Method and system for producing quenched and tempered steels for oilfield applications

Abstract

The invention relates to a method for producing quenched and tempered steels for oilfield applications having specified material properties, which are ensured by a target alloy, wherein at least one primary-metallurgical unit produces a first melt, wherein at least one analysis of the contents of the elements is carried out on the first melt, wherein at least one actual value of the melt analysis is directed to a control system, wherein a distinction is made between influencing elements and compensation elements, wherein influencing elements are elements which have an influence on at least one material property of an end product, and compensation elements are elements which have an influence on the at least one material property and compensate for the influence of the influencing elements, wherein the magnitude of the influence of the at least one actual value of the respective influencing and compensation elements on the at least one material property of the end product is known, wherein the at least one actual value is detected with respect to the influencing and compensation elements that have an influence on the at least one material property of the end product, wherein, for the at least one material property of the end product, at least one compensation element is determined that establishes the at least one material property, wherein one or more compensation elements are alloyed into the melt in an amount that brings the at least one material property into a target range and compensates for the influence of one or more influencing elements on the at least one material property, and wherein two components are used in the control system for this purpose: a prediction model and a correction model, wherein the prediction model calculates the influence of the influencing and compensation elements on the at least one material property of the end product and the correction model calculated corrected target values of the compensation elements, in order to bring the at least one material property into a target range, and a control system for carrying out the method and a metal hollow body, in particular a seamless steel pipe for oilfield applications.

Description

[0001] International patent application

[0002] Voestalpine Tubulars Gmbh & Co KG; Voestalpine Stahl Donawitz GmbH

[0003] 240917WO

[0004] Process and system for the production of heat-treatable steels for oilfield applications

[0005] The invention relates to a method for producing heat-treatable steels for oilfield applications, a system for producing heat-treatable steels and a metallic hollow body, in particular a seamless steel tube for oilfield applications.

[0006] Worldwide, 71.1% of steel (in 2023) is produced via the blast furnace route. Pig iron is obtained from iron ore by melting it in a blast furnace together with reducing agents such as coke and additives. The molten pig iron is then further processed into crude steel in a converter process (e.g., with oxygen) or in an electric arc furnace (using scrap as raw material).

[0007] Primary metallurgical units used in the production of crude steel include: BF (blast furnace), RE-Ent-S (hot metal desulfurization), BOF (basic oxygen furnace), EAF (electric arc furnace), SAF (submerged arc furnace), IF (induction furnace), smelter, MOE (metal oxide electrolysis), plasma reduction metallurgy, etc. The crude steel is then further processed in secondary metallurgy to improve its composition and purity.Here, the steel is treated in secondary metallurgical units such as rinse stations, purging stations, ladle furnaces, RH plants (Ruhrstahl-Heraeus process), VD plants (vacuum degassing), DETEM plants, VOD plants (vacuum oxygen degassing), ASEA-SKF (oxygen vacuum treatment with stirring), CAS plants (composition adjustment by sealed argon bubbling), RS-V plants (Rheinstahl-Siemens vacuum), CAS-OB plants (composition adjustment by sealed argon bubbling - oxygen blowing), calcium-silicon treatment (CaSi injection), magnesium treatment (magnesium injection), VLD processes (vacuum ladle degassing), etc., where additives (metallic and non-metallic feedstocks) such as alloying elements and slag formers are added to achieve the desired chemical composition. and to achieve specific properties of the steel.

[0008] Scrap metal is not normally used in blast furnaces, as the process is primarily based on the reduction of iron ore to produce liquid pig iron. However, scrap metal is used in international patent applications.

[0009] Voestalpine Tubulars Gmbh & Co KG; Voestalpine Stahl Donawitz GmbH

[0010] 240917WO

[0011] It is used in other process steps of steel production, especially in electric arc furnaces or as a coolant in converters.

[0012] The pig iron produced in primary metallurgical units is then further processed in an oxygen converter. In these converters, such as the LD converter (Linz-Donawitz process), liquid pig iron is decarburized by injecting oxygen and converted into crude steel. Scrap metal is added as a coolant, along with other feedstocks. The addition of scrap metal in the converter process helps to control the temperature, as the exothermic nature of the oxygen reactions heats the molten metal considerably.

[0013] Another important production method in the steel industry is the electric arc furnace (EAF). Here, up to 100% scrap metal can be used as feedstock, which is melted using electrical energy to produce liquid steel. This process is particularly environmentally friendly, as the more energy-intensive reduction process is usually unnecessary, resulting in lower CO2 emissions than the blast furnace process.

[0014] In the electric arc furnace process, steel is produced using electrical energy. An electric arc is generated between graphite electrodes and the scrap material in the furnace, creating high temperatures (up to 3,500 °C in the arc zone) that melt the scrap and process it into liquid crude steel.

