CN119801502A - A method for predicting shale oil well wall collapse pressure - Google Patents
A method for predicting shale oil well wall collapse pressure Download PDFInfo
- Publication number
- CN119801502A CN119801502A CN202311303746.5A CN202311303746A CN119801502A CN 119801502 A CN119801502 A CN 119801502A CN 202311303746 A CN202311303746 A CN 202311303746A CN 119801502 A CN119801502 A CN 119801502A
- Authority
- CN
- China
- Prior art keywords
- stress
- shale oil
- well
- well wall
- rock
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Granted
Links
Landscapes
- Investigating Strength Of Materials By Application Of Mechanical Stress (AREA)
- Geophysics And Detection Of Objects (AREA)
Abstract
The invention relates to a shale oil well wall collapse pressure prediction method which comprises the steps of obtaining components, structures and physical and chemical properties of a shale oil reservoir, carrying out immersion-nuclear magnetism-sound wave-triaxial stress joint test experiments of different drilling fluid systems, constructing a shale oil reservoir rock heterogeneous water absorption and strength degradation equation, establishing a ground stress and pore pressure profile, converting far field stress into a well bore and a bedding coordinate system, calculating a well peripheral stress field generated by water absorption of surrounding rock, simulating and calculating temperature field distribution of the rock and calculating a thermal stress value, superposing a well Zhou Yingli value under the coupling effect of calculation force-chemical-thermal-bedding, constructing a well peripheral rock matrix and weak surface shear damage discrimination function and condition collapse, constructing a shale oil reservoir rock pressure numerical simulation iteration test algorithm, determining stratum collapse pressure density control factors and control mechanisms, and reducing shale oil well wall risk collapse through optimization. The method can more accurately predict the collapse pressure of the shale oil well wall under the coupling effect of force-chemical-thermal-bedding.
Description
Technical Field
The invention relates to the technical field of shale oil safety drilling, and in particular relates to a shale oil well wall collapse pressure prediction method.
Background
In recent years, the shale oil reserves ascertained in China are quite rich, the shale oil reserves are mainly formed in the organic-matter-rich shale layer of the land-phase lake basin, and the geological conditions of the reservoir are complex. Shale contains clay minerals such as illite, illite mixed layer, montmorillonite and the like, meanwhile, the structure weaknesses such as the development layer and the like are developed, drilling fluid easily enters into stratum, and mechanical action and chemical reaction occur between the drilling fluid and the well wall, so that the well Zhou Yingli is redistributed and the rock strength is deteriorated, the collapse accident of the well wall is frequently induced in the drilling process, the drilling period and the cost are greatly increased, and the exploration and development process is restricted.
Conventional collapse pressure studies, assuming the formation is a continuous isotropic medium, are relatively lacking in systematic studies of hard brittle, heterogeneous, and bedding developing shale oil reservoirs. For example, chinese patent No. 104806233A discloses a method for predicting the collapse pressure equivalent density window of a weak stratum, which provides the division of a dense section and a crack section of a shaft and the mechanical strength test of a rock body and a crack surface, and based on the method, the near-well pore pressure and stress analysis is carried out based on a fluid-solid coupling mean model, and the damage state and the collapse pressure of a well wall are measured by combining strength criteria. The Chinese patent No. 113356843A discloses a method for predicting a collapse pressure equivalent density window of a weak stratum, which is characterized in that the method is used for collecting various pressure parameters of the stratum and obtaining constitutive parameters of stratum rocks, and on the basis, the ground stress state and a well wall stress model are combined to realize coupling under the coupling of multiple physical fields of an average stratum and well wall stability analysis under the cooperation, so that the optimization of drilling parameters in an oilfield site is facilitated. The Chinese patent No. 114526058A discloses a method and a system for designing the collapse pressure of drilling, the method acquires the well wall stress characteristics at different positions according to the ground stress information by collecting the drilling type and the well wall circumference integrity degree of a target stratum, and based on the well wall stress characteristics, the proportion of the minimum well wall safety area to the well wall circumference area during the safety drilling construction is counted, so that the collapse pressure of drilling is calculated according to the equivalent density of the collapse pressure, and the purposes of reducing the drilling fluid density and improving the safety drilling speed are realized. The Chinese patent CN113095593A provides a method, a device and equipment for determining the state of a well wall of a well, which are used for evaluating the state of the well wall of a well by utilizing an intelligent learning algorithm through collecting relevant data such as formation pressure, shaft pressure, drilling engineering parameters and the like of the well, improving the reliability of the evaluation, and predicting the evaluation parameters and risk prediction results of the state of the well of an un-drilled section at the lower part of the well on the basis of the evaluation. The Chinese patent CN114547906A discloses a well wall stable logging interpretation method for deep stratum with a weak structural surface, which is characterized in that a stratum pressure and ground stress profile is established by collecting logging data and real drilling completion data, and the maximum horizontal main stress azimuth, the bedding inclination angle and the trend are determined, and three pressure profiles are drawn on the basis, so that the influence of the bedding structural surface is considered on the basis of a conventional logging method, the prediction accuracy is improved, and further the safe and efficient drilling of deep complex stratum is effectively guided. The Chinese patent No. 111980667 discloses a quantitative evaluation method of the influence of anisotropy on shale well wall collapse pressure, which is characterized in that the ground stress parameters, bedding production, well track, stratum pressure and the like of a target well region obtained under a geodetic coordinate system are known, rock mechanical parameters of a rock body and a fracture surface are measured, the principal stress is converted to the well periphery and the bedding surface by utilizing coordinate conversion, and the critical collapse pressure on the well periphery is obtained based on a matlab Newton iteration method by combining MC, MGC, ML and MWC strength criteria.
In fact, during the whole drilling period, the shale oil reservoir well wall collapse is a multi-element superposition coupling problem, the shale oil reservoir undergoes heat transfer and temperature change to the well shaft due to low temperature of the well shaft drilling fluid, thermal stress can cause near-well stress field change, and meanwhile, due to capillary force, a clay mineral crystal layer structure, mineralization degree difference between the drilling fluid and stratum fluid and pressure difference between bottom hole pressure and stratum pressure, imbibition, hydration, diffusion and permeation can be induced in the shale oil drilling process, so that the well Zhou Yingli, stratum fluid pressure and rock strength are changed, and the control effect of the layer structure on the dominant directions of water absorption and seepage and the strength degradation speed is further enhanced, so that the well wall collapse is aggravated.
Accordingly, the prior art is in need of improvement.
Disclosure of Invention
The invention mainly solves the defects of the existing shale oil well wall collapse pressure prediction technology, and provides a shale oil well wall collapse pressure prediction method. The method can more accurately predict the collapse pressure of the shale oil well wall under the coupling effect of force-chemical-thermal-bedding, and provides a guarantee for efficient and safe drilling of shale oil.
