PDC environment relative energy consumption while drilling calculation method and device

Abstract

The present application relates to a kind of oil and gas drilling engineering and rock physics cross technical field, it is a kind of PDC relative energy consumption environment while drilling calculation method, device, including based on all while drilling sampling point corresponding well depth's cuttings remodeling body measured Poisson's ratio, theoretical equivalent Poisson's ratio and theoretical equivalent shear modulus, determine the shear attenuation coefficient of each well depth, and establish corresponding formation powder grain slip coefficient curve;Relative shear coupling loss index of each well depth is determined in combination with formation powder grain slip coefficient curve, theoretical equivalent Poisson's ratio and theoretical equivalent shear modulus.The present application combines while drilling cuttings mineral composition determination and cuttings remodeling body acoustic response measurement result, realize the relative energy consumption of PDC drill bit environment while drilling characterization, especially when drilling in dense rock formation, it is different from the energy consumption evaluation technology based on traditional engineering parameter, increase the end information of stratum obtained from while drilling cuttings sample, so that the energy consumption change of relatively dense formation can be described based on particle contact physical quantity.

Description

Technical Field

[0001] This invention relates to the field of interdisciplinary technology of oil and gas drilling engineering and rock physics, and is a method and device for calculating relative energy consumption while drilling in a PDC environment. Background Technology

[0002] In oil and gas drilling, the energy consumption level of the drill bit in breaking rocks directly affects the drilling rate, drill bit wear, and drilling cycle. In engineering, it is necessary to quantify the energy consumption of breaking rocks to support the monitoring of drilling efficiency and parameter optimization.

[0003] In the existing engineering system, Mechanical Specific Energy (MSE) is one of the most representative energy consumption indicators. For example, it originates from the definition of "energy required for rock breaking per unit volume" proposed by TEALER. The concept of specific energy in rockdrilling[J]. International Journal of Rock Mechanics and Mining Sciences&Geomechanics Abstracts, 1965, 2(1): 57-73. DOI:10.1016 / 0148-9062(65)90022-7. In engineering, it can be calculated by measurable operating parameters such as drilling pressure, torque, rotation speed and mechanical drilling speed, thus forming the core means of monitoring energy consumption while drilling and post-drilling review; multiple studies on the correlation between MSE and rock breaking energy consumption have further developed the process of real-time monitoring of engineering energy consumption and guiding drilling speed optimization, such as PESSIER RC, FEAR M J. Quantifying Common Drilling Problems With MechanicalSpecific Energy and a Bit-Specific Coefficient of Sliding Friction[C] / / SPE Annual Technical Conference and Exhibition. 1992: SPE-24584-MS. DOI:10.2118 / 24584-MS. combines MSE with concepts such as drill bit specific slip friction coefficient to quantify common drilling inefficiencies and friction slip-related problems; MOHANK, ADIL F, SAMUEL R. Tracking Drilling Efficiency Using Hydro-Mechanical Specific Energy[C] / / SPE / IADC Drilling Conference and Exhibition. 2009: SPE-119421-MS. DOI:10.2118 / 119421-MS. proposes an optimized hydraulic mechanical specific energy concept, which introduces a hydraulic term that matches the energy required for drilling and overcomes the strength and stress of the drilled formation to identify inefficient drilling conditions; DETOURNAYE, DEFOURNY P. A phenomenological model for the drilling action of drag bits[J].The International Journal of Rock Mechanics and Mining Sciences & Geomechanics Abstracts, 1992, 29(1): 13-23, proposed a phenomenological model of the rock-breaking response of PDC drill bits. Based on this model, DETOURNAY E, RICHARD T, SHEPHERD M. Drilling response of drag bits: Theory and experiment[J]. International Journal of Rock Mechanics and Mining Sciences, 2008, 45(8): 1347-1360. DOI:10.1016 / j.ijrmms.2008.01.010, presented a complete model combining theory and experiment, revealing the mechanism by which cutting and frictional contact contribute to mechanical specific energy in PDC environments, as well as the intrinsic reasons for the increase in rock-breaking energy consumption caused by friction, wear, mud packing, and abnormal cleanliness. The above research combines engineering assessment with the diagnosis of drilling inefficiency problems, forming a relatively mature technical approach of calculating MSE based on engineering parameters and conducting energy consumption evaluation.

[0004] However, this approach, in terms of mechanism, still belongs to the post-hoc evaluation based on engineering input and drilling response. Its values ​​are influenced not only by formation drillability but also by factors such as drill string assembly, operating strategies, wellbore cleanliness, and drill bit wear and vibration. Therefore, when engineering conditions change or historical calibration from adjacent wells is lacking, it is difficult to consistently attribute energy consumption changes to formation-level control factors. From the perspective of rock breaking mechanisms, especially in PDC bit rock breaking environments, the enhanced frictional contact and weakened shear slip commonly found in relatively tight layers significantly affect torque and energy consumption. However, methods for measuring geological and geophysical parameters and corresponding conceptual systems for this aspect have not yet been established. While rock physics research centered on mineral composition and contact mechanics has been used for equivalent elastic parameter prediction and reservoir mechanics interpretation, it typically does not directly address energy consumption characterization during drilling. Furthermore, there is a lack of research and innovation on how to establish a connection between mineral composition, equivalent framework properties, weakened contact shear slip, and related energy consumption changes in friction, slip, and grinding layers under PDC conditions using formation sample information.

[0005] Therefore, current drilling energy consumption assessments (including real-time optimization and prediction) generally follow the engineering energy consumption evaluation route, mainly relying on real-time monitoring and post-analysis of drilling end engineering parameters or data-driven model predictions, such as: CHEN X, WANG R, YANG J, et al. A new intelligent optimization method for drilling parameters of extended reach wells based on mechanical specific energy and machine learning[J]. Petroleum Research, 2025, 10(3): 485-500.DOI:10.1016 / j.ptlrs.2025.03.002. and LIUW, FENG J, ZHU X, et al. Real-time mechanical specific energy prediction for optimizing the drilling parameters using CNN-LSTM model[J]. Petroleum Science and Technology, 2025, 43(18):2413-2436. DOI:10.1080 / 10916466.2024.2385727., The core technology of MSE prediction and drilling parameter optimization based on machine learning or deep learning is still engineering parameter mapping and calibration, but it does not introduce formation end indicators obtained from rock physics and mineral property measurements based on samples returned during drilling. Furthermore, for example: Chinese Patent Publication No. CN114818451B discloses a method, device, storage medium, and equipment for predicting mechanical drilling rate; Chinese Patent Publication No. CN119989852B discloses a method, device, and storage medium for optimizing drilling parameters, which determines multiple drilling parameter optimization decision indicators based on predicted mechanical specific energy information, target mechanical drilling rate prediction model, target torque prediction model, and drilling parameters to be optimized; Chinese Patent Publication No. CN119026441B discloses a drilling parameter optimization method and device, which uses historical logging data and historical drilling parameter data to drive and constructs a drilling parameter optimization method using a random forest regression model; Chinese Patent Publication No. CN114215499B discloses a method for optimizing drilling parameters based on intelligent algorithms, which is a method for establishing a mechanical drilling rate prediction network model by combining BP neural network and genetic algorithm.The above methods all use engineering parameters as the main input to construct prediction models, which have obvious operating condition dependence and are difficult to form a stable reference before or in the early stage of drilling when drilling new wells.