[0015] Raw steel production utilizes raw materials such as scrap metal. A distinction is made between metallic and non-metallic raw materials. These include, for example, iron ore, reducing agents, slag formers, sponge iron in the form of directly reduced iron (DRI) or hot briquetted iron (HBI), deoxidizing agents, alloying agents, and scrap metal.

[0016] Using scrap metal as a raw material for steel offers several advantages. Melting scrap metal requires only the energy needed for heating or melting, and because the energy-intensive reduction process usually involves upstream processes, it requires less energy than the primary production of crude steel from iron ore. Furthermore, scrap recycling reduces CO₂ emissions and the need for new raw materials, thus lowering the environmental impact. Since steel can be recycled again and again, using scrap metal makes a significant contribution to the circular economy in the steel industry.

[0017] Although the use of scrap metal in electric arc furnaces (EAF) offers many advantages, there are also some disadvantages and challenges that must be considered. International patent application

[0018] Voestalpine Tubulars Gmbh & Co KG; Voestalpine Stahl Donawitz GmbH

[0019] 240917WO

[0020] The first challenge when using scrap is its fluctuating quality. Scrap used in EAF (Electronically Advanced Fabrication) is often inhomogeneous and can contain impurities that negatively affect steel quality. For example, unwanted elements such as copper, molybdenum, tin, nickel, and chromium may be present in the scrap. These are difficult to remove from the raw steel and can have negative effects on downstream secondary metallurgy and the properties of the final product for certain applications. Impurities can make the EAF process more complex and expensive, as additional processing or sorting steps may be required.

[0021] The second major challenge concerns controlling the chemical alloy composition. Because scrap can have different alloys and metal compositions, it can be difficult to precisely control the chemical composition of the final product. Adding alloying elements in the EAF (Electron Alloy Forming) therefore becomes more complicated, and additional adjustments are often necessary to achieve the desired steel specification.

[0022] Due to potential impurities and the fluctuating quality of scrap, it is difficult to guarantee the particularly low levels (< 0.005 wt%) of elements such as copper, tin, and zinc required for certain specialized applications using the EAF process. In such cases, the use of primary materials (e.g., pig iron, liquid pig iron, hot metal, sponge iron, DRI, HBI) or very high-quality, sorted scrap is necessary, which increases costs.

[0023] In addition to the chemical composition, which is subject to fluctuations due to the input material in an electric arc furnace process and is therefore often kept within predetermined tolerance limits, the effects of individual elements on the properties of the final product must also be taken into account.

[0024] In particular, during subsequent heat treatment or forming processes, such as rolling, the material properties of the steel are further controlled.

[0025] Several solutions are already known that take into account the undesirable accompanying elements in the alloy composition or provide for additional adjustments to the alloying elements. International patent application

[0026] Voestalpine Tubulars Gmbh & Co KG; Voestalpine Stahl Donawitz GmbH

[0027] 240917WO

[0028] It is common practice to define fixed target ranges for a steel grade, specifying the minimum and maximum values ​​for each alloying element. For trace elements that are not intentionally alloyed but are present in the raw materials in unknown concentrations, maximum concentrations exist to help maintain the material properties within the desired range if these concentrations are not exceeded. However, the actual concentration of these trace elements in the liquid phase is not taken into account.

[0029] A disadvantage of this is that low maximum levels of accompanying elements necessitate the use of raw materials with low levels of these elements. This is primarily achieved through a high proportion of raw materials produced from primary sources.

[0030] From EP 3 956 481 Bl, a computer-aided method for monitoring the steelmaking process in a converter is known. In this method, various materials with specific properties are introduced into the converter to produce liquid crude steel and slag. The method first defines the desired properties of the liquid crude steel and slag to be produced. Then, the required quantities of each material that must be introduced into the converter to achieve the defined target characteristics of the crude steel and slag are calculated. The calculated material quantities are transmitted to the operator or to automatic loading systems, and the converter is loaded accordingly.

[0031] This section describes the loading of the converter with various feedstocks. A disadvantage is that only the composition of the melt produced in the converter is controlled. Subsequent manipulation of the alloy composition is not specified.

[0032] German patent application DE 10 2021 211 320 discloses a method for controlling and regulating a production plant for rolled products made of metallic alloys such as steel, iron, or aluminum. The aim of the method is to optimize the use of raw materials and reduce production costs. Initially, specific target values ​​for the material, surface, and geometric properties of the final product, as well as permissible chemical compositions with defined tolerance ranges, are established for each order. By applying process models, predictive actual values ​​of the product properties are calculated for each order and compared with the target values. Only compositions that lie within the specified tolerances are selected. For each selected chemical composition, cost parameters such as alloy composition, feedstock costs, and other factors are calculated. (International patent application)

[0033] Voestalpine Tubulars Gmbh & Co KG; Voestalpine Stahl Donawitz GmbH

[0034] 240917WO

[0035] Energy, iron, aggregate, and CO2 costs are determined. These are quantified in the form of penalty points or a penalty function. Subsequently, the intersection of permissible chemical compositions is determined for various combinations of production orders to be melted in a single batch.