The technical scheme adopted by the invention is as follows:
according to one aspect of the invention, a shale oil well wall collapse pressure prediction method is provided, which comprises the following steps:
S1, acquiring components, structures and physical and chemical properties of a shale oil reservoir;
S2, carrying out soaking-nuclear magnetism-sound wave-triaxial stress combined test of different drilling fluid systems, and dynamically evaluating various characteristics of shale oil reservoir rocks in different bedding directions under the coupling action of the shale oil reservoir rocks and the drilling fluid;
s3, constructing a shale oil reservoir rock heterogeneous water absorption and water saturation equation, and constructing a relationship equation of expansion strain and water content and a rock strength degradation equation;
s4, establishing vertical stress, maximum horizontal ground stress, minimum horizontal ground stress and pore pressure profile;
s5, converting far-field stress into a borehole coordinate system and a bedding coordinate system by utilizing a coordinate conversion relation, and calculating normal stress and shear stress on a well Zhou Yingli and a bedding surface induced by the far-field stress;
s6, calculating water absorption capacity and shale expansion strain capacity of different spatial positions of shale oil reservoirs at different drilling times, and calculating a well circumferential stress field generated by water absorption of surrounding rocks by combining a surrounding rock equilibrium state equation and boundary conditions;
S7, simulating and calculating the temperature field distribution of the well wall rock under the circulation condition of the drilling fluid, and calculating a thermal stress value;
S8, superposing well Zhou Yingli values under the action of force-chemical-thermal-bedding coupling;
S9, constructing a surrounding rock matrix and weak face shear failure discrimination function and discrimination conditions of the well by using an M-C strength criterion, a D-P strength criterion, an MG-C strength criterion, a corrected Lade strength criterion and a weak face strength criterion;
S10, substituting the well Zhou Yingli and rock mechanical parameters under the force-chemical-thermal-bedding coupling effect into a surrounding rock matrix around the well and weak surface shearing damage discrimination function and discrimination conditions, and constructing shale oil reservoir collapse pressure numerical simulation iterative trial algorithm under different borehole trajectories and imbibition time;
S11, calculating shale oil reservoir well wall collapse pressures under different well angles, azimuth angles, structural surfaces, drilling fluid systems and action time, obtaining influences of factors on the shale oil reservoir well wall collapse pressures, and then determining stratum collapse pressure density control factors and control mechanisms;
And S12, reducing the collapse risk of the shale oil well wall through optimization of a drilling fluid system, optimization of a well track and optimization of drilling process parameters.
In one embodiment of the present invention, in S1, the composition, structure and physicochemical properties of a shale oil reservoir are obtained by conducting shale oil reservoir XRD diffraction experiments, macroscopic, microscopic, microstructural characterization experiments, solidity experiments and permeability anisotropy experiments, and S1 comprises the steps of:
A1, carrying out XRD diffraction experiments, and analyzing the all-rock mineral components and the clay mineral components of the shale oil reservoir;
A2, carrying out sheet analysis, scanning electron microscopy and high-pressure mercury injection experiments, analyzing macroscopic, microscopic and microstructure characteristics of shale oil, and providing basis for compounding and selecting plugging agents while drilling;
a3, carrying out a wettability experiment, and measuring the wetting angle of a drilling fluid system compounded by clear water, kerosene, a hydrophobe and a plugging agent by using a baseline circle method, so as to provide a basis for the selection of the drilling fluid system;
And A4, carrying out a water absorption and diffusion experiment in a parallel bedding direction and a perpendicular bedding direction to obtain the anisotropic characteristic of the water absorption and diffusion coefficient, and establishing a shale oil reservoir water absorption and diffusion model with obvious bedding characteristics and a numerical simulation method.
In one embodiment of the invention, the shale oil reservoir water absorption diffusion model with significant bedding characteristics in A4 is shown as follows:
Wherein:
initial boundary conditions:
Where C ij eff is the equivalent water absorption diffusion coefficient tensor, w a is the saturation water content at the borehole wall, and w 0 is the water content in the original formation.
In one embodiment of the present invention, in S2, the various characteristics include dynamic water absorption characteristics, T2 spectrogram dynamic variation characteristics, dynamic and static mechanical parameter variation characteristics, and S2 comprises the steps of:
B1, soaking shale oil reservoir cores in different drilling fluid systems, measuring longitudinal and transverse wave velocity curves of the rock under a plurality of time nodes respectively, and calculating to obtain dynamic mechanical parameters of the rock soaked by different drilling fluids;
B2, measuring nuclear magnetic resonance characteristics of the rock core at the plurality of time nodes, acquiring relaxation time and amplitude change characteristics, evaluating dynamic water absorption characteristics of the shale oil reservoir, pore size and pore volume change rules, and establishing a dynamic water absorption equation;
B3, selecting a plurality of cores from part of the time nodes, carrying out triaxial stress experiments under different surrounding pressures, obtaining a full stress-strain relation curve, and calculating compressive strength, elastic modulus and Poisson's ratio;
And B4, drawing a limit moire stress circle and an intensity envelope curve of each rock core of each time node on the basis of a triaxial stress experimental result of each lithology at the partial time node, and calculating cohesion and an internal friction angle.
In one embodiment of the invention, in S3, a corresponding equation is constructed based on the control effect of the shale layer theory on the dominant water absorption direction, and S3 comprises the following steps:
C1, based on experimental results of B1 and B2, establishing a relation equation of rock dynamic parameters and water absorption;
c2, based on experimental results of B1, B3 and B4, establishing a relation equation of static parameters and dynamic parameters;
and C3, constructing a relation equation of static elastic modulus, static Poisson ratio, cohesion and internal friction angle and water absorption.
In one embodiment of the invention, in S4, vertical stress, maximum horizontal ground stress, minimum horizontal ground stress, and pore pressure profile are established based on logging data, mine data, and laboratory test data, and S4 comprises the steps of:
D1, carrying out sectional accumulation or integral calculation on vertical stress by using density logging data, or carrying out gradient calculation on static and earth stress, or carrying out comprehensive estimation on the vertical stress;
D2, carrying out inversion on the maximum horizontal ground stress and the minimum horizontal ground stress through an indoor core experiment combining the ancient geomagnetism, the Kesepal effect, the differential strain and the wave velocity anisotropy, or carrying out inversion on mine field data by using a well wall caving method and a micro-fracturing experiment;
and D3, estimating the pore pressure by using a sonic jet lag method and a dc index method based on logging data or sonic jet lag logging data.
In one embodiment of the invention, in S5, the earth coordinate system is taken as an intermediate conversion value according to the earth stress direction, the well hole direction and the bedding trend of the shale oil reservoir, and the conversion is performed by utilizing the coordinate conversion relation, and S5 comprises the following steps:
e1, converting far-field stress into a borehole coordinate system by utilizing a coordinate conversion relation based on the shale oil reservoir stratum ground stress direction and the borehole direction;
e2. well Zhou Yingli tensor is calculated by using the magnitude and direction of the ground stress, and then the well Zhou Yingli distribution state is converted to the layer weak surface.
In one embodiment of the present invention, in E1, the far field stress is expressed as:
Wherein the method comprises the steps of
Wherein sigma H,σh,σv is the maximum horizontal ground stress, the minimum horizontal ground stress and the vertical stress, and MPa; The stress components are the stress components of in-situ stress acting on the surrounding rock of the well wall, and MPa, alpha b and beta b are well inclination angles;
In E2, the weak plane stress expression is:
Wherein:
wherein θ is the well circumference angle.
In one embodiment of the present invention, in S6, the relationship between the water swelling strain and the water content is:
Post-hydration well Zhou Yingli distribution:
Wherein epsilon v、εh is vertical and horizontal strain respectively, delta omega is the rate of change of water content, epsilon rr、εθθ、εzz is the radial, circumferential and axial strain components of the mud shale of the well site under hydration respectively, sigma r、σθ、σz is the radial, circumferential and axial stress components of the mud shale of the well site under hydration respectively, MPa, E is the elastic modulus of rock, and v is the Poisson's ratio of rock.