[0006] On the other hand, the field of rock physics has formed a theoretical system for estimating the equivalent framework modulus based on mineral composition (for example, using various boundary models). (References: HASHIN Z, SHTRIKMAN S. A variational approach to the theory of the elastic behavior of multiphase materials[J]. Journal of the Mechanics and Physics of Solids, 1963, 11(2): 127-140. DOI:10.1016 / 0022-5096(63)90060-7., WALPOLE L J. On bounds for the overall elastic moduli of inhomogeneous systems—I[J]. Journal of the Mechanics and Physics of Solids, 1966, 14(3): 151-162. DOI:10.1016 / 0022-5096(66)90035-4., WALPOLE L J. Onbounds for the overall elastic moduli of inhomogeneous systems). systems—II[J]. Journal of the Mechanics and Physics of Solids, 1966, 14(5): 289-301. DOI:10.1016 / 0022-5096(66)90025-1., BERRYMAN JG, PRIDE SR, WANG H F. Adifferential scheme for elastic properties of rocks with dry or saturatedcracks[J]. Geophysical Journal International, 2002, 151(2): 597-611. DOI:10.1046 / j.1365-246X.2002.01801.x., BERRYMAN J G. Mixture Theories for RockProperties[M] / / Rock Physics&Phase Relations. 1995: 205-228. DOI:10.1029 / RF003p0205; The contact model used is MINDLIN R D.Compliance of Elastic Bodies in Contact[J]. Journal of Applied Mechanics, 1949,16(3): 259-268. DOI:10.1115 / 1.4009973. and MINDLIN RD, DERESIEWICZ H. Elastic Spheres in Contact UnderVarying Oblique Forces[J]. Journal of Applied Mechanics, 2021, 20(3): 327-344. DOI:10.1115 / 1.4010702., DVORKIN J, NUR A, YIN H. Effectiveproperties of cementedgranular materials[J]. Mechanics of Materials, 1994, 18(4): 351-366.DOI:10.1016 / 0167-6636(94)90044-2. etc.), and WALTON K. The effective elastic moduli of arandom packing of spheres[J]. Journal of the Mechanics and Physics of Solids,1987, 35(2): 213-226.DOI:10.1016 / 0022-5096(87)90036-6. and BACHRACH R, AVSETH P. Rock physics modeling of unconsolidated sands: Accounting for nonuniform contacts and heterogeneous stress fields in the effective media approximationwith applications to hydrocarbon exploration[J]. Geophysics,2008, 73(6):E197-E209. DOI:10.1190 / 1.2985821. However, this type of research mainly focuses on the prediction of elastic parameters or mechanical interpretation, and its calculation results lack a direct link with engineering energy consumption assessment.

[0007] In summary, engineering energy consumption evaluation methods and equivalent skeleton modeling based on mineral composition and contact mechanics have long developed independently. A technical route has not yet been formed that can utilize information from drilling cuttings samples to introduce mineral composition, equivalent skeleton properties, and particle contact shear coupling characteristics into a unified calculation framework to construct a relative energy consumption characterization. Summary of the Invention

[0008] This invention provides a method and apparatus for calculating relative energy consumption while drilling in a PDC environment, which overcomes the shortcomings of the prior art. It can effectively solve the problem that existing drilling energy consumption assessment methods rely on drilling operation engineering parameters and cannot use information related to drilling cuttings samples to characterize particle contact shear attenuation features to calculate energy consumption while drilling.

[0009] One of the technical solutions of this invention is achieved through the following measures: a method for calculating relative energy consumption in a PDC environment while drilling, comprising: In the selected well section of the target well, based on the measured Poisson's ratio, theoretical equivalent Poisson's ratio and theoretical equivalent shear modulus of the rock cuttings remodeled body at the corresponding well depth of all drilling sampling points, the shear attenuation coefficient of the formation after pulverization at each well depth is determined, and the corresponding formation powder grain slip coefficient curve is established. The relative shear coupling loss index at each well depth was determined by using the formation powder grain slip coefficient curve and the theoretical equivalent Poisson's ratio and theoretical equivalent shear modulus at each well depth. in, For well depth d i The relative shear coupling loss index at the location; For well depth d i The grain slip coefficient of the formation powder at that location; For well depth d i The theoretical equivalent Poisson's ratio at that location; For well depth d i Theoretical equivalent shear modulus at the point; For well depth d i The porosity can be measured by nuclear magnetic resonance (NMR) or compensated neutron porosity during drilling, or estimated porosity based on modeling of adjacent wells / blocks. Critical porosity; m It is the porosity index; To obtain the maximum value.

[0010] The following are further optimizations and / or improvements to the above-mentioned technical solution: Based on the measured Poisson's ratio, theoretical equivalent Poisson's ratio, and theoretical equivalent shear modulus of the remodeled cuttings at all drilling sampling points at corresponding well depths, the shear attenuation coefficients after formation pulverization at each well depth are determined, including: Obtain the measured Poisson's ratio, theoretical equivalent Poisson's ratio, and theoretical equivalent shear modulus of the rock cuttings remodeled at the corresponding well depth for all drilling sampling points in the selected well section of the target well.

[0011] Based on the measured Poisson's ratio and theoretical equivalent Poisson's ratio of the rock cuttings at each well depth, the shear attenuation coefficient of the formation after pulverization at each well depth was determined. in, For well depth d i The shear attenuation coefficient at that point; For well depth d i Measured Poisson's ratio of the reconstituted rock fragments at the location; This is the theoretical equivalent Poisson's ratio.

[0012] The formation powder grain slip coefficient was determined by using the shear attenuation coefficient at each well depth, and the resulting formation powder grain slip coefficient curve is shown below: in, and These represent taking the maximum / minimum value respectively; For well depth d i The grain slip coefficient of the formation powder at that location; For well depth d i The shear attenuation coefficient at that point.

[0013] The above-mentioned acquisition of the theoretical equivalent Poisson's ratio and theoretical equivalent shear modulus at the corresponding well depths of the drilling sampling points includes: Obtain cuttings samples returned from the well depth corresponding to the drilling sampling point; After pretreatment, grinding and screening of the rock cuttings samples, powder samples from the depth of the well were obtained, and X-ray diffraction tests were performed on them to determine the mineral composition ratio at the depth of the well. Based on the mineral composition ratio at the depth of the well, the equivalent skeleton modulus of the multiphase mineral system at the depth of the well is calculated using the multiphase mineral equivalent skeleton modulus calculation method based on random structure cloud, and the corresponding theoretical equivalent Poisson's ratio and theoretical equivalent shear modulus are obtained.

[0014] The above-mentioned acquisition of the measured Poisson's ratio of the cuttings remodeling at the corresponding well depth at the drilling sampling point includes: Obtain cuttings samples returned from the well depth corresponding to the drilling sampling point; After pretreatment, grinding and screening of the rock cuttings samples, powder samples from the depth of the well were obtained. The powder sample from the depth of the well was made into a corresponding rock cuttings remodeling body. The PDC drill bit environmental rock cuttings acoustic logging curve acquisition method was used to obtain the P-wave transit time and S-wave transit time of the rock cuttings remodeling body at the depth of the well. Then, the measured Poisson's ratio of the rock cuttings remodeling body at the depth of the well was calculated. in, For well depth d i P-wave velocity of the remodeled rock debris at the location, ; For well depth d i Shear wave velocity of the remodeled rock debris at the location, ; For well depth d i P-wave time difference of the remodeled rock debris at the location; For well depth d i Shear wave time difference of the rock debris remodeling body at the location; For well depth d i Measured Poisson's ratio of the rock fragment remodeling at the location.

[0015] The second technical solution of the present invention is achieved through the following measures: a PDC environment relative energy consumption calculation device while drilling, comprising: The first calculation unit, in the selected well section of the target well, determines the shear attenuation coefficient of the formation after pulverization at each well depth based on the measured Poisson's ratio, theoretical equivalent Poisson's ratio, and theoretical equivalent shear modulus of the rock cuttings remodeled body at all drilling sampling points at corresponding well depths, and establishes the corresponding formation powder grain slip coefficient curve. The second calculation unit uses the formation powder grain slip coefficient curve and the theoretical equivalent Poisson's ratio and theoretical equivalent shear modulus at each well depth to determine the relative shear coupling loss index at each well depth. in, For well depth d i The relative shear coupling loss index at the location; For well depth d i The grain slip coefficient of the formation powder at that location; For well depth d i The theoretical equivalent Poisson's ratio at that location; For well depth d i Theoretical equivalent shear modulus at the point; For well depth d i The porosity can be measured by nuclear magnetic resonance (NMR) or compensated neutron porosity during drilling, or estimated porosity based on modeling of adjacent wells / blocks. Critical porosity; m It is the porosity index; To obtain the maximum value.

[0016] The following are further optimizations and / or improvements to the above-mentioned technical solution: The aforementioned first computing unit includes: The basic data acquisition module acquires the measured Poisson's ratio, theoretical equivalent Poisson's ratio, and theoretical equivalent shear modulus of the rock cuttings remodeled at the corresponding well depth for all drilling sampling points in the selected well section of the target well.