[0036] The disadvantage of this approach is that tolerance ranges are determined for each composition. Precise control of the composition is not possible with this model.

[0037] From EP 4 183 498 A1, an AI-based predictive model is known that can predict mechanical properties from previously measured input values, such as the composition of the melt. To influence the mechanical properties, an adjustment of the manufacturing parameters, such as pre-roll ratio, finish-roll ratio, rolling start temperature, cooling start time, cooling rate, or line speed, is proposed as output.

[0038] The model is optimized for specific production lines and processes. If production conditions or requirements need to change quickly, the system may have difficulty adapting.

[0039] US Patent 5,462,613 A discloses a method for producing steel bars with a predefined tensile strength. An empirical model is used to first predict the tensile strength based on a sample analysis of the molten steel. The same model is then used to calculate a "moving setpoint" for one or more control elements, such as carbon, required to achieve the target tensile strength. The melt is then "trimmed" by adding these elements before being rolled into bars.

[0040] A method for controlling the composition of reinforcing steel, with the primary goal of reducing alloy costs, is disclosed in CN 115 874 012 A. After an initial adjustment of the carbon content, a predictive model is used to calculate the yield strength of the melt based on its current chemical composition. The alloy offering the best cost-effectiveness is then identified to compensate for the difference between the predicted and target yield strength. Only the precise amount of this most cost-efficient alloy required is added to avoid material waste and unnecessary strength excesses. (International patent application)

[0041] Voestalpine Tubulars Gmbh & Co KG; Voestalpine Stahl Donawitz GmbH

[0042] 240917WO

[0043] CN 103 194 683 A discloses a material for seamless steel pipes containing a small proportion of rare earth elements, intended for high-toughness oilfield pipe couplings, and its manufacture. The manufacturing process involves low-temperature refining, in which the chemical composition is adjusted based on the analysis of the converter steel. A final heat treatment by quenching and tempering ensures the desired high toughness.

[0044] Quenched and tempered steel is steel produced by quenching and tempering, i.e., hardening followed by tempering, and exhibits high tensile and fatigue strength. The hardness of quenched and tempered steel is determined by the material (chemical composition) and the process parameters during hardening (selected hardening temperature and quenching rate). The transformation hardening process allows for targeted control of the strength-to-toughness ratio.

[0045] Heat-treated steel is used in the manufacture of crankshafts, shafts, axles, bolts, screws and other high-strength structural components, such as seamless steel pipes for use in the oil and gas industry.

[0046] The heat-treatable steels for seamless steel pipes used in the oil and gas industry are based on the following standards:

[0047] • API Specification 5CT: “Casing and tubing” (German: Gehäuse und Rohre)

[0048] • API Specification 5L: “Line pipe” (German: Rohrleitung)

[0049] • EN ISO 11960: “Oil and gas industry - Steel pipes for use as casing or riser pipes for drilling”

[0050] Heat-treatable steels in strength classes up to and including 80 ksi (kilopounds per square inch), corresponding to 552 MPa, are produced as naturally hardened or normalized tubes. Strength classes above 80 ksi are achieved through a specific heat treatment process (hardening, water quenching, and tempering). In addition to process parameters such as temperature and time, the chemical composition of the steel is crucial for the formation of the microstructure and thus the strength.

[0051] The corrosion resistance of the material is also an essential product property in the application. For this specific application, resistance to sour gas (H₂S) is particularly important. (International patent application for heat-treatable steels for oilfield applications)

[0052] Voestalpine Tubulars Gmbh & Co KG; Voestalpine Stahl Donawitz GmbH

[0053] 240917WO

[0054] The required corrosion resistance, in turn, depends on a balanced and coordinated alloy composition and a homogeneous microstructure.

[0055] The main alloying elements in such heat-treatable steels are carbon, manganese, silicon, molybdenum, and chromium. In addition, the presence of accompanying elements such as sulfur, phosphorus, and copper must be appropriately limited.

[0056] The material properties, particularly the mechanical properties, of heat-treatable steels can be controlled by the targeted addition of alloying elements. However, the exact alloy composition is difficult to control in the EAF process due to the accompanying elements introduced by the input materials, such as scrap. Nevertheless, methods must be found within the EAF process to achieve the target specifications for the respective heat-treatable steels with regard to their material properties, especially their mechanical properties.

[0057] The object of the invention is to provide a method for the production of heat-treatable steels for oilfield applications, which enables targeted control of the material properties, in particular mechanical properties, even with larger fluctuations in the accompanying elements.

[0058] The problem is solved by a method having the features of claim 1.

[0059] Advantageous further training options are indicated in the sub-requirements.

[0060] Furthermore, the object of the invention is to provide a system for the production of heat-treatable steels which enables targeted control of the material properties, in particular mechanical properties, even with larger fluctuations in the accompanying elements.

