​​of the target formation in the adjacent wells. Rock mechanical parameters include tensile strength, uniaxial compressive strength, triaxial compressive strength, elastic modulus, and Poisson's ratio. Also, construct logging interpretation profiles for formation pressure, formation collapse pressure, formation leakage pressure, and formation fracture pressure of the target formation in 5 or more adjacent wells of the target formation. Step 1.2: Based on the analysis of rock and mineral composition testing, electron microscopy, thin section identification and imaging logging of the target formation in 5 or more adjacent wells, clarify the lithology, fracture development and occurrence and pore development of the target formation in the adjacent wells. Reveal the tensile strength performance, formation leakage channels and reservoir space characteristics of the target formation in the adjacent wells from the perspective of rock lithology and structural characteristics. Step 1.3: Based on the well logging interpretation profiles of the target formation with corrected rock mechanics parameters and corrected geostress values ​​from 5 or more adjacent wells, as well as the well logging interpretation profiles of formation pressure, formation collapse pressure, formation leakage pressure and formation fracture pressure, and combined with the natural gamma curve, resistivity curve and sonic curve of the target formation from the adjacent wells, the target formation is finely divided into sub-layers. Step 1.4: Based on the results of the fine division of the target formation into smaller layers, use the rock mechanics parameter correction values, geostress correction values, and formation pressure data obtained from the interpretation of acoustic logging data of 5 or more adjacent wells of the target formation, and perform data thinning or interpolation. Step 1.5: Based on the distance between 5 or more sample neighboring wells and the predicted well, obtain the prediction weight value of each sample neighboring well; Step 1.6: Based on the prediction weight values ​​of 5 or more adjacent wells, use the corrected values ​​of rock mechanics parameters, geostress, and formation pressure of the target formation of the 5 or more adjacent wells to calculate the weighted average to obtain the rock mechanics parameters, geostress, and formation pressure of the target formation of the predicted well. Step 1.7: Based on the rock mechanical parameters, geostress, and formation pressure of the target formation in the predicted well, construct well logging interpretation profiles for formation collapse pressure, formation leakage pressure, and formation fracture pressure of the target formation in the predicted well; Step 1.8: Correct the logging interpretation profile of formation collapse pressure, formation leakage pressure and formation fracture pressure of the target formation in the predicted well using the mode difference; Step 1.9: Based on the formation collapse pressure, formation leakage pressure and formation fracture pressure logging interpretation profiles of the target formation of the predicted well, and in combination with the leakage channels and reservoir space characteristics of the target formation, determine the drilling fluid leakage-prone layers of the target formation of the predicted well. The specific steps of step 1.4 are as follows: Step 1.4.1: Based on the target formation thickness of 5 or more adjacent wells and the original data sampling interval, calculate the corrected values ​​of rock mechanics parameters, geostress, and formation pressure data for each sub-layer of the target formation in the adjacent wells. The formula is as follows: In the formula: n sl For the target formation of the adjacent well in the sample l Corrected values ​​for rock mechanical parameters, corrected values ​​for in-situ stress, and data volume of formation pressure in the sublayer. l It is an integer; H sl For the first l Layer thickness, m; N The original data sampling interval is m, typically 0.125m; Step 1.4.2: Calculate the corrected values ​​of rock mechanics parameters, geostress, and total formation pressure data of the target formation from 5 or more adjacent wells. The formula is as follows: In the formula: n s This represents the total data volume of corrected rock mechanics parameters, corrected geostress, and formation pressure for the target formation in adjacent wells, in integer form. L The total number of layers, an integer; Step 1.4.3: Calculate the thickness of each sub-layer of the target formation in the predicted well. H tl Thickness of each sub-layer of the target formation in adjacent wells of 5 or more samples H sl ratio m l The formula is as follows: Step 1.4.4, when m l When the value is less than 1, the corrected values ​​of rock mechanics parameters, geostress, and formation pressure data of the corresponding sub-layers in adjacent wells are thinned out, and the number of data extraction intervals is calculated using the following formula: In the formula: k rl For the number of extraction intervals of rock mechanics parameter correction values, geostress correction values, and formation pressure data, an integer; Corrected values ​​for rock mechanics parameters, geostress, and formation pressure data of the target formation in adjacent wells at intervals. k rl One data point is extracted for each sample, and the extracted data is the corrected value of the rock mechanical parameters, the corrected value of the in-situ stress, and the formation pressure data of the corresponding sub-layer of the predicted well mapped by the adjacent well of that sample. Step 1.4.5, when m l When the value is greater than 1, interpolate the corrected values ​​of rock mechanics parameters, geostress, and formation pressure data of the corresponding sub-layers in adjacent wells, and calculate the interpolation number between adjacent data. The formula is as follows: In the formula: k il The number of interpolations between adjacent data points, an integer; The adjacent data of rock mechanics parameters, in-situ stress, and formation pressure of each sub-layer of the target formation in the sample well were analyzed. k il Linear interpolation of the data yields the corrected values ​​of rock mechanics parameters, geostress, and formation pressure of the adjacent wells in the corresponding sub-layers of the predicted well.