[0017] The shear attenuation coefficient calculation module determines the shear attenuation coefficient of the formation after pulverization at each well depth based on the measured Poisson's ratio and theoretical equivalent Poisson's ratio of the rock cuttings remodeled body at each well depth. in, For well depth d i The shear attenuation coefficient at that point; For well depth d i Measured Poisson's ratio of the reconstituted rock fragments at the location; Theoretically equivalent Poisson's ratio; The curve acquisition module uses the shear attenuation coefficient at each well depth to determine the corresponding formation powder grain slip coefficient, thus forming a formation powder grain slip coefficient curve. in, and These represent taking the maximum / minimum value respectively; For well depth d i The grain slip coefficient of the formation powder at that location.

[0018] The aforementioned basic data acquisition module includes: The equivalent skeleton modulus acquisition module obtains the theoretical equivalent Poisson's ratio and theoretical equivalent shear modulus at the corresponding well depths of the drilling sampling points, including: Obtain cuttings samples returned from the well depth corresponding to the drilling sampling point; After pretreatment, grinding and screening of the rock cuttings samples, powder samples from the depth of the well were obtained, and X-ray diffraction tests were performed on them to determine the mineral composition ratio at the depth of the well. Based on the mineral composition ratio at the depth of the well, the equivalent skeleton modulus of the multiphase mineral system at the depth of the well is calculated using the multiphase mineral equivalent skeleton modulus calculation method based on random structure cloud, and the corresponding theoretical equivalent Poisson's ratio and theoretical equivalent shear modulus are obtained. The acoustic logging curve acquisition module acquires the measured Poisson's ratio of the remodeled cuttings at the corresponding well depth at the drilling sampling point, including: Obtain cuttings samples returned from the well depth corresponding to the drilling sampling point; After pretreatment, grinding and screening of the rock cuttings samples, powder samples from the depth of the well were obtained. The powder sample from the depth of the well was made into a corresponding rock cuttings remodeling body. The PDC drill bit environmental rock cuttings acoustic logging curve acquisition method was used to obtain the P-wave transit time and S-wave transit time of the rock cuttings remodeling body at the depth of the well. Then, the measured Poisson's ratio of the rock cuttings remodeling body at the depth of the well was calculated. in, For well depth d i P-wave velocity of the remodeled rock debris at the location, ; For well depth d i Shear wave velocity of the remodeled rock debris at the location, ; For well depth d i P-wave time difference of the remodeled rock debris at the location; For well depth d i Shear wave time difference of the rock debris remodeling body at the location; For well depth d i Measured Poisson's ratio of the rock fragment remodeling at the location.

[0019] This invention is a method that does not rely on drilling operation engineering parameters but utilizes information from drilling cuttings samples to reflect the particle contact shear coupling state and uses it for relative energy consumption characterization calculations. Specifically, based on the measured Poisson's ratio and theoretical equivalent Poisson's ratio of the reconstituted cuttings at all drilling sampling points at corresponding well depths, the shear attenuation coefficient of the formation after pulverization at each well depth is determined. Using the formation powder grain slip coefficient as a bridge, this coefficient is transformed into a continuously calculable quantitative index, the "relative shear coupling loss index," forming a parameter mapping link from the description of "contact shear coupling state" to "relative energy consumption characterization." Unlike traditional energy consumption evaluation techniques based on engineering parameters, this invention adds formation-end information obtainable from drilling cuttings samples, enabling the energy consumption changes in relatively dense formations to be described based on particle contact physical quantities, thus improving the physical interpretability of energy consumption changes. Attached Figure Description

[0020] AppendixFigure 1 This is a schematic diagram of the process for calculating relative energy consumption in a PDC environment during drilling, as provided in an embodiment of the present invention.

[0021] Appendix Figure 2 A schematic diagram of the process for constructing the grain slip coefficient curve of formation powder provided in an embodiment of the present invention.

[0022] Appendix Figure 3 A schematic flowchart illustrating the method for obtaining the measured Poisson's ratio, theoretical equivalent Poisson's ratio, and theoretical equivalent shear modulus of rock cuttings remodeled at deep well depths, as provided in an embodiment of the present invention.

[0023] Appendix Figure 4 This is a schematic diagram of the XRD measurement results and equivalent skeleton modulus calculation results of well X provided in an embodiment of the present invention, wherein, Figure 4 (a) is the equivalent structural cloud skeleton bulk modulus-shear modulus distribution map calculated based on the mineral composition distribution measured by XRD at a depth of 4500m in Well X. Figure 4 (b) is the equivalent structural cloud skeleton Poisson's ratio-Young's modulus distribution map calculated based on the mineral composition distribution measured by XRD at a depth of 4500m in Well X. Figure 4 (c) shows the XRD measurement results of the target depth section of the X well embodiment and the equivalent skeleton modulus curve calculated based on XRD.

[0024] Appendix Figure 5 This is a schematic diagram showing the P / S wave waveform, wave velocity, and Poisson's ratio of the remolded rock fragments in Well X, provided in an embodiment of the present invention. Figure 5 (a) The original waveform of the P-wave measurement of the remodeled body. Figure 5 (b) The original waveform for S-wave measurement of the reshaped body. Figure 5 (c) is the P-wave time difference curve of the remodeled body. Figure 5 (d) is the S-wave time difference curve of the remodeled body. Figure 5 (e) is the P-wave velocity curve of the reshaped body; Figure 5 (f) is the S-wave velocity curve of the reshaped body. Figure 5 (g) is the Poisson's ratio curve of the remodeled body.

[0025] Appendix Figure 6 This is a schematic diagram illustrating the relative energy consumption estimation of Well X and its comparison with actual engineering results provided in an embodiment of the present invention.

[0026] Appendix Figure 7 This is a schematic diagram of the structure of the PDC environment relative energy consumption calculation device for drilling provided in an embodiment of the present invention. Detailed Implementation

[0027] The present invention is not limited to the following embodiments, and the specific implementation can be determined according to the technical solution of the present invention and the actual situation.

[0028] Those skilled in the art will understand that, unless otherwise stated, in the embodiments of this application, "module" or "unit" refers to a computer program or part of a computer program with a predetermined function, which works together with other related parts to achieve a predetermined goal, and can be implemented, wholly or partially, using software, hardware (such as processing circuitry or memory), or a combination thereof. Similarly, a processor (or multiple processors or memory) can be used to implement one or more modules or units. Furthermore, each module or unit can be part of an overall module or unit that includes the functionality of that module or unit.

[0029] In addition, in the embodiments of this application, "multiple" refers to two or more, and "first" and "second" are used to distinguish descriptions and should not be construed as implying relative importance.

[0030] Based on this, the technical solution of this application will be described and explained below with reference to several examples.

[0031] Example 1: As shown in the attached document Figure 1 As shown in the figure, this invention discloses a method for calculating relative energy consumption in a PDC environment during drilling, including: Step S110: In the selected well section of the target well, based on the measured Poisson's ratio, theoretical equivalent Poisson's ratio and theoretical equivalent shear modulus of the rock cuttings remodeled body at the corresponding well depth of all drilling sampling points, determine the shear attenuation coefficient of the formation after pulverization at each well depth, and establish the corresponding formation powder grain slip coefficient curve. Step S120: Using the formation powder grain slip coefficient curve and the theoretical equivalent Poisson's ratio and theoretical equivalent shear modulus at each well depth, determine the relative shear coupling loss index at each well depth. in, For well depth d i The relative shear coupling loss index at the location; For well depth d i The grain slip coefficient of the formation powder at that location; For well depth d i The theoretical equivalent Poisson's ratio at that location; For well depth d i Theoretical equivalent shear modulus at the point; For well depth d i The porosity can be measured by nuclear magnetic resonance (NMR) or compensated neutron porosity during drilling, or estimated porosity based on modeling of adjacent wells / blocks. Critical porosity; m It is the porosity index; To obtain the maximum value.

[0032] In the rock breaking scenario of PDC drill bit, mechanical energy consumption is not only determined by rock strength and the chip formation process, but also closely related to the shear coupling state of the particle contact network. The weakening of shear slip at the interface between the grinding layer and the particles will change the tangential contact stiffness, thereby affecting the energy transfer efficiency and manifesting as a change in the level of mechanical energy consumption.

