CN-122014104-A - Drilling optimization decision-making method, device and equipment based on downhole parameter regulation and control

CN122014104ACN 122014104 ACN122014104 ACN 122014104ACN-122014104-A

Abstract

The embodiment of the specification relates to the technical field of drilling engineering, in particular to a drilling optimization decision method, device and equipment based on underground parameter regulation, wherein the method comprises the steps of obtaining drilling data, wherein the drilling data comprise underground engineering data and ground logging data, calculating drilling mechanical drilling speed, mechanical specific energy and complex working condition indexes according to the drilling data, wherein the complex working condition indexes are used for representing vibration levels and abrasion degrees of drill bits, constructing an optimization model by taking the maximum mechanical drilling speed and the minimum mechanical specific energy as targets and taking the complex working condition indexes as conditions for meeting risk working condition constraint, optimizing the underground engineering data according to the optimization model, wherein the underground engineering data at least comprise underground weight data and underground rotating speed data, and regulating and controlling underground engineering parameters according to the optimized underground engineering data. By acquiring and carrying out optimization decision according to underground engineering data, the problem of well ground transmission deviation caused by dependence on ground logging data is fundamentally solved.

Inventors

SONG XIANZHI
LI QIHAO
PAN TAO
ZHU ZHAOPENG
ZHANG CHENGKAI
WANG TIANYU
LI GENSHENG
HUANG ZHONGWEI
WANG BIN
ZHANG RUI

Assignees

中国石油大学(北京)

Dates

Publication Date: 20260512
Application Date: 20260302

Claims (10)

1. The well drilling optimization decision-making method based on downhole parameter regulation and control is characterized by comprising the following steps of: acquiring drilling data, wherein the drilling data comprises underground engineering data and ground logging data; according to the drilling data, calculating the mechanical drilling speed, the mechanical specific energy and the complex working condition index of the drilling, wherein the complex working condition index is used for representing the vibration level and the abrasion degree of the drill bit; Constructing an optimization model on the condition that the complex working condition index meets risk working condition constraint by taking the maximization of the mechanical drilling speed and the minimization of the mechanical specific energy as targets; Optimizing underground engineering data according to the optimization model, wherein the underground engineering data at least comprises underground weight-on-bit data and underground rotating speed data; And regulating and controlling the underground engineering parameters according to the optimized underground engineering data.
2. The method of claim 1, wherein the acquiring drilling data comprises: acquiring underground engineering data at the drill bit, wherein the underground engineering data at least further comprises underground torque data and inner and outer annulus pressure data; The method comprises the steps of acquiring ground logging data, wherein the ground logging data at least comprises ground weight-on-bit data, turntable rotating speed data, pump displacement data and hook load data; and carrying out space-time alignment on the underground engineering data and the ground logging data to obtain the drilling data.
3. The method of claim 1, wherein the calculating the rate of penetration of the well comprises: Determining drilling parameter data influencing the rock breaking efficiency of the drill bit according to the drilling data, wherein the rock breaking parameters influencing the rock breaking efficiency of the drill bit at least comprise underground drilling pressure, underground torque, underground rotating speed, internal and external annular pressure, pump displacement and hook load; And calculating the mechanical drilling speed of the well drilling by using a preset mechanical drilling speed prediction model according to the drilling parameter data influencing the rock breaking efficiency of the drill bit, wherein the mechanical drilling speed prediction model is used for representing the mapping relation between the drilling parameter influencing the rock breaking efficiency of the drill bit and the mechanical drilling speed.
4. The method of claim 1, wherein calculating the mechanical specific energy of the well comprises: Calculating a static rock breaking factor of the drill bit according to the size data of the drill bit, wherein the static rock breaking factor is inversely related to the size of the drill bit; Calculating a dynamic friction factor of the drill bit according to the underground weight-on-bit data, the underground torque data, the underground rotating speed data, the size data of the drill bit and the mechanical drilling speed data, wherein the dynamic friction factor is positively correlated with the underground torque and the underground rotating speed; and calculating the mechanical specific energy of drilling according to the underground weight data, the static rock breaking factor and the dynamic friction factor of the drill bit.
5. The method of claim 1, wherein calculating the complex operating index of the well comprises: Calculating the drilling resistance of the stratum according to the underground rotating speed data, the size data of the drill bit and the mechanical drilling speed data, wherein the drilling resistance is positively correlated with the size of the drill bit and the underground rotating speed; And calculating the complex working condition index of the well drilling according to the mechanical specific energy and the drilling resistance of the stratum.
6. The method of claim 1, wherein said subject to said complex operating index meeting a risk operating constraint comprises: the conditions that the pressure of the inner annulus and the outer annulus meets the overflow and lost circulation risk constraint, the complex working condition index meets the abrasion and vibration risk constraint, and the underground drilling pressure and the underground drilling speed meet the engineering risk constraint are adopted.
7. The method of claim 1, wherein the constructing an optimization model comprises: determining weight coefficients of the rate of penetration and mechanical specific energy based on drilling phase data; Based on the weight coefficients, a multi-objective optimization function is constructed with the objective of maximizing the rate of penetration and minimizing the mechanical specific energy.
8. The method of claim 7, wherein optimizing downhole engineering data according to the optimization model comprises: According to a preset intelligent optimization algorithm, solving the multi-objective optimization function to obtain a plurality of underground engineering parameter combinations of underground drilling pressure and underground rotating speed, wherein each underground engineering parameter combination corresponds to an optimization scheme of underground engineering data; Screening one or more candidate underground engineering parameter combinations meeting the risk working condition constraint from the plurality of underground engineering parameter combinations; sorting the one or more candidate underground engineering parameter combinations, and screening out an optimal underground engineering parameter combination; optimizing downhole engineering data according to the optimal downhole engineering parameter combination of the downhole weight on bit and the downhole rotating speed; Regulating and controlling the underground engineering parameters according to the optimized underground engineering data, wherein the method comprises the following steps: Generating an underground control instruction according to the optimized underground engineering data; And regulating and controlling underground engineering parameters according to the underground control instruction.
9. Drilling optimization decision-making device based on downhole parameter regulation and control, characterized by comprising: the acquisition module is used for acquiring drilling data, wherein the drilling data comprises underground engineering data and ground logging data; The calculation module is used for calculating the mechanical drilling speed, the mechanical specific energy and the complex working condition index of the drilling according to the drilling data, wherein the complex working condition index is used for representing the vibration level and the abrasion degree of the drill bit; The construction module is used for constructing an optimization model on the condition that the complex working condition index meets the risk working condition constraint with the aim of maximizing the mechanical drilling speed and minimizing the mechanical specific energy; The optimizing module is used for optimizing underground engineering data according to the optimizing model, wherein the underground engineering data at least comprises underground weight-on-bit data and underground rotating speed data; And the regulation and control module is used for regulating and controlling the underground engineering parameters according to the optimized underground engineering data.
10. A computer device, comprising: A memory for storing a computer program; A processor for executing the computer program to implement the method of any one of claims 1-8.