In one embodiment of the invention, S7 comprises the steps of:
F1, based on the heat exchange effect of drilling fluid in a drill string, the drill string, annulus drilling fluid and stratum, simulating and calculating the temperature field distribution of a well Zhou Yandan under the condition of drilling fluid circulation;
f2, calculating the corresponding additional thermal stress on the well wall according to the temperature field distribution of the well Zhou Yandan.
In one embodiment of the invention, the temperature field profile of the well Zhou Yandan is as follows:
Wherein sigma rT、σθT、σzT is the temperature difference between radial, circumferential and axial directions and is added with thermal stress, MPa, alpha T is the thermal expansion coefficient of rock, 1/DEGC, E is the elastic modulus of rock, MPa, v is the Poisson's ratio of rock, T f is the temperature difference of stratum, DEG C, r w is the radius of a borehole, and m.
In one embodiment of the invention, in S8, the value of the well Zhou Yingli under force-chemical-thermal-bedding coupling is calculated based on the stress components generated by the earth stress, the drilling fluid column pressure, the pore pressure, the hydration stress, the temperature stress, using the superposition principle, and S8 comprises the steps of:
g1, assuming that the rock is a small deformation elastomer, respectively calculating vertical stress, maximum horizontal ground stress and minimum horizontal ground stress induced well wall stress components, and performing superposition calculation as a well wall stress static value;
g2, according to the contact time of the shale reservoir and the drilling fluid, analyzing the well wall stress components generated by the fluid column pressure, the pore pressure, the hydration stress and the temperature stress of the drilling fluid, and performing superposition calculation as a well wall stress dynamic value;
And G3, performing superposition calculation on the static value and the dynamic value of the well wall stress to obtain the total well wall stress value of the shale oil reservoir under the force-chemical-thermal-bedding coupling effect and different contact time of the shale oil reservoir and the drilling fluid.
In one embodiment of the invention, S9 comprises the steps of:
H1, constructing a shear failure function of the shale matrix by using an M-C strength criterion, wherein the shear failure function is as follows:
and H2, constructing a shear failure function of the shale matrix by using a D-P strength criterion, wherein the shear failure function is as follows:
and H3, constructing a shear failure function of the shale matrix by using an MG-C strength criterion, wherein the shear failure function is as follows:
H4, constructing a shear failure function in the shale layer by using the corrected Lade strength criterion:
and H5, constructing a shear failure function in the shale layer by using a weak face strength criterion, wherein the shear failure function is as follows:
H6, judging that the surrounding rock of the well wall is sheared and damaged when at least one of f i (i=1, 2, 3, 4 and 5) is smaller than 0, judging that the surrounding rock of the well wall is in a collapse unstable state when f i is equal to 0, judging that the surrounding rock of the well wall is in a shearing and damage critical state and the stability of the well wall is in a critical state, judging that the surrounding rock of the well wall is not sheared and damaged when f i is larger than 0, and judging that the well wall is in a stable state,
Wherein, in the formula, the compound (I),Is the internal matrix friction angle, σ 1 is the first principal stress, σ 2 is the second principal stress, σ 3 is the third principal stress, k is the permeability, α is the rock thermal expansion coefficient,Is the friction angle in the weak surface,Is the principal stress of the weak face,Is weak-face shear strength, C is cohesive force,Is weak cohesive force, eta is a material constant, and a, b and S are constants.
In one embodiment of the invention, S10 comprises the steps of:
I1, substituting a drilling fluid density, a well Zhou Yingli and rock mechanical parameters under the force-chemical-thermal-bedding coupling effect into a surrounding rock matrix around the well and weak face shearing damage discrimination function and discrimination conditions, and calculating f i;
I2, recalculating f i if at least one of f i is less than-5% and the drilling fluid density is increased by 0.01g/cm 3, recalculating f i if f i is greater than 5% and the drilling fluid density is reduced by 0.01g/cm 3, and defining the corresponding drilling fluid density as collapse pressure equivalent density if-5% is less than or equal to all f i is less than or equal to 5%;
And I3, carrying out iterative computation to obtain the equivalent density range of the collapse pressure.
In one embodiment of the invention, S11 comprises the steps of:
j1, simulating and calculating shale oil reservoir well wall collapse pressure under different layers of physical and chemical properties to obtain the influence of geological factors on collapse stress;
J2, simulating and calculating shale oil reservoir well wall collapse pressure under different well oblique angles and azimuth angles, and obtaining the influence of well track factors on collapse stress;
J3, calculating the collapse pressure of the shale oil reservoir well wall under different drilling fluid systems and action time, and obtaining the influence of the drilling fluid on the collapse period;
And J4, combining geological and engineering factors, and determining shale oil reservoir collapse pressure control factors and control mechanisms.
In one embodiment of the invention, S12 comprises the steps of:
K1, adding a plugging agent and a water repellent, adjusting a drilling fluid system, increasing the compactness of a well wall, increasing the contact angle of the drilling fluid on the surface of rock, reducing the free energy of the surface of clay minerals, and preventing and reducing the entry of the drilling fluid.
And K2, optimizing the well track, reasonably selecting the deflecting point, the orientation and the azimuth of the horizontal well section, and avoiding the coincidence of the well azimuth and the azimuth of the maximum ground stress so as to reduce the risk of well instability.
By adopting the technical scheme, the invention has at least the following beneficial effects:
The method for predicting the collapse pressure of the shale oil well wall is realized by considering the comprehensive factors of stratum temperature, bedding and matrix rock water absorption heterogeneity, bedding matrix rock strength degradation, rock expansion under the condition of water absorption water content difference and the like.
Drawings
In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the drawings that are needed for the embodiments will be briefly described below, and it is obvious that the drawings in the following description are only some embodiments of the present invention, and other drawings may be obtained according to these drawings without inventive effort for a person skilled in the art.
FIG. 1 shows a flow chart of a shale oil well wall collapse pressure prediction method provided by the invention;
FIG. 2 illustrates multi-scale structural features of a shale oil reservoir in an embodiment of the invention;
FIGS. 3 (a) and (b) show the results of the water absorption and diffusion simulation of the structures inside the layer in the embodiment of the present invention;
Fig. 4 (a) and (b) show the moral circles and envelopes of shale oil reservoir rocks after 0h and 24h of soaking, respectively, in an embodiment of the invention;
FIGS. 5 (a) and (b) illustrate the conversion of the earth stress coordinate system and the borehole coordinate system, respectively, in an embodiment of the present invention;
FIG. 6 shows simulation results of different cycle time temperature fields in an embodiment of the invention;
FIG. 7 shows an iterative calculation flow of shale oil reservoir collapse pressure in an embodiment of the invention;
FIG. 8 shows a graph of the effect of shale oil reservoir layer formation angle on collapse pressure in an embodiment of the invention;
FIG. 9 is a graph showing the effect of well inclination on collapse pressure in an embodiment of the present invention;
FIG. 10 is a graph showing the effect of shale oil reservoir contact time with drilling fluid on collapse pressure in an embodiment of the invention.