[0033] Furthermore, under relatively dense formation conditions, the main controlling factor of drilling energy consumption gradually shifts from being controlled by porosity and microfractures to being jointly controlled by the inherent rock properties of the formation and the particle contact state. Therefore, in rock physics contact theory, it is shown that the particle contact shear stiffness can be described by the Hertz–Mindlin framework and its shear correction form (e.g., MINDLIN R D. Compliance of Elastic Bodies in Contact[J]. Journal of Applied Mechanics,1949, 16(3): 259-268. DOI:10.1115 / 1.4009973.), where the shear attenuation coefficient is used to characterize the degree of shear weakening during the transition of particle contact from complete adhesion to partial slip. Moreover, mineral composition determines the equivalent skeleton elastic properties, while the acoustic response of the remodeled body can reflect the equivalent shear coupling state of the real particle contact network. Therefore, the particle contact shear weakening characteristics can be characterized by the difference between the theoretical equivalent Poisson's ratio and the measured Poisson's ratio of the remodeled body prepared under specific control variable conditions.

[0034] In summary, this embodiment determines the shear attenuation coefficient after formation pulverization based on the measured Poisson's ratio and theoretical equivalent Poisson's ratio of the remodeled rock cuttings at the corresponding well depths of the drilling sampling points. The shear attenuation coefficient reflects the strength of the average shear attenuation between powder particles in the powder grain pack and can be used as a parameter for weakening particle contact shear. Based on the shear attenuation coefficient after formation pulverization, the corresponding formation powder grain slip coefficient is determined, forming the formation powder grain slip coefficient curve for the selected well section. Here, the formation powder grain slip coefficient reflects the strength of the ability of powder particles to generate relative slip between powder particles under the same external pressure. The larger the coefficient, the worse the shear carrying capacity between powder particles and the easier it is for rock-breaking energy to be converted into relative slip. This slip approximately represents the combined effect of relative sliding of pulverized medium layer particles, mud bagging in dense layers, and drill bit friction energy consumption. It can usually lead to more severe mud bagging and ineffective stick-slip, and therefore has a positive correlation with mechanical specific energy in dense layers. Finally, by combining the effects of porosity (obtained through measurements while drilling or data from adjacent wells) and inherent rock properties (shear modulus, Poisson's ratio, etc.), the relative shear coupling loss index of drilling is defined.

[0035] This invention provides a method that, without relying on drilling operation engineering parameters, utilizes information from drilling cuttings samples to reflect the particle contact shear coupling state and uses it for relative energy consumption characterization calculations. Specifically, based on the measured Poisson's ratio and theoretical equivalent Poisson's ratio of the reconstituted cuttings at all drilling sampling points at corresponding well depths, the shear attenuation coefficient of the formation after pulverization at each well depth is determined. Using the formation powder grain slip coefficient as a bridge, this coefficient is transformed into a continuously calculable quantitative index, the "relative shear coupling loss index," forming a parameter mapping link from the description of "contact shear coupling state" to "relative energy consumption characterization." Unlike traditional energy consumption evaluation techniques based on engineering parameters, this invention adds formation-end information obtainable from drilling cuttings samples, enabling the energy consumption variation in relatively dense formations to be described based on particle contact physical quantities, thus improving the physical interpretability of energy consumption changes.

[0036] Example 2: As shown in the attached document Figure 2 As shown, this embodiment of the invention is a further optimization of the above embodiment. In the selected well section of the target well, based on the measured Poisson's ratio, theoretical equivalent Poisson's ratio, and theoretical equivalent shear modulus of the reconstituted rock cuttings at all drilling sampling points at corresponding well depths, the shear attenuation coefficient of the formation after pulverization at each well depth is determined, and the corresponding formation powder grain slip coefficient curve is established, including: Step S210: Obtain the measured Poisson's ratio, theoretical equivalent Poisson's ratio, and theoretical equivalent shear modulus of the rock cuttings remodeled at the corresponding well depth for all drilling sampling points in the selected well section of the target well.

[0037] Step S220: Based on the measured Poisson's ratio and theoretical equivalent Poisson's ratio of the rock cuttings remodeled bodies at each well depth, determine the shear attenuation coefficient of the formation after pulverization at each well depth. in, For well depth d i The shear attenuation coefficient at that point; For well depth d i Measured Poisson's ratio of the reconstituted rock fragments at the location; This is the theoretical equivalent Poisson's ratio.

[0038] In this embodiment, the coefficient reflects the strength of the average shear attenuation between powder particles in the powder grain pack, and its theoretical value range is [range missing]. Theoretically, when When the intergranular shear is strongest, the powder grain packing model is completely equivalent to the Hertz-Mindlin contact model; when At that time, there must exist a measured Poisson's ratio for the reconstituted rock fragments. That is, the ideal equivalent Poisson contact model (also known as the Walton model); when In this case, the powder contact model is consistent with the findings of Manificat & Guéguen.

[0039] Considering that the Poisson's ratio may be negative in actual measurements (i.e., the corresponding...) For all recorded well depths d i The corresponding measured shear attenuation coefficient ,use Normalization is used to define and calculate the formation powder grain slip coefficient curve, where Minimum cuttings logging depth / initial well depth; (The maximum cuttings logging depth).

[0040] Step S230: Determine the corresponding formation powder grain slip coefficient using the shear attenuation coefficient at each well depth, and form a formation powder grain slip coefficient curve; in, and These represent taking the maximum / minimum value respectively; For well depth d i The slip coefficient of the formation powder grains can also be defined as the dissipation coefficient. It reflects the strength of the ability of powder particles to generate relative slip between powder particles under the same external pressure when they come into contact. The larger the value, the worse the shearing and carrying capacity between powder particles, and the easier it is for rock-breaking energy to be converted into relative slip.

[0041] Example 3: As shown in the attached document Figure 3 As shown, the embodiment of the present invention further optimizes the above embodiment, wherein obtaining the measured Poisson's ratio, theoretical equivalent Poisson's ratio, and theoretical equivalent shear modulus of the cuttings remodeling body at the well depth corresponding to the drilling sampling point includes: Step S310: Obtain the cuttings sample returned from the well depth corresponding to the drilling sampling point.

[0042] Step S320: After pretreatment and grinding and screening of the rock cuttings sample, a powder sample from the depth of the well is obtained, and X-ray diffraction test is performed on it to determine the mineral composition ratio at the depth of the well. This step specifically includes: (1) Clean the rock cuttings samples to remove drilling fluid residue, mud coating and surface contaminants. After cleaning, dry them and then manually or with image assistance screen the dried rock cuttings samples to remove obvious non-co-layer fragments (non-co-layer fragments are large and have a significantly different color and shape from the rock cuttings of the same layer, and have a significantly different degree of surface weathering or rounding, thus removing obvious non-co-layer fragments). (2) Randomly sample the remaining rock fragments that have not been screened out, and mechanically crush and repeatedly grind the selected samples into powder. Then, pass the ground powder through a screen of a predetermined mesh size to unify the particle size distribution (in the example, a 100 to 150 mesh screen can be selected) to form a powder sample at the depth of the well. (3) Perform X-ray diffraction (XRD) tests on the powder sample to determine the mineral composition at the depth of the well. , N This represents the total number of phases in a crystalline mineral. j For mineral phase sequence numbers; This step specifically includes: (a) Place the powder sample in a sample carrier and spread the sample using a scraping method to make the powder surface flat and dense, so as to improve the representativeness of the diffraction peaks and reduce the influence of preferred orientation. (b) Obtain diffraction patterns using XRD equipment; (c) Combining mineral diffraction reference databases (such as the ICDD-PDF database) with existing geological experience and knowledge of the mineral composition of the drilling block, conduct phase identification and quantitative analysis of the diffraction spectra to obtain the mineral component content at the well depth and determine the mineral component proportion. ; Furthermore, the Rietveld refinement method or internal standard method can be used for analysis and calibration to improve the accuracy of mineral content calculation.