[0061] This problem is solved with a control system having the features of claim 15.

[0062] Advantageous further training options are indicated in the sub-requirements.

[0063] Furthermore, it is also an object of the invention to provide a metallic hollow body, in particular a seamless steel tube for oilfield applications made of a heat-treated steel.

[0064] This problem is solved with a metallic hollow body having the features of claim 20. International patent application

[0065] Voestalpine Tubulars Gmbh & Co KG; Voestalpine Stahl Donawitz GmbH

[0066] 240917WO

[0067] This is a concept according to the invention for dynamic alloying. In this process, the element boundaries for alloying elements are adapted in the liquid phase.

[0068] An analysis of the melt determines the actual values ​​of the element contents. These actual values ​​are fed into a data-driven predictive model suitable for a specified heat-treatable steel. This allows the influence of the respective elements on a material-related, particularly mechanical, property to be modeled. If necessary, a correction model is used to identify a response in the form of adapted alloying element limits to bring the material-related, particularly mechanical, property into a desired target range. These adapted alloying element limits are then fed into the alloy calculator as adapted target values. The alloy calculator uses these adapted alloying element limits to determine the masses of raw materials.

[0069] The inventors recognized that a distinction should be made between two defined types of elements when dynamically correcting element levels: influencing elements and compensation elements.

[0070] Various raw materials are used in the steelmaking process. These include iron ore, sponge iron in the form of directly reduced iron (DRI) or hot briquetted iron (HBI), and scrap metal. These raw materials naturally introduce not only iron but also so-called accompanying elements and trace elements.

[0071] Trace elements are usually unavoidable elements, such as Si, Mn, S, P, O, N, and H, and are removed during a subsequent metallurgical process, if possible. If removal is not possible, the respective trace element and its influence on metallurgical processes must be taken into account.

[0072] For each type of steel, which is defined by the chemical composition of the alloy and the manufacturing route, there exists a defined class of accompanying elements resulting from practical experience; that is, certain upper limits for the levels of accompanying elements must be observed.

[0073] Trace elements are explicitly disruptive accompanying elements (e.g., As and Sb) that are present in very small quantities. These are not taken into account during the (dynamic) alloying process carried out here. International patent application

[0074] Voestalpine Tubulars Gmbh & Co KG; Voestalpine Stahl Donawitz GmbH

[0075] 240917WO

[0076] Alloying elements are elements that are deliberately added to give steel desired material properties. These properties can include mechanical properties such as hardness, tensile strength, toughness, and others, as well as chemical properties such as resistance to corrosion or hydrogen embrittlement, and others.

[0077] When using raw materials, especially metallic and non-metallic raw materials, it must be taken into account that they contain accompanying elements from their raw material history and alloying elements from their metallurgical history.

[0078] If, for example, scrap metal is used as a raw material in steel production, its components, apart from iron, are accompanying and trace elements for the product that is to be produced using the scrap metal.

[0079] Their presence must therefore be taken into account, since they (as former alloying elements) can only be removed from the product via metallurgical processes with great difficulty or not at all. However, their effect can be considered and compensated for according to the invention.

[0080] In the classic manufacturing process, the starting point is a product (steel) that possesses specific material properties according to market requirements. It is then chemically / metallurgically adjusted to meet these requirements. Such a product is therefore an alloy, where the alloying elements are defined by a specific content with upper or lower limits. Thus, the properties of a given alloy are known.

[0081] If, due to changed conditions, the use of raw materials such as scrap metal is significantly increased, the product will consequently be loaded with a higher quantity of accompanying elements. These accompanying elements (as "former" alloying elements) have an influence, for example, on the material properties of the product.

[0082] Therefore, this must be taken into account when adding alloys. The following scenarios can occur.

[0083] A) For example, the proportion of element A introduced by the starting material is below the desired level. In this case, less element A may need to be added. International patent application

[0084] Voestalpine Tubulars Gmbh & Co KG; Voestalpine Stahl Donawitz GmbH

[0085] 240917WO

[0086] B) For element A, a content is introduced via the starting material that is already within the target range; nothing further needs to be added.

[0087] C) More element A than desired is introduced. The content of element A can only be reduced metallurgically with increased effort. Accordingly, the effect of element A must be compensated for.

[0088] The above example becomes more complex when several accompanying elements or alloying elements interact to produce specific properties.

[0089] The invention addresses this by selecting alloying elements to complement the accompanying elements that have an influence on a material-related, in particular mechanical, property of the heat-treatable steel (hereinafter referred to as influencing elements), which can compensate for the influence of the influencing element on the material-related, in particular mechanical, property (hereinafter referred to as compensation elements).

[0090] Compensation elements are elements that are at best already regular alloying elements of the target alloy, so that only quantitative adjustments are made within the framework of the desired qualitative alloy composition.