2. The method for predicting easily leaking formations using well logging data according to claim 1, characterized in that, The specific steps of step 1.1 are as follows: Step 1.1.1: Obtain the rock acoustic velocity of downhole rock samples from the target formation in 5 or more adjacent wells through a rock acoustic transit time test experiment; Step 1.1.2: Obtain the experimental values ​​of rock mechanical parameters of downhole rock samples from 5 or more adjacent wells of the target formation through rock tensile strength test, rock uniaxial compressive strength test, and rock triaxial compressive strength test. The rock mechanical parameters include tensile strength, uniaxial compressive strength, triaxial compressive strength, elastic modulus, and Poisson's ratio. Step 1.1.3: Obtain the in-situ stress test values ​​of downhole rock samples from the target formation in 5 or more adjacent wells through rock acoustic emission in-situ stress testing experiments; Step 1.1.4: Based on the rock acoustic velocity of downhole rock samples from the target formation in 5 or more adjacent wells, calculate the dynamic rock mechanics parameters and dynamic geostress of the downhole rock samples from the target formation in the adjacent wells. Combine the experimental values ​​of rock mechanics parameters and geostress obtained from experimental tests to construct a dynamic and static rock mechanics parameter and geostress conversion model for the target formation in the adjacent wells. Step 1.1.5: Based on the interpretation of acoustic logging data of the target formation from 5 or more adjacent wells, calculate and obtain the dynamic rock mechanics parameters and dynamic geostress logging interpretation values ​​of the target formation from the adjacent wells. Based on the dynamic and static rock mechanics parameters and geostress conversion model of the target formation from the adjacent wells, correct the dynamic rock mechanics parameters and dynamic geostress logging interpretation values ​​of the target formation from the adjacent wells to obtain the corrected rock mechanics parameters and geostress logging interpretation profiles of the target formation from the adjacent wells. Step 1.1.6: Using well logging interpretation profiles with corrected values ​​of rock mechanics parameters and geostress of the target formation from 5 or more adjacent wells, calculate and construct well logging interpretation profiles of formation pressure, formation collapse pressure, formation leakage pressure and formation fracture pressure of the target formation from the adjacent wells based on the calculation model of formation pressure, formation collapse pressure, formation leakage pressure and formation fracture pressure.

3. The method for predicting easily leaking formations using well logging data according to claim 1, characterized in that, The specific steps of step 1.2 are as follows: Step 1.2.1: Using an X-ray diffractometer, test downhole rock samples from 5 or more adjacent wells of the target formation, and determine the rock and mineral composition by observing the characteristic peak intensities in specific X-ray spectra of the rocks and minerals. Step 1.2.2: Cut and obtain fresh cross-sections of rock samples from 5 or more adjacent wells of the target formation. Use scanning electron microscopy to observe and clarify the microscopic fracture and pore morphology characteristics of the fresh cross-sections of the rock samples. Step 1.2.3: Prepare thin sections of downhole rock samples from 5 or more adjacent wells of the target formation. Use a polarizing microscope to identify the thin sections and clarify the rock lithology, microscopic fracture and pore morphology. Step 1.2.4: Use acoustic imaging logging technology to obtain high-resolution imaging logging interpretation images of the target formation in 5 or more adjacent wells, and reveal the development characteristics of natural fractures and dissolution cavities and specific stratigraphic positions based on the imaging logging interpretation images; Step 1.2.5: Based on the rock mineral composition, microscale fracture and pore morphology, rock lithology, microscale fracture and pore morphology, development characteristics of natural fractures and dissolution cavities, and specific stratigraphic positions, reveal the tensile strength properties, leakage channels, and reservoir space characteristics of the target strata rocks.

4. The method for predicting easily leaking formations using well logging data according to claim 1, characterized in that, The specific steps of step 1.3 are as follows: Step 1.3.1: Based on the well logging interpretation profiles of corrected rock mechanical parameters and corrected geostress values ​​of the target formation from 5 or more adjacent wells, and the well logging interpretation profiles of formation pressure, perform preliminary stratification of the target formation; Step 1.3.2: Analyze the target formation logging curve data from 5 or more adjacent wells, extract abrupt change characteristic points from the natural gamma logging curves to determine the lithological interface; identify the oil-water interface and gas-bearing show zones through resistivity logging curve morphology analysis to determine fluid properties; use sonic transit time logging data to determine lithology and porosity changes by comparing the sonic transit time range of standard lithology; identify pressure anomaly zones and determine pressure characteristic changes based on the logging interpretation profiles of formation collapse pressure, formation leakage pressure, and formation fracture pressure; further, based on the preliminary stratification of the target formation, perform fine sub-layer division of the target formation.