[0043] Step S330: Based on the mineral composition ratio at the depth of the well, the equivalent skeleton modulus of the multiphase mineral system at the depth of the well is calculated using the multiphase mineral equivalent skeleton modulus calculation method based on random structure cloud, and the corresponding theoretical equivalent Poisson's ratio and theoretical equivalent shear modulus are obtained. In this step, the method for calculating the equivalent framework modulus of multiphase minerals based on random structure clouds is specifically described in the Chinese patent publication document CN122392699A, and can be briefly summarized as follows: (1) Construct an atom block assembly consisting of the elastic modulus and volume fraction of the mineral phase; (2) Based on the two-phase recursive Hashin-Shtrikman-Walpole boundary calculation, atomic blocks are randomly paired and recursively merged to generate equivalent sub-blocks; (3) Given the block parameters, Dirichlet random allocation parameters and structure control parameters, the structure pool is recursively iterated until a single equivalent block is obtained. (4) Repeat the random structure generation process to obtain the well depth. The corresponding equivalent skeleton modulus structure cloud and its statistical estimation results.

[0044] In this step, when calculating the equivalent framework modulus of a multiphase mineral system at a certain well depth using the multiphase mineral equivalent framework modulus calculation method based on random structure clouds, a mineral structure hierarchy classification strategy based on geological understanding is introduced. Specifically, the well depth... d i Processing mineral composition percentages determined by X-ray diffraction testing While the input itself is deterministic, the structural roles of each mineral in the strata (diagenetic framework minerals, secondary framework minerals, inclusion minerals, cementing minerals) can be classified based on block geological understanding, sedimentary diagenetic patterns, or existing interpretation experience. Based on the aforementioned prior structural understanding, this embodiment employs a layered equivalent calculation method, the steps of which include: (1) Select the matrix mineral set of the diagenetic framework, construct the set of atomic blocks of the bottom framework, and call the method for calculating the equivalent framework modulus of multiphase minerals based on random structure cloud disclosed in Chinese patent publication document CN122392699A to calculate the equivalent framework modulus of the bottom layer. (2) Based on the bottom skeleton equivalent block, the secondary skeleton minerals are added to the structure pool, and the two-phase recursive equivalent calculation is continued to obtain the extended skeleton equivalent modulus. It should be noted that when the prior knowledge can only distinguish between skeleton minerals and non-skeleton minerals, but cannot further distinguish between diagenetic skeleton minerals and secondary skeleton minerals, the two are uniformly merged into a skeleton mineral set and input as a skeleton atomic block to perform the above calculation. (3) Add the inclusion minerals and cementing minerals to the structural pool and continue to perform recursive equivalent calculations to obtain the final formation equivalent skeleton modulus.

[0045] In the absence of the aforementioned mineral structural role classification or prior geological knowledge, according to the Chinese patent publication document CN122392699A, the method for calculating the equivalent framework modulus of multiphase minerals based on random structural clouds involves inputting all mineral components as atomic blocks into the structural cloud computing process at once to directly obtain the equivalent framework modulus. When only framework minerals can be identified but inclusions or cementing minerals cannot be identified, all remaining minerals are uniformly incorporated into the structural pool for merged calculation.

[0046] Therefore, this step can yield wells of any depth. d i The equivalent skeleton properties at the location are used for subsequent calculations, specifically the statistical average values ​​of the structure cloud in the multiphase mineral equivalent skeleton modulus calculation method based on random structure clouds disclosed in Chinese Patent Publication No. CN122392699A. These properties include: in, Well depth d iThe equivalent bulk modulus, equivalent shear modulus, equivalent Poisson's ratio, and equivalent Young's modulus at the given location. and Used for subsequent calculation of shear attenuation coefficient and estimation of relative energy consumption.

[0047] Step S340: The powder sample from the depth of the well is made into a corresponding rock cuttings remodeling body. The PDC drill bit environmental rock cuttings acoustic logging curve acquisition method is used to obtain the P-wave transit time and S-wave transit time of the rock cuttings remodeling body at the depth of the well. Then, the measured Poisson's ratio of the rock cuttings remodeling body at the depth of the well is calculated. in, For well depth d i P-wave velocity of the remodeled rock debris at the location, ; For well depth d i Shear wave velocity of the remodeled rock debris at the location, ; For well depth d i P-wave time difference of the remodeled rock debris at the location; For well depth d i Shear wave time difference of the rock debris remodeling body at the location; For well depth d i Measured Poisson's ratio of the rock fragment remodeling at the location.

[0048] In this step, the well depth will be... d i When preparing the corresponding rock fragment remodeling body from the powder sample, a fixed radius and mold size are selected. The powder sample is placed into the mold and pressed under constant vertical pressure to obtain a cylindrical disc-shaped rock fragment remodeling body. In this embodiment, a vertical pressure of 30 MPa can be uniformly used, and the holding time can be uniformly set to 10 to 15 seconds.

[0049] The specific steps for obtaining the measured Poisson's ratio of the remodeled rock cuttings at a deep well depth include: (1) Using the method and apparatus for obtaining PDC drill bit environmental cuttings acoustic logging curves disclosed in Chinese patent application document No. 2025118660023, the well depth was obtained. d iThe thickness and P-wave (P-wave) and S-wave (S-wave) waveforms of the remolded cuttings are described in detail, but the specific process will not be repeated here. It should be noted that this process can be performed immediately after each remolded cuttings is prepared during drilling, or it can be performed uniformly after all remolded cuttings are prepared; however, in order to ensure the timeliness of the measurement, this embodiment adopts the technical solution of measuring immediately after the remolded cuttings are prepared.

[0050] (2) For the acquired dataset (thickness and longitudinal and transverse waveforms), the method and apparatus for obtaining PDC drill bit environmental cuttings acoustic logging curves disclosed in Chinese patent application document No. 2025118660023 were also used to obtain the normalized longitudinal wave envelope function after data slicing, iterative deconvolution, normalization, multiplication by attenuation factor, and calculation of envelope function. and normalized transverse wave envelope function The specific technical steps will not be elaborated here; then, the acoustic time difference extraction technology described in the patent is used to extract the time difference from... and Extract and calculate well depth Corresponding P-wave time of rock debris remodeling Shear wave time difference with rock debris remodeling Then calculate the corresponding rock debris remodeling wave velocity, the formula is: in, For well depth d i P-wave velocity of the remodeled rock debris at the location, For well depth d i Measured Poisson's ratio of the rock fragment remodeling at the location.

[0051] (3) Calculate the well depth using the wave velocity of the remolded rock cuttings obtained from the extraction calculation. d i Measured Poisson's ratio of the rock fragment remodeling at the location The calculation formula is: In summary, the Poisson's ratio of the remodeled body can be measured and calculated in real time at any drilling depth, which can be used for subsequent relative energy consumption estimation.

[0052] Example 4: This example is a further optimization of the above examples. The process of constructing the relative shear coupling loss exponent formula at deep well depth includes: The relative shear coupling loss index of drilling is defined by combining the combined effects of porosity (obtained through measurements while drilling or adjacent well data) and inherent rock properties (tangential stiffness, shear modulus, Poisson's ratio, etc.). Generalized expression: in, For well depth d i The measured porosity during drilling, such as nuclear magnetic resonance porosity / compensated neutron porosity, or the estimated porosity based on adjacent wells / block modeling, is used; m is the porosity term index. Critical porosity; To obtain the maximum value; the entire The sub-item is the critical porosity determination item, which means that when the porosity is close to or greater than a certain critical value, the original solid mechanical state of close particle contact is completely transformed into fluid dominance. At this time, the energy consumption required for rock breaking will be rapidly reduced (or manifested as the mechanical specific energy rapidly decreasing to close to 0). For well depth d i Theoretical equivalent shear modulus at that point. x This is the exponent of the shear modulus term; To be with well depth d i Theoretical equivalent Poisson's ratio at the location Related functions to be determined.

[0053] Examining the Hertz-Mindlin contact model and the Bachrach-Avseth model, which considers contact shear attenuation, reveals differences in the expression of the shear modulus between the two models, as shown below: in, Porosity; and These are the normal and tangential stiffness of the contact surface, respectively. R The equivalent particle radius at the contact surface; n The particle contact coordination number; Compared with the examples The same definition applies; is the shear attenuation coefficient; in the above formula, the powder tangential stiffness... The defining formula is: in, This is the normal component of the contact force; and This represents the actual radius of the contacting particle; and These are the equivalent shear modulus and the equivalent Poisson's ratio, respectively.