[0091] A simple example will illustrate this. If, in addition to iron, a desired steel alloy contains elements A, B, and C, and element A is present in an amount exceeding the desired quantity, and C is an element that reduces the influence of A on a specific material-related, particularly mechanical, property, then C is added in an amount that, in addition to its own effect, also compensates for the effect of A.

[0092] Another example is when element A is present in the raw materials in an amount exceeding the desired quantity. If element C has a comparable influence on the material properties, particularly mechanical properties, as A, but is present in the alloy in small amounts or only in traces, only enough of it is added so that the combined effect of A and C results in the material properties, particularly mechanical properties, specified by the desired grade of heat-treated steel. In this case, that means less C is added than would normally be added to compensate for the excessively high A content. International patent application

[0093] Voestalpine Tubulars Gmbh & Co KG; Voestalpine Stahl Donawitz GmbH

[0094] 240917WO

[0095] Compensation in the sense of the invention therefore means that an adjustment of the target alloy composition can take place upwards or downwards.

[0096] In this case, B is, for example, an element that has no influence on the material properties, especially the mechanical properties.

[0097] Overall, this inventive procedure allows for a coarser pre-selection of the input material.

[0098] Input parameters for the forecasting model are all elements that are contained in the liquid phase and have been analyzed.

[0099] The starting parameters are adapted element limits for elements that are alloyed in the liquid phase. These are the so-called compensation elements, such as C, Si, Mn, and Cr. Compensation elements are therefore elements that are added in the liquid phase to counteract the influence of the other elements, so that the desired properties of the final alloy are achieved.

[0100] Both the influencing and the compensating elements are elements that are introduced into the melt by adding raw materials.

[0101] These are trace elements that inevitably occur in iron or steel and may be present in small quantities. They can originate from the raw materials used, such as ore or scrap, or be introduced into the melt during processing. These trace elements influence the properties of the steel and, depending on their concentration, can have positive or negative effects on selected material properties, particularly mechanical ones.

[0102] In steel production, "scrap" refers to recycled, reusable metallic secondary material used as a feedstock for the production of new steel. Scrap consists primarily of iron-based alloys and is classified into various grades and varieties depending on its purity, shape, size, and chemical composition.

[0103] The present process, which uses feedstocks, relates to the production of heat-treatable steels for oilfield applications with material properties, particularly mechanical properties, specified for a heat-treatable steel grade. International patent application

[0104] Voestalpine Tubulars Gmbh & Co KG; Voestalpine Stahl Donawitz GmbH

[0105] 240917WO

[0106] The concept is based on producing a final product of a specific heat-treatable steel grade in which a material-related, particularly mechanical, property remains unchanged or changes only minimally despite increased levels of influencing elements introduced by the raw materials in metallurgical units. This is in comparison to the material-related, particularly mechanical, property that results when raw materials with low levels of influencing elements are used in the melt production, thus introducing lower levels of undesirable accompanying elements (e.g., primary route). This ensures that the product falls within a target range specified by the heat-treatable steel grade with regard to its material-related, particularly mechanical, properties. This also ensures that subsequent post-treatment steps following steel production do not need to be modified.

[0107] This is achieved by adapting one or more alloying elements and is subsequently referred to as dynamic alloying. The adaptation is carried out by applying a predictive model, which initially models the expected material properties, particularly mechanical properties, based on actual values ​​from the analysis. Should these properties lie outside the target range specified by the desired grade of heat-treated steel, corrected alloying element contents are calculated using a correction model so that the specified requirements for the material properties, particularly mechanical properties, can be met.

[0108] For heat-treatable steels, relevant mechanical properties include, for example, tensile strength (TS), yield strength (YS), toughness, yield strength, and corrosion resistance. The inventive method is specifically designed to allow control of tensile strength and yield strength. Furthermore, hardenability indices, such as the carbon equivalent (CAE), are also important parameters and are intended to be taken into account by the inventive method.

[0109] Various machine learning models can be used to generate the forecast and / or correction model, for example, linear regression models, polynomial regression models, decision tree-based regression models, random forest regression models, nearest neighbor models, neural network models, support vector machine models, ADA boost models, regression boost models, HIST boost models, XGBOOST models, generalized additive models, and symbolic regression models. International patent application

[0110] Voestalpine Tubulars Gmbh & Co KG; Voestalpine Stahl Donawitz GmbH

[0111] 240917WO

[0112] These models are data-driven. Database-driven queries, for example, can be used as the data basis for chemical and mechanical values. Process parameters, particularly heat treatment temperature and holding times, can also be derived from corresponding database-driven queries. Furthermore, datasets can be augmented with simulation data to represent the influence of higher pollutant loads. The data basis is divided into training and validation data; for example, 80% of the data is used for training purposes and 20% for validation purposes.