Detailed Description
In order to make the objects, technical solutions and advantages of the present invention more apparent, the following embodiments of the present invention will be described in further detail with reference to the accompanying drawings.
As shown in FIG. 1, the shale oil well wall collapse pressure prediction method provided by the invention comprises the following steps:
s1, carrying out XRD diffraction experiments, macroscopic, microscopic, microstructure characteristic experiments, compactibility experiments and permeability anisotropy experiments on the shale oil reservoir to obtain components, structures and physical and chemical properties of the shale oil reservoir. The specific process of the step S1 is as follows:
and A1, carrying out XRD diffraction experiments to analyze the all-rock mineral components and the clay mineral components of the shale oil reservoir.
And A2, carrying out evaluation of structural features of different scales such as rock core, sheet analysis, scanning electron microscope and the like, analyzing macroscopic, microscopic and microscopic structural features of shale oil, and providing basis for compounding and selecting plugging agents while drilling. In this embodiment, a shale oil reservoir of a hong Kong oilfield is adopted, the structural characteristics of the shale oil reservoir under the dimensions of a core, a slice and an electron microscope are shown as in fig. 2, cracks are all ubiquitous, and the size of each crack ranges from tens of nanometers to hundreds of micrometers.
A3, carrying out a wettability experiment, and determining the wetting angle of the drilling fluid system compounded by the clear water, the kerosene, the hydrophobe and the plugging agent by using a baseline circle method, so as to provide a basis for the selection of the drilling fluid system.
And A4, carrying out a water absorption and diffusion experiment in a parallel bedding direction and a perpendicular bedding direction to obtain the anisotropic characteristic of the water absorption and diffusion coefficient, and establishing a shale oil reservoir water absorption and diffusion model with obvious bedding characteristics and a numerical simulation method.
The shale oil reservoir water absorption diffusion model with significant bedding characteristics is shown in the following equation, and the numerical simulation results are shown in fig. 3 (a) and (b).
Wherein:
initial boundary conditions:
In the formula, Is the equivalent water absorption and diffusion coefficient tensor, w a is the saturated water content at the well wall, and w 0 is the water content in the original stratum.
S2, carrying out soaking-nuclear magnetism-sound wave-triaxial stress combined test of different drilling fluid systems, and dynamically evaluating dynamic water absorption characteristics, T2 spectrogram dynamic change characteristics and dynamic and static mechanical parameter change characteristics of shale oil reservoir rocks in different bedding directions under the coupling action of the shale oil reservoir rocks and the drilling fluid. The specific process of the step S2 is as follows:
B1, soaking shale oil reservoir cores in different drilling fluid systems, measuring longitudinal and transverse wave velocity curves of the rock at 0h,0.5h,1h,2h,4h,8h,16h,24h,48h and 96h respectively, and calculating to obtain dynamic mechanical parameters of the rock after soaking in different drilling fluids.
B2, nuclear magnetic resonance characteristics of the rock core are measured at time nodes of 0h,0.5h,1h,2h,4h,8h,16h,24h,48h and 96h, relaxation time and amplitude change characteristics are obtained, dynamic water absorption characteristics of the shale oil reservoir are evaluated, and a dynamic water absorption equation is established according to pore size and pore volume change rules.
And B3, selecting 3-5 cores at time nodes of 0h,2h,8h and 24h, carrying out triaxial stress experiments under different surrounding pressures, obtaining a full stress-strain relation curve, and calculating compressive strength, elastic modulus and poisson ratio.
And B4, drawing a limit Moire stress circle and an intensity envelope curve of each core of each time node at time nodes of 0h,2h,8h and 24h based on a triaxial stress experimental result, and calculating cohesion and an internal friction angle. In this example, the moral circle and envelope of a shale oil reservoir rock of the harbor oilfield used after 0h and 24h soaking are shown in fig. 4 (a) and (b).
And S3, constructing a shale oil reservoir rock heterogeneous water absorption water saturation equation, an expansion strain and water content relation equation and a rock strength degradation equation by considering the control effect of the shale layer theory on the water absorption dominant direction. The specific process of the step S3 is as follows:
c1, combining experimental results of B1 and B2, and establishing a relation equation of rock dynamic parameters and water absorption;
C2, combining the experimental results of B1B3 and B4 to establish a relation equation of static parameters and dynamic parameters;
and C3, constructing a relation equation of static elastic modulus, static Poisson ratio, cohesion and internal friction angle and water absorption.
S4, establishing vertical stress, maximum horizontal ground stress, minimum horizontal ground stress and pore pressure profile based on logging data, mine site data and indoor experimental data. The specific process of the step S4 is as follows:
The vertical stress is estimated by using the sectional accumulation or integral calculation of the density logging data or the static stress gradient or the combination of the two.
And D2, carrying out inversion on mine field data such as maximum horizontal ground stress and minimum horizontal ground stress through indoor core experiments such as combined paleogeomagnetism, kesepal effect, differential strain and wave velocity anisotropy, or using a well wall caving method, micro-fracturing experiments and the like.
And D3, estimating the pore pressure from logging data or acoustic time difference logging data by using an acoustic time difference method, a dc index method and the like.
S5, converting far-field stress into a borehole coordinate system and a bedding coordinate system by taking a geodetic coordinate system as an intermediate conversion value according to the earth stress direction, the borehole direction and the bedding trend of the shale oil reservoir, and calculating positive stress and shear stress on a bedding surface and a well Zhou Yingli induced by the far-field stress. The specific process of the step S5 is as follows:
E1, converting far-field ground stress into a borehole coordinate system according to the ground stress direction and the borehole direction of the shale oil reservoir by utilizing a coordinate conversion relation as shown in (a) and (b) of fig. 5.
Wherein the method comprises the steps of
Wherein sigma H,σh,σv is the maximum horizontal ground stress, the minimum horizontal ground stress and the vertical stress, and MPa; The stress components of in-situ stress acting on the wall surrounding rock are MPa, alpha b is the well inclination azimuth angle, and beta b is the well inclination angle.
E2. after the well Zhou Yingli tensor is obtained by using the magnitude and the direction of the ground stress, the well Zhou Yingli distribution state can be converted to a layer weak surface, and the weak surface stress expression is as follows:
Wherein:
wherein θ is the well circumference angle.
S6, calculating water absorption capacity and shale expansion strain capacity of different spatial positions of the shale oil reservoir at different drilling times, and calculating a well circumferential stress field generated by water absorption of surrounding rock by combining a surrounding rock equilibrium state equation and boundary conditions. The specific process of the step S6 is as follows:
The relationship between the water absorption expansion strain and the water content is as follows:
Post-hydration well Zhou Yingli distribution:
Wherein epsilon v、εh is vertical and horizontal strain respectively, delta omega is the rate of change of water content, epsilon rr、εθθ、εzz is the radial, circumferential and axial strain components of the mud shale of the well site under hydration respectively, sigma r、σθ、σz is the radial, circumferential and axial stress components of the mud shale of the well site under hydration respectively, MPa, E is the elastic modulus of rock, and v is the Poisson's ratio of rock.