[0054] After solving for the difference, we can obtain: in, The sign is proportional; this embodiment refers to the above. To align with the theoretical relationship and ensure consistency with the parameters of the theoretical model, the parameters in the relative shear coupling loss exponent are set to... , And C=1; therefore The final expression is as follows: Among them, only m and As a parameter to be determined, considering the decisive influence of porosity / microcracks on drillability and mechanical specific energy (high porosity usually greatly reduces mechanical specific energy and relative energy consumption), the porosity term index is typically used. In this embodiment m The value ranges from 2 to 6; Due to lithological influences, different values ​​may exist for different strata. The specific values ​​can be determined by inversion from adjacent actual curves, or by referring to relevant studies such as NUR A, MAVKO G, DVORKIN J, et al. Critical porosity: A key to relating physical properties toporosity in rocks[J]. The Leading Edge, 1998, 17(3): 357-362.DOI:10.1190 / 1.1437977. (For example, for sandstone layers, values ​​can be set as follows). wait).

[0055] Example 5: This embodiment of the invention uses Well X as an example to demonstrate how the invention obtains the coupled loss index during drilling by comprehensively measuring the PDC cuttings returned during drilling and compares it with the actual mechanical energy curve in engineering. Considering the good theoretical positive correlation between the loss index described in this invention and the mechanical energy in tight mudstone / shale layers, this embodiment selects the lithology transition section with a well depth range of 4286~4720m for measurement and calculation during drilling. Among them, the well depth range of 4286~4445m is a relatively high-porosity carbonaceous shale layer; the well depth range of 4445~4720m is a low-porosity tight shale layer and the formation where the target oil and gas formation is located; the mechanical energy within the layer is abnormally high, which is a characteristic difficult-to-drill formation of this well.

[0056] It should be noted that this embodiment is a comparative evaluation example combining drilling cuttings / engineering logging measurements with post-drilling logging (compensated neutron) and post-drilling curve calculations, used to demonstrate the similarity between the energy consumption curve obtained by this invention and the measured mechanical specific energy curve. This invention is not limited to the specific embodiment shown, and the method described in this invention is not limited to post-drilling evaluation or evaluation while drilling.

[0057] The specific steps in this embodiment include: (1) Obtain the mineral composition ratio at each well depth, construct a structural cloud based on XRD analysis, and obtain the equivalent modulus curve.

[0058] First, the method for calculating the equivalent framework modulus of multiphase minerals based on random structure clouds, disclosed in Chinese patent publication CN122392699A, is used. A structure cloud is constructed during drilling based on the XRD volume fraction results of PDC drill cuttings from well X. The equivalent shear modulus and equivalent Poisson's ratio are obtained through statistical averaging and used as the theoretical equivalent Poisson's ratio and theoretical equivalent shear modulus. To improve the overall well computational efficiency, simplified structure cloud construction parameters are used: , , , , In the multi-level structured cloud computing, based on geological experience in the area where Well X is located, "quartz, plagioclase, calcite, halite, sodium borosilicate, dolomite, montmorillonite, illite, illite-montmorillonite mixed layer, and analcime" are used as the diagenetic matrix framework minerals. After calculating the matrix equivalent structure cloud, "anhydrite, barite, and kaolinite" inclusion minerals are added for secondary mixing calculation to obtain the final equivalent modulus of the structure cloud. Amorphous substances and other solids or low-content minerals that cannot be identified by XRD are not included in the calculation. The composition, volume content, and reference grain modulus of the minerals constituting the Well X sample are shown in Table 1 below. Table 1. Main mineral components and reference grain framework modulus of Well X .

[0059] Table Note: Transparent minerals in the table are diagenetic matrix minerals, light blue minerals are secondary matrix minerals from the sedimentary process (also used as matrix minerals in the calculation), and gray minerals are cementing / inclusion minerals (non-matrix minerals).

[0060] The equivalent structural cloud skeleton modulus, skeleton Poisson ratio, and 99.7% confidence boundary obtained based on XRD calculations in this embodiment are shown in the attached figure. Figure 4 As shown, the attached Figure 4 Image a shows an example of the equivalent structural cloud skeleton bulk modulus-shear modulus distribution map (KG cloud map) of Well X at a depth of 4500m, calculated based on the mineral composition distribution measured by XRD. The HSW subscript indicates the conventional Hashin-Shtrikman-Walpole equivalent medium modulus boundary, with all "+" signs indicating the upper bound and "-" signs indicating the lower bound (the same applies below). Red crosses represent the statistical mean, and blue lines indicate the statistical ±99.7% confidence interval. (See attached image.) Figure 4 b is an example of a contour plot of the Poisson's ratio-Young's modulus (ν-E) of the skeleton at the same well depth. (Attached) Figure 4c shows the main mineral components measured by XRD in the overall target depth range in this embodiment (green dashed box) and the equivalent skeleton modulus curve calculated based on XRD (black solid box), where red is the statistical mean, green is the lower bound, and blue is the upper bound (the red curve data was used in subsequent calculations).

[0061] The effect of this step is that the XRD obtained from the pre-processed cuttings retrieved during drilling can be used to calculate the shear attenuation coefficient and estimate the well depth required for relative energy consumption. d i Theoretical equivalent Poisson's ratio at the location Wakabuka d i Theoretical equivalent shear modulus at the location By combining existing knowledge of minerals and mineralization processes in the block with the equivalent modulus calculation method based on structural cloud statistics described in the related patent, the required values ​​and whole-well curve results are more stable and consistent with actual geological understanding.

[0062] (2) Measure the wave velocity of the rock fragment remolded body and calculate the measured Poisson's ratio of the rock fragment remolded body.

[0063] This embodiment uses the method and apparatus for obtaining PDC drill bit environmental cuttings acoustic logging curves disclosed in Chinese patent application document No. 2025118660023 to measure the well depth. d i The thickness of the rock fragment remodeling body and the waveforms of the longitudinal (P-wave) and transverse (S-wave) waves were measured. For the longitudinal wave measurement, the equipment parameters used in this embodiment were consistent with those in Chinese patent application document No. 2025118660023 (main frequency of 5 MHz). For the transverse wave measurement, considering the high attenuation characteristics of the transverse wave and the thickness of the prepared sample, a transverse wave transducer with a main frequency of 1 MHz was used. For the measurement of the two waves, based on the acoustic transit time obtained from the deconvolution signal enhancement as described in Chinese patent application document No. 2025118660023, the acoustic transit time was also measured directly at the location of the extreme value, and the arithmetic mean was used to calculate the average acoustic transit time as the acoustic transit time of the remodeling body; the P-wave and S-wave transit times are shown in the attached figures. Figure 5 As shown in (c to d). The introduction of this arithmetic mean makes the P-wave and S-wave remodeling body measurement curves relatively more stable and less susceptible to travel time misreadings caused by the "period jump" phenomenon of wave phases. It should be noted that this embodiment only shows the average of the results based on two acoustic time difference acquisition methods. In practical applications, more acoustic time difference or wave velocity extraction techniques, as well as other averaging methods (such as geometric average), can be used to obtain stable results. Subsequently, the P-wave velocity, S-wave velocity, and remodeling body Poisson's ratio are calculated. The obtained X-well wave velocity and Poisson's ratio curves are shown in the appendix. Figure 5 As shown in (e to g), it should also be noted that the appendix... Figure 5 The solid black line represents the Poisson's ratio of the remodeled body used in subsequent calculations, calculated from the mean P-wave and mean S-wave values ​​of the remodeled body; the dashed gray line corresponds to the Poisson's ratio results calculated independently from the P / S wave curves measured through different methods.

[0064] The effect of this step is that, by utilizing the preparation and measurement of remolded material from drilling cuttings, the Poisson's ratio of the remolded material required for calculating the shear attenuation coefficient and estimating relative energy consumption can be obtained in real time during drilling. Furthermore, by referring to the technical content of the Chinese patent application document with application number 2025118660023, the reliability of the results for P, S waves, and Poisson's ratio was ensured as much as possible.

[0065] (3) Construct a relative energy consumption estimation / curve.