[0113] To improve the accuracy of the models, additional important process parameters besides the chemical composition, such as the temperature profile of the rolling and cooling processes, could be considered. Furthermore, it is useful to identify the most relevant parameters and, where applicable, negligible parameters with regard to a specific material-related, particularly mechanical, property.

[0114] Purely data-driven models are well-suited for prediction within the data space defined by the training data. However, prediction accuracy may deteriorate if there is a significant deviation from this known data space, i.e., if a significantly different alloy composition is incorporated into the calculation of the material properties, particularly mechanical properties, using the prediction and / or correction model. Furthermore, small training datasets may suffer from high variance, which can impair prediction accuracy. This effect can be minimized by using larger training datasets.

[0115] To identify the model with the highest accuracy for modeling the material properties, particularly mechanical properties, the actual values ​​determined by melt analysis are fed into potential models (see the list above). The most accurate predictive and / or correction model, characterized by the smallest deviation / value of the root mean square error (RMSE), is then used to model the material properties, particularly mechanical properties. When considering multiple material properties, particularly mechanical properties, the mean value and / or the sum of the square roots of the RMSE of these properties is used. International patent application

[0116] Voestalpine Tubulars Gmbh & Co KG; Voestalpine Stahl Donawitz GmbH

[0117] 240917WO

[0118] The tensile strength TS and the yield strength YS can be calculated in a prediction and / or correction model based on multiple linear regression analysis according to the following formulas:

[0119] T

[0120]

[0121] S = a0+ x X r + ax X2+ — I- a n x X n ;

[0122] TS = ßo + ßi x Yi + ß2x X2+ — I- ß n x X n ,

[0123] where

[0124] ao and ßo basic factors of tensile strength TS and yield strength YS,

[0125] ai- a n and ßi- ßn regression coefficients and

[0126] Xi-Xn element contents in wt.% are given.

[0127] The calculated values ​​for the material properties, especially mechanical properties, are compared with their respective target values ​​to assess the necessity of dynamic alloying, which is only necessary if the material property, especially mechanical property, lies outside a defined target range.

[0128] In addition to material properties, particularly mechanical ones, so-called hardenability indices, which represent a measure of the steel's hardenability, are important. A variety of known parameters can be used as hardenability indices. For example, but not exclusively, hardenability indices as described in the following standards or patents are possible: DIN EN 10025-2, EN 1011-2, ASTM A255 DE69607702T2, EP2692890, EP2695960B1, EP2589676B1, EP3561130B1, EP2726637B2, EP2562272B1, DE102015221387A1, EP2258880B1, EP2514844B1. Such parameters can also be found, for example, in the publications “Hardness Prediction in Quenched and Tempered Nodullar Cast Iron Using the Hollomon-Jaffe Parameter” (Guillanon et al., Metals 2021, 11(2), 297) and “A historical overview of steel tempering parameters” (Totten et al., Int. J. Microstructure and Materials Properties, Vol. 3, Nos. 4 / 5, 2008).

[0129] The carbon equivalent is frequently used as a hardenability index. Essentially, the carbon equivalent is a measure of a steel's weldability and serves to prevent hardening cracks and to estimate the need for preheating. Furthermore, the carbon equivalent is suitable for assessing the influence of elements on hardenability and workability during the tempering process. [The international patent application]

[0130] Voestalpine Tubulars Gmbh & Co KG; Voestalpine Stahl Donawitz GmbH

[0131] 240917WO

[0132] Carbon equivalent can be used as a descriptive measure for the total carbon content of a steel alloy.

[0133] Basically, there are a large number of definitions of carbon equivalents in the prior art, all of which can readily be applied in the modeling according to the invention.

[0134] The calculation of the carbon equivalent depends on the specific alloy and / or the underlying standards and / or specifications. The following formulas, for example, but not exclusively, are used in the prediction model:

[0135] wt.% Mn wt.% Cr + wt.% Mo + wt.% V CEV (Carbon Equivalent Value) = wt. — %C +

[0136]

[0137] 6 5

[0138] wt.%Ni + wt.%Cu_

[0139] 15

[0140] wt.-%Mn+wt.-%Mo wt.-%Cr+wt.-%Cu GET (Carbon Equivalent Thyssen) = wt. - %C

[0141]

[0142] 10 20

[0143] wt% Ni

[0144] 40

[0145] wt.% Si wt.% Mn + wt.% Cu + wt.% Cr Pcm (Critical Metal Parameter) = wt. — %C +

[0146]

[0147] 30 20

[0148] wt.%Mo, wt.%Ni, wt.%V, r > >

[0149] - 1 - 1 - I- 5 X Weight — %B

[0150] 15 60 10

[0151] where wt.%i is the content of the respective element i in wt.%.

[0152] Modeling the material properties, particularly mechanical properties, reveals whether dynamic alloying is necessary to bring the property within a specified target range. If the material properties, particularly mechanical properties, fall within the target range, no compensation of the influencing elements by selected compensating elements takes place. However, if the material properties, particularly mechanical properties, deviate from the intended target range, the correction model calculates adapted element contents of the target alloy. Accordingly, at least one compensating element is added to bring the material properties, particularly mechanical properties, into the target range.