And S7, considering the heat exchange effect of drilling fluid, drilling string, annulus drilling fluid and stratum in the drilling string, simulating and calculating the temperature field distribution of the well wall rock under the circulating condition of the drilling fluid, and calculating the thermal stress value and the collapse pressure added value caused by the temperature stress. The specific process of the step S7 is as follows:
And F1, performing simulation calculation on the temperature field distribution of the well Zhou Yandan under the condition of drilling fluid circulation by taking into consideration the heat exchange effect of drilling fluid in the drill string, annulus drilling fluid and stratum. In this embodiment, taking a shale well of Songlao basin as an example, the temperature fields of the well wall at different cycle times are shown in FIG. 6.
Wherein sigma rT、σθT、σzT is the temperature difference between radial, circumferential and axial directions and is added with thermal stress, MPa, alpha T is the thermal expansion coefficient of rock, 1/DEGC, E is the elastic modulus of rock, MPa, v is the Poisson's ratio of rock, T f is the temperature difference of stratum, DEG C, r w is the radius of a borehole, and m.
And S8, calculating a well Zhou Yingli value under the force-chemical-thermal-bedding coupling effect by adopting a superposition principle in consideration of stress components generated by ground stress, drilling fluid column pressure, pore pressure, hydration stress and temperature stress. The specific process of the step S8 is as follows:
and G1, assuming the rock is a small deformation elastomer, respectively calculating vertical stress, maximum horizontal ground stress and minimum horizontal ground stress induced well wall stress components, and performing superposition calculation as a well wall stress static value.
And G2, analyzing the well wall stress components generated by the liquid column pressure, the pore pressure, the hydration stress and the temperature stress of the drilling fluid according to the contact time of the shale reservoir and the drilling fluid, and performing superposition calculation as a well wall stress dynamic value.
And G3, performing superposition calculation on the static value and the dynamic value of the well wall stress to obtain the total well wall stress value of the shale oil reservoir under the force-chemical-thermal-bedding coupling effect and different contact time of the shale oil reservoir and the drilling fluid.
S9, constructing a surrounding rock matrix and weak face shear failure discrimination function and discrimination conditions of the well by using the M-C strength criterion, the D-P strength criterion, the MG-C strength criterion, the corrected Lade strength criterion and the weak face strength criterion. The specific process of the step S9 is as follows:
H1, constructing a shear failure function of the shale matrix by using an M-C strength criterion, wherein the shear failure function is as follows:
and H2, constructing a shear failure function of the shale matrix by using a D-P strength criterion, wherein the shear failure function is as follows:
and H3, constructing a shear failure function of the shale matrix by using an MG-C strength criterion, wherein the shear failure function is as follows:
H4, constructing a shear failure function in the shale layer by using the corrected Lade strength criterion:
and H5, constructing a shear failure function in the shale layer by using a weak face strength criterion, wherein the shear failure function is as follows:
H6, judging that the surrounding rock of the well wall is sheared and damaged when at least one of f i (i=1, 2, 3, 4 and 5) is smaller than 0, judging that the surrounding rock of the well wall is in a collapse unstable state when f i is equal to 0, judging that the surrounding rock of the well wall is in a shearing and damage critical state and the stability of the well wall is in a critical state, judging that the surrounding rock of the well wall is not sheared and damaged when f i is larger than 0, and judging that the well wall is in a stable state,
Wherein, in the formula, the physical meaning expressed by the function f i is that the shear strength of the rock matrix subtracts the shear stress acting on the surrounding rock of the well wall,Is the internal matrix friction angle, σ 1 is the first principal stress, σ 2 is the second principal stress, σ 3 is the third principal stress, k is the permeability, α is the rock thermal expansion coefficient,Is the friction angle in the weak surface,Is the principal stress of the weak face,Is weak-face shear strength, C is cohesive force,Is weak cohesive force, eta is a material constant, and a, b and S are constants.
S10, substituting the well Zhou Yingli and rock mechanical parameters under the force-chemical-thermal-bedding coupling effect into a surrounding rock matrix around the well and weak face shearing damage discriminant function and discriminant conditions, and constructing shale oil reservoir collapse pressure numerical simulation iterative test algorithms under different borehole trajectories and imbibition time. The specific process of the step S10 is as follows:
And I1, substituting the well Zhou Yingli and rock mechanical parameters under the coupling effect of the calculation force-chemical-thermal-bedding into the surrounding rock matrix around the well and the weak face shear damage discrimination function and discrimination conditions, and calculating f i.
I2-if at least one of f i is less than-5%, the drilling fluid density is increased by 0.01g/cm 3, f i is recalculated, if f i is greater than 5%, the drilling fluid density is decreased by 0.01g/cm 3, f i is recalculated, and if-5% is less than or equal to all f i is less than or equal to 5%, the corresponding drilling fluid density is defined as the collapse pressure equivalent density.
And I3, carrying out iterative computation according to the formulas (1) and (15) to obtain the equivalent density range of the collapse pressure, wherein the iterative computation flow is shown in figure 7.
And S11, calculating the influence of different well angles, azimuth angles, structural surfaces, drilling fluid systems and action time on the collapse pressure of the shale oil reservoir well wall, and obtaining stratum collapse pressure density control factors and control mechanisms. The specific process of the step S11 is as follows:
And J1, calculating the collapse pressure of the shale oil reservoir well wall under different layers of physical and chemical properties to obtain the influence of geological factors on the collapse stress. The effect of the bedding angle on the collapse pressure equivalent density for a shale oil reservoir of an oilfield in this example is shown in figure 8.
And J2, calculating shale oil reservoir well wall collapse pressure under different well oblique angles and azimuth angles, and obtaining the influence of the well track factors on the collapse stress. The effect of the well angle on the collapse pressure equivalent density for a shale oil reservoir of an oilfield in this example is shown in figure 9.
And J3, calculating the collapse pressure of the shale oil reservoir well wall under different drilling fluid systems and action time to obtain the influence of the drilling fluid on the collapse period. The effect of soak time on collapse pressure equivalent density for a shale oil reservoir of an oilfield in this example is shown in figure 10.
And J4, combining geological and engineering factors, and determining shale oil reservoir collapse pressure control factors and control mechanisms.
And S12, reducing the collapse risk of the shale oil well wall through optimization of a drilling fluid system, optimization of a well track and optimization of drilling process parameters. The specific process of the step S12 is as follows:
And K1, adding a plugging agent and a water repellent, adjusting a drilling fluid system, increasing the compactness of a well wall, increasing the contact angle of the drilling fluid on the surface of rock, reducing the free energy of the surface of clay minerals, and preventing and reducing the entry of the drilling fluid. If the size of the hole seam of a shale oil reservoir in a certain oil field ranges from tens of nanometers to hundreds of micrometers, the single plugging agent is difficult to form effective plugging, the nano-micrometer plugging agent particle size grading is performed, and a better plugging effect is realized.
And K2, optimizing the well track, reasonably selecting the deflecting point and the orientations of the directional and horizontal well sections, and avoiding the coincidence of the well orientation and the maximum ground stress orientation as much as possible so as to reduce the risk of well instability.
Therefore, the method for predicting the collapse pressure of the shale oil well wall is realized under the influence of comprehensive factors such as formation temperature, bedding and matrix rock water absorption heterogeneity, bedding matrix rock strength degradation, rock expansion under the condition of water absorption water content difference and the like. The method can more accurately predict the collapse pressure of the shale oil well wall under the coupling effect of force-chemical-thermal-bedding, and provides a guarantee for efficient and safe drilling of shale oil.