5. The method for predicting easily leaking formations using well logging data according to claim 1, characterized in that, The specific steps of step 1.5 are as follows: Step 1.5.1: Based on the layout diagram of adjacent wells and predicted wells of 5 or more samples, calculate the distance between adjacent wells and predicted wells; Step 1.5.2: Based on the distances between five or more adjacent wells and the predicted well, calculate the prediction weight value for each adjacent well, using the following formula: In the formula: q k For the first k The predicted weight values ​​for adjacent wells in the sample are dimensionless. x k The distance between the sample well and the predicted well, in meters; Step 1.5.3: Normalize the prediction weight values ​​of adjacent wells for samples of 5 or more, using the following formula: In the formula: p k For the first k The predicted weights of the adjacent wells after normalization of the sample are dimensionless.

6. The method for predicting easily leaking formations using well logging data according to claim 5, characterized in that, The specific steps of step 1.6 are as follows: Step 1.6.1: Based on the corrected values ​​of rock mechanics parameters, in-situ stress, and formation pressure of 5 or more adjacent wells mapped to the corresponding sub-layers of the prediction well, and using the normalized prediction weight values ​​of each adjacent well, calculate the prediction components of the target formation rock mechanics parameters, in-situ stress, and formation pressure of each adjacent well for the prediction well. The formula is as follows: In the formula: w k Refers to the first k The predicted components of rock mechanical parameters, geostress, and formation pressure of the target formation in the sample adjacent wells; s k Refers to the first k Rock mechanics parameters, geostress, and formation pressure of the target formation in adjacent wells of the sample; Step 1.6.2: Based on the predicted components of the target formation rock mechanical parameters, in-situ stress, and formation pressure of the predicted well from 5 or more adjacent wells, sum and calculate the target formation rock mechanical parameters, in-situ stress, and formation pressure of the predicted well, as shown in the following formula: In the formula: s It refers to the rock mechanical parameters, geostress, and formation pressure of the target formation in the predicted well.

7. The method for predicting easily leaky formations of drilling fluid using well logging data according to claim 1, characterized in that, The specific steps of step 1.7 are as follows: Step 1.7.1: Based on the predicted formation stress and formation pressure of the target formation in the well, perform stress coordinate axis transformation, establish a wellbore cylindrical coordinate stress distribution model centered on the wellbore axis, and obtain the maximum principal stress and minimum principal stress of the wellbore cylindrical coordinate system; Step 1.7.2: Based on the rock mechanics parameters of the target formation in the predicted well, formation pressure, and the maximum and minimum principal stresses in the wellbore cylindrical coordinate system, calculate and construct the well logging interpretation profile of the formation collapse pressure, formation leakage pressure, and formation fracture pressure of the target formation in the predicted well, based on the calculation model of formation collapse pressure, formation leakage pressure, and formation fracture pressure.

8. The method for predicting easily leaking formations using well logging data according to claim 5, characterized in that, The specific steps of step 1.8 are as follows: Step 1.8.1: Perform a weighted average of the mode of formation collapse pressure, formation leakage, and formation fracture pressure for the target formation in 5 or more adjacent wells, using the following formula: In the formula: z s The mode of formation collapse pressure, formation leakage pressure and formation fracturing pressure of the target formation after weighted average processing, in MPa; z k Refers to the first k Mode of formation collapse pressure, formation leakage pressure and formation fracture pressure of the target formation in the adjacent well of the sample, MPa; Step 1.8.2: Using the weighted average processed mode of formation collapse pressure, formation leakage pressure, and formation fracture pressure of the target formation, calculate and construct the corrected value profiles of formation collapse pressure, formation leakage pressure, and formation fracture pressure of the target formation in the predicted well, based on the well logging interpretation profile data of the formation collapse pressure, formation leakage pressure, and formation fracture pressure of the target formation in the predicted well. The formula is as follows: In the formula: Df jz The corrected values ​​for formation collapse pressure, formation leakage pressure, and formation fracture pressure of the target formation in the predicted well, in MPa; Df The well logging interpretation value, in MPa, refers to the formation collapse pressure, formation loss pressure, or formation fracture pressure of the target formation in the predicted well. z To predict the formation collapse pressure, formation leakage pressure, and formation fracture pressure mode of the target formation in the well.

9. The method for predicting easily leaky formations of drilling fluid using well logging data according to claim 1, characterized in that, The specific steps of step 1.9 are as follows: Step 1.9.1: Based on the profile of formation pressure, formation collapse pressure, formation leakage pressure and formation fracture pressure correction values ​​of the target formation of the predicted well, find the low value areas of formation leakage pressure and formation fracture pressure of the target formation of the predicted well, as well as the areas where the difference between formation pressure and formation collapse pressure and formation leakage pressure and formation fracture pressure is small. Step 1.9.2: Based on the characteristics of the target formation leakage channels and reservoir space, in areas with low formation leakage pressure and formation fracture pressure in the target formation of the predicted well, and in areas where the difference between formation pressure and formation collapse pressure and formation leakage pressure and formation fracture pressure is small, determine whether formation leakage channels and reservoir space are developed. If formation leakage channels and reservoir space are developed, they are identified as fractured leakage risk formations. If formation fracture pressure is low but formation leakage channels and reservoir space are not developed, they are identified as fractured leakage risk formations.

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