[0153] After the addition of compensating elements, a further analysis can be performed. The actual value of the alloy composition is checked and, if necessary, dynamically corrected again using the correction model. International patent application

[0154] Voestalpine Tubulars Gmbh & Co KG; Voestalpine Stahl Donawitz GmbH

[0155] 240917WO

[0156] The elements Cu, Mo, and Ni are considered influencing elements. C, Si, Mn, and / or Cr are generally chosen as compensating elements.

[0157] Exceptions to this include certain alloy steels, such as the following: For Ni-alloyed heat-treatable steels, only Cu and Mo are considered influencing elements; for Mo-alloyed heat-treatable steels, only Cu and Ni; and for Ni-Mo-alloyed heat-treatable steels, only Cu. In these cases, the aforementioned alloying elements are also suitable as compensating elements.

[0158] The influence of the individual elements on the material properties of the alloy is as follows.

[0159] Copper is added to conventional steels as an alloying element only in extremely small quantities due to the risk of ductility loss and intergranular surface cracking. Copper also negatively impacts cold formability, hot formability, and impact toughness, and reduces weldability. Excessively high copper content can lead to undesirable red brittleness, which occurs during hot forming due to the formation of a copper melt caused by selective corrosion and can lead to cracks or fractures even under minimal stress. Red brittleness can be counteracted, for example, by adding nickel. On the other hand, copper can increase yield strength, tensile strength, and hardenability. Through precipitation hardening, copper effectively contributes to increased strength. In weathering steels, adding copper can improve weather and corrosion resistance.

[0160] It is advantageous if a copper content of 0.001 to 0.5 wt.%, preferably 0.001 to 0.45 wt.%, particularly preferably 0.001 to 0.42 wt.%, and further particularly preferably 0.001 to 0.4 wt.% is selected.

[0161] Steel melts produced via the EAF route, in particular, often exhibit excessively high copper content due to the increased scrap input. Removing copper from the melt is extremely difficult, so its effect must be compensated for by other alloying elements.

[0162] Nickel increases through-hardening and tempering by reducing the critical cooling rate. It also increases the toughness, hardness, and strength of steel, as well as the solubility of copper in steel, thus counteracting undesirable red brittleness. Nickel can also improve the corrosion resistance of steel. (International patent application)

[0163] Voestalpine Tubulars Gmbh & Co KG; Voestalpine Stahl Donawitz GmbH

[0164] 240917WO

[0165] They can be improved. However, the high costs incurred when using nickel as an alloying element are a disadvantage.

[0166] It is advantageous if a nickel content of 0.001 to 4.0 wt.%, preferably 0.001 to 3.8 wt.%, particularly preferably 0.001 to 3.5 wt.%, and further particularly preferably 0.001 to 3.0 wt.% is selected.

[0167] Molybdenum interacts strongly with phosphorus, thus limiting its damaging effects in steel (segregation at the former austenite grain boundaries). Through its pronounced carbide-forming behavior, molybdenum increases the strength of steel while reducing its ductility. Molybdenum carbides also increase wear resistance and tempering resistance and can act as hydrogen traps, thereby improving resistance to delayed fracture. Furthermore, the weldability of steel decreases with increasing molybdenum content.

[0168] It is advantageous if a molybdenum content of 0.001 to 1.5 wt.%, preferably 0.001 to 1.45 wt.%, particularly preferably 0.001 to 1.4 wt.%, and further particularly preferably 0.001 to 1.35 wt.% is selected.

[0169] Tin has a work-hardening and hardening effect, but simultaneously reduces elongation at break and tends to cause greater segregation, thus affecting structural stability. Furthermore, tin is surface-active and impairs hot formability.

[0170] It is advantageous if a tin content of 0.001 to 0.03 wt.%, preferably 0.001 to 0.028 wt.%, particularly preferably 0.001 to 0.026 wt.%, and further particularly preferably 0.001 to 0.025 wt.% is selected.

[0171] As a carbide former with various elements (e.g., cementite, FeS-C), carbon increases the hardness, strength, and yield strength of steel. Low carbon contents ensure good formability and weldability but do not result in high strength. High carbon contents increase strength but also carry the risk of embrittlement and thus cracking. One of the most important properties of carbon as an alloying element is its ability to harden malleable steel through quenching. International patent application

[0172] Voestalpine Tubulars Gmbh & Co KG; Voestalpine Stahl Donawitz GmbH

[0173] 240917WO

[0174] It is advantageous if a carbon content of 0.05 to 1.2 wt.%, preferably 0.05 to 1.1 wt.%, particularly preferably 0.05 to 1.05 wt.%, and further particularly preferably 0.05 to 1.0 wt.% is selected.