The above description is only of the preferred embodiments of the present invention, and is not intended to limit the scope of the invention, but the invention is modified or equivalent to be included in the scope of the appended claims without departing from the spirit and scope of the invention.
Claims (16)
1. The shale oil well wall collapse pressure prediction method is characterized by comprising the following steps of:
S1, acquiring components, structures and physical and chemical properties of a shale oil reservoir;
S2, carrying out soaking-nuclear magnetism-sound wave-triaxial stress combined test of different drilling fluid systems, and dynamically evaluating various characteristics of shale oil reservoir rocks in different bedding directions under the coupling action of the shale oil reservoir rocks and the drilling fluid;
s3, constructing a shale oil reservoir rock heterogeneous water absorption and water saturation equation, and constructing a relationship equation of expansion strain and water content and a rock strength degradation equation;
s4, establishing vertical stress, maximum horizontal ground stress, minimum horizontal ground stress and pore pressure profile;
s5, converting far-field stress into a borehole coordinate system and a bedding coordinate system by utilizing a coordinate conversion relation, and calculating normal stress and shear stress on a well Zhou Yingli and a bedding surface induced by the far-field stress;
s6, calculating water absorption capacity and shale expansion strain capacity of different spatial positions of shale oil reservoirs at different drilling times, and calculating a well circumferential stress field generated by water absorption of surrounding rocks by combining a surrounding rock equilibrium state equation and boundary conditions;
S7, simulating and calculating the temperature field distribution of the well wall rock under the circulation condition of the drilling fluid, and calculating a thermal stress value;
S8, superposing well Zhou Yingli values under the action of force-chemical-thermal-bedding coupling;
S9, constructing a surrounding rock matrix and weak face shear failure discrimination function and discrimination conditions of the well by using an M-C strength criterion, a D-P strength criterion, an MG-C strength criterion, a corrected Lade strength criterion and a weak face strength criterion;
S10, substituting the well Zhou Yingli and rock mechanical parameters under the force-chemical-thermal-bedding coupling effect into a surrounding rock matrix around the well and weak surface shearing damage discrimination function and discrimination conditions, and constructing shale oil reservoir collapse pressure numerical simulation iterative trial algorithm under different borehole trajectories and imbibition time;
S11, calculating shale oil reservoir well wall collapse pressures under different well angles, azimuth angles, structural surfaces, drilling fluid systems and action time, obtaining influences of factors on the shale oil reservoir well wall collapse pressures, and then determining stratum collapse pressure density control factors and control mechanisms;
And S12, reducing the collapse risk of the shale oil well wall through optimization of a drilling fluid system, optimization of a well track and optimization of drilling process parameters.
2. The method for predicting collapse pressure of shale oil well wall according to claim 1, wherein in S1, components, structures and physicochemical properties of the shale oil reservoir are obtained by performing XRD diffraction experiments, macroscopic, microscopic, and microscopic structural feature experiments, solidity experiments and permeability anisotropy experiments of the shale oil reservoir, and S1 comprises the steps of:
A1, carrying out XRD diffraction experiments, and analyzing the all-rock mineral components and the clay mineral components of the shale oil reservoir;
A2, carrying out sheet analysis, scanning electron microscopy and high-pressure mercury injection experiments, analyzing macroscopic, microscopic and microstructure characteristics of shale oil, and providing basis for compounding and selecting plugging agents while drilling;
a3, carrying out a wettability experiment, and measuring the wetting angle of a drilling fluid system compounded by clear water, kerosene, a hydrophobe and a plugging agent by using a baseline circle method, so as to provide a basis for the selection of the drilling fluid system;
And A4, carrying out a water absorption and diffusion experiment in a parallel bedding direction and a perpendicular bedding direction to obtain the anisotropic characteristic of the water absorption and diffusion coefficient, and establishing a shale oil reservoir water absorption and diffusion model with obvious bedding characteristics and a numerical simulation method.
3. The method for predicting collapse pressure of shale oil well wall according to claim 2, wherein a shale oil reservoir water absorption diffusion model with remarkable layer physical characteristics in A4 is shown as the following formula:
Wherein:
initial boundary conditions:
In the formula, Is the equivalent water absorption and diffusion coefficient tensor, w a is the saturated water content at the well wall, and w 0 is the water content in the original stratum.
4. The method for predicting collapse pressure of shale oil well wall according to claim 1, wherein in S2, the various characteristics include dynamic water absorption characteristics, T2 spectrogram dynamic change characteristics, dynamic and static mechanical parameter change characteristics, and S2 comprises the steps of:
B1, soaking shale oil reservoir cores in different drilling fluid systems, measuring longitudinal and transverse wave velocity curves of the rock under a plurality of time nodes respectively, and calculating to obtain dynamic mechanical parameters of the rock soaked by different drilling fluids;
B2, measuring nuclear magnetic resonance characteristics of the rock core at the plurality of time nodes, acquiring relaxation time and amplitude change characteristics, evaluating dynamic water absorption characteristics of the shale oil reservoir, pore size and pore volume change rules, and establishing a dynamic water absorption equation;
B3, selecting a plurality of cores from part of the time nodes, carrying out triaxial stress experiments under different surrounding pressures, obtaining a full stress-strain relation curve, and calculating compressive strength, elastic modulus and Poisson's ratio;
And B4, drawing a limit moire stress circle and an intensity envelope curve of each rock core of each time node on the basis of a triaxial stress experimental result of each lithology at the partial time node, and calculating cohesion and an internal friction angle.
5. The method for predicting collapse pressure of shale oil well wall according to claim 4, wherein in S3, a corresponding equation is constructed based on the control action of the shale layer theory to the dominant water absorption direction, and S3 comprises the following steps:
C1, based on experimental results of B1 and B2, establishing a relation equation of rock dynamic parameters and water absorption;
c2, based on experimental results of B1, B3 and B4, establishing a relation equation of static parameters and dynamic parameters;
and C3, constructing a relation equation of static elastic modulus, static Poisson ratio, cohesion and internal friction angle and water absorption.
6. The method of claim 1, wherein in S4, the vertical stress, the maximum horizontal ground stress, the minimum horizontal ground stress, and the pore pressure profile are established based on logging data, mine data, and laboratory test data, and S4 comprises the steps of:
D1, carrying out sectional accumulation or integral calculation on vertical stress by using density logging data, or carrying out gradient calculation on static and earth stress, or carrying out comprehensive estimation on the vertical stress;
D2, carrying out inversion on the maximum horizontal ground stress and the minimum horizontal ground stress through an indoor core experiment combining the ancient geomagnetism, the Kesepal effect, the differential strain and the wave velocity anisotropy, or carrying out inversion on mine field data by using a well wall caving method and a micro-fracturing experiment;
and D3, estimating the pore pressure by using a sonic jet lag method and a dc index method based on logging data or sonic jet lag logging data.
7. The method for predicting collapse pressure of shale oil well wall according to claim 1, wherein in S5, the borehole direction and the bedding direction are converted by using a coordinate conversion relation with a geodetic coordinate system as an intermediate conversion value according to the shale oil reservoir ground stress direction, and S5 comprises the steps of:
e1, converting far-field stress into a borehole coordinate system by utilizing a coordinate conversion relation based on the shale oil reservoir stratum ground stress direction and the borehole direction;
e2. well Zhou Yingli tensor is calculated by using the magnitude and direction of the ground stress, and then the well Zhou Yingli distribution state is converted to the layer weak surface.