[0066] This embodiment can instantly obtain data at any well depth based on the cuttings returned during drilling. d i Data excluding porosity is required to calculate relative energy consumption. All parameters to be measured outside the area. Porosity prediction data can usually be obtained through three-dimensional porosity modeling based on seismic data of the block. In this embodiment, to more accurately compare with the actual engineering curve, compensated neutron logging (CNL) data obtained from conventional logging is directly used for calculation. Considering that compensated neutron logging data usually significantly overestimates porosity (especially in tight mudstone and shale layers), this embodiment uses critical porosity. (i.e., 35%) A simplified relative energy consumption estimation curve is constructed.

[0067] The actual engineering curve used for comparison in this embodiment is the mechanical specific energy (MSE) calculated with reference to the Teale formula, and its square root value (the square root value is often used in engineering as a post-evaluation reference parameter for drillability). The formula for calculating this mechanical specific energy MSE (expressed in MPa) is: in, (0.216 m) is the drill bit diameter; WOB Drilling pressure, unit: kN; RPM This refers to the drill string rotation speed, in r / min. TQ Torque, in kN·m; DT Drilling time is expressed in minutes per meter (min / m). The engineering input parameters for Well X (actual drilling pressure / rotation speed / torque / drilling time) are attached. Figure 6 The fifth and sixth channels from the left are shown in the middle; the calculated Teale mechanical energy MSE and its square root √MSE are shown in the appendix. Figure 6 The second from the right and the first from the right are shown by the red curves.

[0068] This embodiment calculates the shear attenuation coefficient curve based on XRD analysis of well X and acoustic wave measurements of the reshaped volume. The formation powder grain slip coefficient curve obtained by normalization calculation As attached Figure 6 As shown in the fourth and third tracks from the right. Substitute the values ​​into the compensated neutron logging curves respectively. Calculate the corresponding relative shear coupling loss index The resulting curve is shown in the attached figure. Figure 6 As shown in the second from the right and the first from the right, the black curve corresponds to... The loss index, corresponding to the gray curve and The loss index.

[0069] As can be seen from the comparison, in the low-porosity tight shale layer of Well X, except for the top cap layer at 4445 to 4472 m where there is a mismatch, at other depths, the relative shear coupling loss index proposed in this invention matches the actual mechanical specific energy and its square root curve with extremely high degree of agreement (see Appendix). Figure 6 (black dashed box), and relative shear coupling loss index and powder grain slip coefficient The specific energy exhibits several local extreme values ​​that coincide with those of actual engineering machinery (see appendix). Figure 6 The green dashed line demonstrates the effectiveness of the loss index described in this invention in assessing relative energy consumption.

[0070] In summary, this invention can be directly applied to scenarios involving combined evaluation of cuttings logging and drilling energy consumption while drilling. Under conditions of conventional cuttings return, fixed-interval sampling, XRD measurement, and remodeling acoustic testing, formation-end indices reflecting the degree of particle contact shear attenuation can be calculated based on cuttings mineral composition data and P-wave and S-wave data of the remodeled cuttings, further forming a relative energy consumption characterization quantity. This result can be compared with engineering data such as specific energy, drilling pressure, torque, rotational speed, and drilling speed in the field to identify abnormal energy consumption sections and relative changes in relatively dense layers caused by the formation of grinding layers, changes in particle contact state, and enhanced friction / slip. This provides supplementary evidence for interpreting the drilling process, identifying inefficient drilling, and adjusting parameters. Compared to monitoring methods based solely on engineering parameters, this invention adds formation-end information obtainable from cuttings samples, improving the physical interpretability of energy consumption changes.

[0071] In terms of extended applications, after accumulating cuttings XRD data, cuttings remodeling acoustic data, and corresponding well depth information from multiple wells in the same block, it is possible to further conduct adjacent well comparisons and stratigraphic statistical modeling scenarios to form templates for the distribution characteristics of contact shear weakening indicators and relative energy consumption trends in stratigraphic segments. Combining well logging curves, geological stratification results, and 3D geological models, these indicators can be introduced as formation-end constraint parameters into block-scale energy consumption trend analysis and 3D attribute modeling, providing prior references for pre-drilling scheme design for new wells. Furthermore, if combined with historical engineering parameters and drilling performance data, it can also be used for pre-quantitative optimization of drilling parameters, virtual well energy consumption trend prediction, and expansion of digital drilling model input, thereby supporting the application extension from "monitoring while drilling" to "pre-drilling prediction and planning."

[0072] Example 6: As shown in the appendix Figure 7 As shown in the figure, this invention discloses a method for calculating relative energy consumption in a PDC environment during drilling, including: The first calculation unit, in the selected well section of the target well, determines the shear attenuation coefficient of the formation after pulverization at each well depth based on the measured Poisson's ratio, theoretical equivalent Poisson's ratio, and theoretical equivalent shear modulus of the rock cuttings remodeled body at all drilling sampling points at corresponding well depths, and establishes the corresponding formation powder grain slip coefficient curve. The second calculation unit uses the formation powder grain slip coefficient curve and the theoretical equivalent Poisson's ratio and theoretical equivalent shear modulus at each well depth to determine the relative shear coupling loss index at each well depth. in, For well depth d i The relative shear coupling loss index at the location; For well depth d i The grain slip coefficient of the formation powder at that location; For well depth d i The theoretical equivalent Poisson's ratio at that location; For well depth d i Theoretical equivalent shear modulus at the point; For well depth d i The porosity can be measured by nuclear magnetic resonance (NMR) or compensated neutron porosity during drilling, or estimated porosity based on modeling of adjacent wells / blocks. Critical porosity; m It is the porosity index; To obtain the maximum value.

[0073] Example 7: Humidity of the present invention further optimized from the above embodiments, wherein the first calculation unit includes: The basic data acquisition module acquires the measured Poisson's ratio, theoretical equivalent Poisson's ratio, and theoretical equivalent shear modulus of the rock cuttings remodeled at the corresponding well depth for all drilling sampling points in the selected well section of the target well.

[0074] The shear attenuation coefficient calculation module determines the shear attenuation coefficient of the formation after pulverization at each well depth based on the measured Poisson's ratio and theoretical equivalent Poisson's ratio of the rock cuttings remodeled body at each well depth. in, For well depth d i The shear attenuation coefficient at that point; For well depth d i Measured Poisson's ratio of the reconstituted rock fragments at the location; Theoretically equivalent Poisson's ratio; The curve acquisition module uses the shear attenuation coefficient at each well depth to determine the corresponding formation powder grain slip coefficient, thus forming a formation powder grain slip coefficient curve. in, and These represent taking the maximum / minimum value respectively; For well depth d i The grain slip coefficient of the formation powder at that location.

[0075] Example 8: Humidity in an embodiment of the present invention. A further optimization of the above embodiments, wherein the basic data acquisition module includes: The equivalent skeleton modulus acquisition module obtains the theoretical equivalent Poisson's ratio and theoretical equivalent shear modulus at the corresponding well depths of the drilling sampling points, including: Obtain cuttings samples returned from the well depth corresponding to the drilling sampling point; After pretreatment, grinding and screening of the rock cuttings samples, powder samples from the depth of the well were obtained, and X-ray diffraction tests were performed on them to determine the mineral composition ratio at the depth of the well. Based on the mineral composition ratio at the depth of the well, the equivalent skeleton modulus of the multiphase mineral system at the depth of the well is calculated using the multiphase mineral equivalent skeleton modulus calculation method based on random structure cloud, and the corresponding theoretical equivalent Poisson's ratio and theoretical equivalent shear modulus are obtained. The acoustic logging curve acquisition module acquires the measured Poisson's ratio of the remodeled cuttings at the corresponding well depth at the drilling sampling point, including: Obtain cuttings samples returned from the well depth corresponding to the drilling sampling point; After pretreatment, grinding and screening of the rock cuttings samples, powder samples from the depth of the well were obtained. The powder sample from the depth of the well was made into a corresponding rock cuttings remodeling body. The PDC drill bit environmental rock cuttings acoustic logging curve acquisition method was used to obtain the P-wave transit time and S-wave transit time of the rock cuttings remodeling body at the depth of the well. Then, the measured Poisson's ratio of the rock cuttings remodeling body at the depth of the well was calculated. in, For well depth d i P-wave velocity of the remodeled rock debris at the location, ; For well depth d i Shear wave velocity of the remodeled rock debris at the location, ; For well depth d i P-wave time difference of the remodeled rock debris at the location; For well depth d i Shear wave time difference of the rock debris remodeling body at the location; For well depth d i Measured Poisson's ratio of the rock fragment remodeling at the location.