Description

Drilling optimization decision-making method, device and equipment based on downhole parameter regulation and control Technical Field The embodiment of the specification relates to the technical field of drilling engineering, in particular to a drilling optimization decision method, device and equipment based on downhole parameter regulation. Background Drilling engineering is an indispensable key link in oil and gas exploration and development, and the cost of the drilling engineering accounts for about 30-80% of the total cost of exploration and development. Currently, with the gradual shift of oil and gas exploration and development to deep, ultra-deep, deep water, unconventional and other complex oil and gas reservoirs, the fields become an important direction for the current and future oil and gas resource succession. However, the common occurrence condition of the resources is poor, the geological environment is complex, the underground working condition is severe, the efficiency, the safety and the quality of the drilling operation are all challenged, the cost and efficiency of the drilling operation are reduced, and a new method and a new technology with an revolutionary significance are urgently needed to be developed. Along with the wide application of wells with complex structures such as ultra-deep wells, large displacement wells and the like, underground stratum lithology is frequent alternately, the control difficulty of a well track is high, the friction resistance and the torque of a drill string are obviously increased, so that the bit pressure applied on the ground is difficult to be effectively transmitted to the bottom of a well, and the method has become a key bottleneck for restricting the acceleration and the efficiency of deep and unconventional oil and gas drilling. Too low weight on bit will result in insufficient rock breaking efficiency, while too high weight on bit or too high fluctuation will easily cause abnormal wear of drill bit and severe vibration of drill string, and even induce downhole failure such as stuck drill bit in severe cases. Therefore, the method realizes accurate characterization and accurate regulation of downhole drilling parameters, and is an important foundation for improving drilling efficiency and guaranteeing safety. At present, the well drilling parameter optimization method mainly comprises two types, namely a traditional optimization method based on statistics or rock breaking mechanism, wherein an optimal parameter combination is screened by establishing experience or theoretical relations between mechanical drilling speeds and well drilling parameters in different stratum or well sections, and a well drilling parameter optimization method based on an intelligent algorithm, a nonlinear mapping between ground logging parameters and rock breaking efficiency indexes (such as mechanical drilling speeds) is established through a data driving model, and the well drilling parameters are recommended by inversion of the optimization algorithm. Although the method system is continuously evolved, the mainstream scheme in the industry generally takes the ground logging parameters (such as ground weight on bit, rotating disc rotating speed, pump discharge capacity and the like) as an optimization core, and a parameter optimization strategy is formulated by analyzing the association between the ground logging parameters and drilling performance indexes. However, the prior method has obvious technical limitations that the ground parameters are required to be transmitted to an underground action area through a drill string, drilling fluid and other mediums, and are interfered by complex factors such as drill string deformation, hydraulic loss, high-temperature and high-pressure environment, lithology mutation and the like in the process, so that obvious deviation exists between the ground parameters and actual action parameters at the bottom of a well. The optimization mode taking the ground parameters as the core is essentially indirect deduction of underground real working conditions, the ground parameters such as ground weight on bit, torque and the like are difficult to effectively transfer to the bottom of the well, the underground real working conditions and the actual rock breaking requirements are difficult to be matched accurately, the optimization strategy is easy to be disjointed from the underground real state and the actual requirements, the drilling speed increasing effect is limited, risks such as instability of a well wall and sticking of a drill bit are possibly aggravated due to parameter mismatch, and the improvement of the overall drilling performance is restricted. Disclosure of Invention The embodiment of the specification aims to provide a drilling optimization decision method, device and equipment based on downhole parameter regulation and control, so as to solve the problem that in the existing method, the underground real working condition