8. The method for predicting collapse pressure of shale oil well wall according to claim 7, wherein in E1, the far-field stress is expressed as:
Wherein the method comprises the steps of
Wherein sigma H,σh,σv is the maximum horizontal ground stress, the minimum horizontal ground stress and the vertical stress, and MPa; The stress components are the stress components of in-situ stress acting on the surrounding rock of the well wall, and MPa, alpha b and beta b are well inclination angles;
In E2, the weak plane stress expression is:
Wherein:
wherein θ is the well circumference angle.
9. The method for predicting collapse pressure of shale oil well wall according to claim 1, wherein in S6, the relationship between the water swelling strain and the water content is:
Post-hydration well Zhou Yingli distribution:
Wherein epsilon v、εh is vertical and horizontal strain respectively, delta omega is the rate of change of water content, epsilon rr、εθθ、εzz is the radial, circumferential and axial strain components of the mud shale of the well site under hydration respectively, sigma r、σθ、σz is the radial, circumferential and axial stress components of the mud shale of the well site under hydration respectively, MPa, E is the elastic modulus of rock, and v is the Poisson's ratio of rock.
10. The shale oil well wall collapse pressure prediction method according to claim 1, wherein S7 comprises the following steps:
F1, based on the heat exchange effect of drilling fluid in a drill string, the drill string, annulus drilling fluid and stratum, simulating and calculating the temperature field distribution of a well Zhou Yandan under the condition of drilling fluid circulation;
f2, calculating the corresponding additional thermal stress on the well wall according to the temperature field distribution of the well Zhou Yandan.
11. The method of claim 10, wherein the temperature field distribution of the well Zhou Yandan is as follows:
Wherein sigma rT、σθT、σzT is the temperature difference between radial, circumferential and axial directions and is added with thermal stress, MPa, alpha T is the thermal expansion coefficient of rock, 1/DEGC, E is the elastic modulus of rock, MPa, v is the Poisson's ratio of rock, T f is the temperature difference of stratum, DEG C, r w is the radius of a borehole, and m.
12. The method for predicting collapse pressure of shale oil well wall according to claim 1, wherein in S8, a value of the well Zhou Yingli under the force-chemical-thermal-bedding coupling action is calculated based on stress components generated by ground stress, drilling fluid column pressure, pore pressure, hydration stress and temperature stress by using a superposition principle, and S8 comprises the steps of:
g1, assuming that the rock is a small deformation elastomer, respectively calculating vertical stress, maximum horizontal ground stress and minimum horizontal ground stress induced well wall stress components, and performing superposition calculation as a well wall stress static value;
g2, according to the contact time of the shale reservoir and the drilling fluid, analyzing the well wall stress components generated by the fluid column pressure, the pore pressure, the hydration stress and the temperature stress of the drilling fluid, and performing superposition calculation as a well wall stress dynamic value;
And G3, performing superposition calculation on the static value and the dynamic value of the well wall stress to obtain the total well wall stress value of the shale oil reservoir under the force-chemical-thermal-bedding coupling effect and different contact time of the shale oil reservoir and the drilling fluid.
13. The shale oil well wall collapse pressure prediction method according to claim 1, wherein S9 comprises the following steps:
H1, constructing a shear failure function of the shale matrix by using an M-C strength criterion, wherein the shear failure function is as follows:
and H2, constructing a shear failure function of the shale matrix by using a D-P strength criterion, wherein the shear failure function is as follows:
and H3, constructing a shear failure function of the shale matrix by using an MG-C strength criterion, wherein the shear failure function is as follows:
H4, constructing a shear failure function in the shale layer by using the corrected Lade strength criterion:
and H5, constructing a shear failure function in the shale layer by using a weak face strength criterion, wherein the shear failure function is as follows:
H6, judging that the surrounding rock of the well wall is sheared and damaged when at least one of f i (i=1, 2, 3, 4 and 5) is smaller than 0, judging that the surrounding rock of the well wall is in a collapse unstable state when f i is equal to 0, judging that the surrounding rock of the well wall is in a shearing and damage critical state and the stability of the well wall is in a critical state, judging that the surrounding rock of the well wall is not sheared and damaged when f i is larger than 0, and judging that the well wall is in a stable state,
Wherein, in the formula, the compound (I),Is the internal matrix friction angle, σ 1 is the first principal stress, σ 2 is the second principal stress, σ 3 is the third principal stress, k is the permeability, α is the rock thermal expansion coefficient,Is the friction angle in the weak surface,Is the principal stress of the weak face,Is weak-face shear strength, C is cohesive force,Is weak cohesive force, eta is a material constant, and a, b and S are constants.
14. The method of predicting collapse pressure of a shale oil borehole wall of claim 13, wherein S10 comprises the steps of:
I1, substituting a drilling fluid density, a well Zhou Yingli and rock mechanical parameters under the force-chemical-thermal-bedding coupling effect into a surrounding rock matrix around the well and weak face shearing damage discrimination function and discrimination conditions, and calculating f i;
I2, recalculating f i if at least one of f i is less than-5% and the drilling fluid density is increased by 0.01g/cm 3, recalculating f i if f i is greater than 5% and the drilling fluid density is reduced by 0.01g/cm 3, and defining the corresponding drilling fluid density as collapse pressure equivalent density if-5% is less than or equal to all f i is less than or equal to 5%;
And I3, carrying out iterative computation to obtain the equivalent density range of the collapse pressure.
15. The shale oil well wall collapse pressure prediction method according to claim 1, wherein S11 comprises the steps of:
j1, simulating and calculating shale oil reservoir well wall collapse pressure under different layers of physical and chemical properties to obtain the influence of geological factors on collapse stress;
J2, simulating and calculating shale oil reservoir well wall collapse pressure under different well oblique angles and azimuth angles, and obtaining the influence of well track factors on collapse stress;
J3, calculating the collapse pressure of the shale oil reservoir well wall under different drilling fluid systems and action time, and obtaining the influence of the drilling fluid on the collapse period;
And J4, combining geological and engineering factors, and determining shale oil reservoir collapse pressure control factors and control mechanisms.
16. The shale oil well wall collapse pressure prediction method according to claim 1, wherein S12 comprises the steps of:
K1, adding a plugging agent and a water repellent, adjusting a drilling fluid system, increasing the compactness of a well wall, increasing the contact angle of the drilling fluid on the surface of rock, reducing the free energy of the surface of clay minerals, and preventing and reducing the entry of the drilling fluid.