[0076] The above content is merely a specific embodiment of this application, which has strong adaptability and implementation effect. However, the protection scope of this application is not limited thereto. Any changes or substitutions that can be easily conceived by those skilled in the art within the technical scope disclosed in this application should be included within the protection scope of this application. Therefore, equivalent changes made in accordance with the claims of this application are still within the scope of this application.

Claims

1. A method for calculating relative energy consumption during drilling in a PDC environment, characterized in that, include: Obtain the measured Poisson's ratio, theoretical equivalent Poisson's ratio, and theoretical equivalent shear modulus of the rock cuttings remodeled at the corresponding well depths of all drilling sampling points in the selected well section of the target well. Based on the measured Poisson's ratio and theoretical equivalent Poisson's ratio of the rock cuttings remodeled bodies at each well depth, the shear attenuation coefficient after formation pulverization at each well depth was determined as follows: in, For well depth The shear attenuation coefficient at that point; For well depth Measured Poisson's ratio of the reconstituted rock fragments at the location; Theoretically equivalent Poisson's ratio; The formation powder grain slip coefficient was determined using the shear attenuation coefficient at each well depth, resulting in the corresponding formation powder grain slip coefficient curve, as shown below: in, and These represent taking the maximum / minimum value respectively; For well depth The grain slip coefficient of the formation powder at that location; For well depth The shear attenuation coefficient at that point; The relative shear coupling loss index at each well depth was determined by using the formation powder grain slip coefficient curve and the theoretical equivalent Poisson's ratio and theoretical equivalent shear modulus at each well depth. in, For well depth The relative shear coupling loss index at the location; For well depth The grain slip coefficient of the formation powder at that location; For well depth The theoretical equivalent Poisson's ratio at that location; For well depth Theoretical equivalent shear modulus at the point; For well depth The measured NMR porosity or compensated neutron porosity at the location during drilling, or the estimated porosity based on adjacent well / block modeling; Critical porosity; It is the porosity index; To obtain the maximum value.

2. The method for calculating relative energy consumption in a PDC environment while drilling according to claim 1, characterized in that, Obtain the theoretical equivalent Poisson's ratio and theoretical equivalent shear modulus at the corresponding well depths of the drilling sampling points, including: Obtain cuttings samples returned from the well depth corresponding to the drilling sampling point; After pretreatment, grinding and screening of the rock cuttings samples, powder samples from the depth of the well were obtained, and X-ray diffraction tests were performed on them to determine the mineral composition ratio at the depth of the well. Based on the mineral composition ratio at the depth of the well, the equivalent skeleton modulus of the multiphase mineral system at the depth of the well is calculated using the multiphase mineral equivalent skeleton modulus calculation method based on random structure cloud, and the corresponding theoretical equivalent Poisson's ratio and theoretical equivalent shear modulus are obtained.

3. The method for calculating relative energy consumption in a PDC environment while drilling according to claim 1 or 2, characterized in that, Obtain the measured Poisson's ratio of the remodeled cuttings at the corresponding well depths of the drilling sampling points, including: Obtain cuttings samples returned from the well depth corresponding to the drilling sampling point; After pretreatment, grinding and screening of the rock cuttings samples, powder samples from the depth of the well were obtained. The powder sample from the depth of the well was made into a corresponding rock cuttings remodeling body. The PDC drill bit environmental rock cuttings acoustic logging curve acquisition method was used to obtain the P-wave transit time and S-wave transit time of the rock cuttings remodeling body at the depth of the well. Then, the measured Poisson's ratio of the rock cuttings remodeling body at the depth of the well was calculated. in, For well depth P-wave velocity of the remodeled rock debris at the location, ; For well depth Shear wave velocity of the remodeled rock debris at the location, ; For well depth P-wave time difference of the remodeled rock debris at the location; For well depth Shear wave time difference of the rock debris remodeling body at the location; For well depth Measured Poisson's ratio of the rock fragment remodeling at the location.

4. A PDC environment relative energy consumption calculation device for drilling, applying the method described in any one of claims 1 to 3, characterized in that, include: The first calculation unit, in the selected well section of the target well, determines the shear attenuation coefficient of the formation after pulverization at each well depth based on the measured Poisson's ratio, theoretical equivalent Poisson's ratio, and theoretical equivalent shear modulus of the rock cuttings remodeled body at all drilling sampling points at corresponding well depths, and establishes the corresponding formation powder grain slip coefficient curve. The second calculation unit uses the formation powder grain slip coefficient curve and the theoretical equivalent Poisson's ratio and theoretical equivalent shear modulus at each well depth to determine the relative shear coupling loss index at each well depth. in, For well depth The relative shear coupling loss index at the location; For well depth The grain slip coefficient of the formation powder at that location; For well depth The theoretical equivalent Poisson's ratio at that location; For well depth Theoretical equivalent shear modulus at the point; For well depth The measured NMR porosity or compensated neutron porosity at the location during drilling, or the estimated porosity based on modeling of adjacent wells / blocks; Critical porosity; It is the porosity index; To obtain the maximum value.

5. The PDC environment relative energy consumption calculation device for drilling according to claim 4, characterized in that, The first computing unit includes: The basic data acquisition module acquires the measured Poisson's ratio, theoretical equivalent Poisson's ratio, and theoretical equivalent shear modulus of the rock cuttings remodeling body at the corresponding well depth for all drilling sampling points in the selected well section of the target well. The shear attenuation coefficient calculation module determines the shear attenuation coefficient of the formation after pulverization at each well depth based on the measured Poisson's ratio and theoretical equivalent Poisson's ratio of the rock cuttings remodeled body at each well depth. in, For well depth The shear attenuation coefficient at that point; For well depth Measured Poisson's ratio of the reconstituted rock fragments at the location; Theoretically equivalent Poisson's ratio; The curve acquisition module uses the shear attenuation coefficient at each well depth to determine the corresponding formation powder grain slip coefficient, thus forming a formation powder grain slip coefficient curve. in, and These represent taking the maximum / minimum value respectively; For well depth The grain slip coefficient of the formation powder at that location.

6. The PDC environmental relative energy consumption calculation device for drilling according to claim 5, characterized in that, The basic data acquisition module includes: The equivalent skeleton modulus acquisition module obtains the theoretical equivalent Poisson's ratio and theoretical equivalent shear modulus at the corresponding well depths of the drilling sampling points, including: Obtain cuttings samples returned from the well depth corresponding to the drilling sampling point; After pretreatment, grinding and screening of the rock cuttings samples, powder samples from the depth of the well were obtained, and X-ray diffraction tests were performed on them to determine the mineral composition ratio at the depth of the well. Based on the mineral composition ratio at the depth of the well, the equivalent skeleton modulus of the multiphase mineral system at the depth of the well is calculated using the multiphase mineral equivalent skeleton modulus calculation method based on random structure cloud, and the corresponding theoretical equivalent Poisson's ratio and theoretical equivalent shear modulus are obtained. The acoustic logging curve acquisition module acquires the measured Poisson's ratio of the remodeled cuttings at the corresponding well depth at the drilling sampling point, including: Obtain cuttings samples returned from the well depth corresponding to the drilling sampling point; After pretreatment, grinding and screening of the rock cuttings samples, powder samples from the depth of the well were obtained. The powder sample from the depth of the well was made into a corresponding rock cuttings remodeling body. The PDC drill bit environmental rock cuttings acoustic logging curve acquisition method was used to obtain the P-wave transit time and S-wave transit time of the rock cuttings remodeling body at the depth of the well. Then, the measured Poisson's ratio of the rock cuttings remodeling body at the depth of the well was calculated. in, For well depth P-wave velocity of the remodeled rock debris at the location, ; For well depth Shear wave velocity of the remodeled rock debris at the location, ; For well depth P-wave time difference of the remodeled rock debris at the location; For well depth Shear wave time difference of the rock debris remodeling body at the location; For well depth Measured Poisson's ratio of the rock fragment remodeling at the location.

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