And K2, optimizing the well track, reasonably selecting the deflecting point, the orientation and the azimuth of the horizontal well section, and avoiding the coincidence of the well azimuth and the azimuth of the maximum ground stress so as to reduce the risk of well instability.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202311303746.5A CN119801502B (en) | 2023-10-09 | 2023-10-09 | Shale oil well wall collapse pressure prediction method |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202311303746.5A CN119801502B (en) | 2023-10-09 | 2023-10-09 | Shale oil well wall collapse pressure prediction method |
Publications (2)
| Publication Number | Publication Date |
|---|---|
| CN119801502A true CN119801502A (en) | 2025-04-11 |
| CN119801502B CN119801502B (en) | 2025-11-11 |
Family
ID=95276925
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN202311303746.5A Active CN119801502B (en) | 2023-10-09 | 2023-10-09 | Shale oil well wall collapse pressure prediction method |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN119801502B (en) |
Cited By (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN120213278A (en) * | 2025-05-19 | 2025-06-27 | 中国地质科学院地质力学研究所 | A core three-dimensional ground stress measurement system and method based on multi-source data |
| CN120671398A (en) * | 2025-06-18 | 2025-09-19 | 广州地铁设计研究院股份有限公司 | Intensity prediction method and system based on improved Hoek-Brown criterion slate softening constitutive model |
| CN121006962A (en) * | 2025-10-27 | 2025-11-25 | 中国石油大学(华东) | A method and system for heat insulation and cooling of the wellbore by adsorption of porous hollow microspheres while drilling in ultra-deep wells |
Citations (6)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| WO2011010989A1 (en) * | 2009-07-20 | 2011-01-27 | Services Petroliers Schlumberger | Estimating formation stresses using radial profiles of three shear moduli |
| CN104463686A (en) * | 2014-10-29 | 2015-03-25 | 中国石油集团川庆钻探工程有限公司 | Method for identifying shale gas reservoir while drilling by using discriminant analysis method |
| CN110685600A (en) * | 2018-06-20 | 2020-01-14 | 中国石油化工股份有限公司 | Drill bit adjustment prediction method for geosteering |
| RU2018127256A (en) * | 2018-07-24 | 2020-01-24 | Общество с ограниченной ответственностью "Газпромнефть Научно-Технический Центр" (ООО "Газпромнефть НТЦ") | METHOD FOR FORECASTING AREAS OF ABSORPTION OF A DRILLING MILL FOR DRILLING WELLS ON THE BASIS OF A THREE-DIMENSIONAL GEOMECHANICAL MODEL AND A TECTONIC DEPOSIT |
| CN111980667A (en) * | 2020-09-17 | 2020-11-24 | 西南石油大学 | Quantitative evaluation method for influences of anisotropy on shale borehole wall collapse pressure |
| CN115951422A (en) * | 2023-03-14 | 2023-04-11 | 北京阳光杰科科技股份有限公司 | Method for constructing natural fracture leakage pressure model |
-
2023
- 2023-10-09 CN CN202311303746.5A patent/CN119801502B/en active Active
Patent Citations (6)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| WO2011010989A1 (en) * | 2009-07-20 | 2011-01-27 | Services Petroliers Schlumberger | Estimating formation stresses using radial profiles of three shear moduli |
| CN104463686A (en) * | 2014-10-29 | 2015-03-25 | 中国石油集团川庆钻探工程有限公司 | Method for identifying shale gas reservoir while drilling by using discriminant analysis method |
| CN110685600A (en) * | 2018-06-20 | 2020-01-14 | 中国石油化工股份有限公司 | Drill bit adjustment prediction method for geosteering |
| RU2018127256A (en) * | 2018-07-24 | 2020-01-24 | Общество с ограниченной ответственностью "Газпромнефть Научно-Технический Центр" (ООО "Газпромнефть НТЦ") | METHOD FOR FORECASTING AREAS OF ABSORPTION OF A DRILLING MILL FOR DRILLING WELLS ON THE BASIS OF A THREE-DIMENSIONAL GEOMECHANICAL MODEL AND A TECTONIC DEPOSIT |
| CN111980667A (en) * | 2020-09-17 | 2020-11-24 | 西南石油大学 | Quantitative evaluation method for influences of anisotropy on shale borehole wall collapse pressure |
| CN115951422A (en) * | 2023-03-14 | 2023-04-11 | 北京阳光杰科科技股份有限公司 | Method for constructing natural fracture leakage pressure model |
Cited By (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN120213278A (en) * | 2025-05-19 | 2025-06-27 | 中国地质科学院地质力学研究所 | A core three-dimensional ground stress measurement system and method based on multi-source data |
| CN120671398A (en) * | 2025-06-18 | 2025-09-19 | 广州地铁设计研究院股份有限公司 | Intensity prediction method and system based on improved Hoek-Brown criterion slate softening constitutive model |
| CN121006962A (en) * | 2025-10-27 | 2025-11-25 | 中国石油大学(华东) | A method and system for heat insulation and cooling of the wellbore by adsorption of porous hollow microspheres while drilling in ultra-deep wells |
Also Published As
| Publication number | Publication date |
|---|---|
| CN119801502B (en) | 2025-11-11 |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| CN119801502B (en) | Shale oil well wall collapse pressure prediction method | |
| CN108868748B (en) | Method for calculating repeated fracturing fracture opening pressure of shale gas horizontal well | |
| CN113356843B (en) | Method, device, medium and equipment for analyzing stability of well wall of stratum | |
| CN112412434B (en) | Improved loose sandstone ground stress calculation method | |
| CN106285646A (en) | Drilling well loss horizon recognition methods based on Multi-information acquisition | |
| US20020147574A1 (en) | Method of predicting the on-set of formation solid production in high-rate perforated and open hole gas wells | |
| CN107169248B (en) | Special stratum safe mud density window determination method | |
| CN103510948B (en) | A kind of experimental technique being applicable to the prediction of brittle rock Well-bore Stability During Gas Drilling | |
| Li et al. | Modeling progressive breakouts in deviated wellbores | |
| CN118187842A (en) | A method for calculating wellbore collapse pressure considering underbalanced drilling of infill wells | |
| Yu et al. | On how asymmetric stimulated rock volume in shales may impact casing integrity | |
| Khodami et al. | The 3D simulation of the effect of casing standoff on cement integrity by considering the direction of horizontal stresses in one of the wells of Iranian oil fields | |
| Zhao et al. | A novel evaluation on fracture pressure in depleted shale gas reservoir | |
| CN116717224A (en) | A fracturing productivity prediction method for complex fracture networks in low-permeability tight reservoirs | |
| CN105298478A (en) | Method for determining formation pore pressure of fault structure | |
| Zeng et al. | Mechanism and controlling method for casing deformation in shale gas wells | |
| CN115964836A (en) | Method for measuring stress interference intensity among staged multi-cluster fracturing clusters of continental facies shale horizontal well | |
| Xu et al. | Three‐Dimensional Numerical Simulation of Fracture Extension in Conglomerate Fracturing Considering Pore‐Fracture Seepage and Study of Influencing Factors | |
| Cai et al. | A new fractal temporal conductivity model for propped fracture and its application in tight reservoirs | |
| CN114233283A (en) | Compressibility evaluation method for shale oil reservoir | |
| CN117973258A (en) | A fluid-solid coupling prediction method for the initiation pressure of oriented perforating hydraulic fracturing | |
| Igor et al. | Specifics of mechanical and strength rock properties estimation for wells drilling and exploitation | |
| CN110145286A (en) | A Design Method for Completion Engineering of Low Permeability Reservoir or Gas Reservoir | |
| Tan et al. | Leak-off mechanism and pressure prediction for shallow sediments in deepwater drilling | |
| CN116306374A (en) | A method for predicting the pressure bearing capacity of deep fractured formation plugging |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| PB01 | Publication | ||
| PB01 | Publication | ||
| SE01 | Entry into force of request for substantive examination | ||
| SE01 | Entry into force of request for substantive examination | ||
| GR01 | Patent grant | ||
| GR01 | Patent grant |