[0175] Silicon has a beneficial effect on the ductility and strength of steel. It also improves scale resistance, thus reducing the risk of red brittleness. Due to its high affinity for oxygen, it is an important deoxidizing agent. High silicon contents lead to work hardening of the microstructure through solid solution formation. However, excessively high contents can have a detrimental effect, for example, on cold formability. Silicon increases the yield strength and tensile strength without significantly reducing elongation. Furthermore, the element lowers the critical cooling rate, thereby increasing hardening. Silicon also increases scale resistance and has a significant influence on the electrical properties of steel.

[0176] It is advantageous if a silicon content of 0.001 to 1.9 wt.%, preferably 0.001 to 1.85 wt.%, particularly preferably 0.001 to 1.8 wt.%, and further particularly preferably 0.001 to 1.75 wt.% is selected.

[0177] At low concentrations, manganese has a beneficial effect on segregation behavior in continuous casting and improves formability. Manganese also has a positive effect on hardenability and through-hardening. Higher manganese concentrations result in higher intrinsic strength but also increase the risk of hydrogen embrittlement because manganese accelerates the segregation of phosphorus and sulfur at the former austenite grain boundaries. Manganese is an effective deoxidizing agent and a strong austenite stabilizer. It can also help prevent red brittleness.

[0178] It is advantageous if a manganese content of 0.1 to 3.5 wt.%, preferably 0.1 to 3.4 wt.%, particularly preferably 0.1 to 3.2 wt.%, and further particularly preferably 0.1 to 3.0 wt.% is selected.

[0179] Chromium increases tensile strength while only slightly reducing elongation. By lowering the bainitic start temperature of the steel, chromium leads to a refinement of the bainitic structure. Additionally, it increases hardness and resistance to hydrogen fracture through carbide formation. Higher chromium contents also improve hot strength and tempering resistance. However, chromium has a negative impact on weldability. International patent application

[0180] Voestalpine Tubulars Gmbh & Co KG; Voestalpine Stahl Donawitz GmbH

[0181] 240917WO

[0182] It is advantageous if a chromium content of 0.001 to 15 wt.%, preferably 0.001 to 14.8 wt.%, particularly preferably 0.001 to 14.6 wt.%, and further particularly preferably 0.001 to 14.5 wt.% is selected.

[0183] Vanadium has a hardening effect, thus enabling bainitic tempering at higher temperatures. Excessively high vanadium contents lead to precipitates that impair the steel's resistance to delayed hydrogen fracture.

[0184] It is advantageous if a vanadium content of 0.001 to 0.4 wt.%, preferably 0.001 to 0.40 wt.%, particularly preferably 0.001 to 0.38 wt.%, and further particularly preferably 0.001 to 0.34 wt.% is selected.

[0185] Aluminum is an important deoxidizing agent, especially in steels with low manganese and silicon contents. The formation of aluminum nitrides can control austenitic grain coarsening during hot rolling. However, excessively high aluminum contents lead to the coarsening of aluminate-like inclusions in the steel, which can be particularly detrimental to its toughness.

[0186] It is advantageous if an aluminium content of 0.0005 to 0.1 wt.%, preferably 0.0005 to 0.095 wt.%, particularly preferably 0.0005 to 0.092 wt.%, and further particularly preferably 0.0005 to 0.09 wt.% is selected.

[0187] Boron improves hardenability and reduces the risk of red brittleness in copper-alloyed steels. Through segregation at the former austenitic grain boundaries, boron also increases resistance to hydrogen fracture. Boron acts synergistically with molybdenum and niobium, thus enhancing the effectiveness of these elements. However, higher boron contents should be avoided, as these lead to the formation of brittle iron-boron carbides.

[0188] It is advantageous to select a boron content of 0.0005 to 0.01 wt.%, preferably 0.0005 to 0.009 wt.%, particularly preferably 0.0005 to 0.008 wt.%, and further particularly preferably 0.0005 to 0.007 wt.%.

[0189] Titanium can bind unwanted nitrogen and contributes to precipitation hardening. It also increases delayed fracture toughness. A disadvantage associated with higher titanium contents is the binding of dissolved boron in the form of titanium borides, which form even at high temperatures. International patent application

[0190] Voestalpine Tubulars Gmbh & Co KG; Voestalpine Stahl Donawitz GmbH

[0191] 240917WO

[0192] It is advantageous to select a titanium content of 0.001 to 0.08 wt.%, preferably 0.001 to 0.075 wt.%, particularly preferably 0.001 to 0.072 wt.%, and more preferably 0.001 to 0.07 wt.%.

[0193] Niobium increases hydrogen resistance and promotes a good distribution of harmful elements such as phosphorus and sulfur in steel. However, high niobium contents lead to significant precipitation, which impairs the steel's resistance to latent fracture. Furthermore, excessive niobium content increases the risk of surface cracking defects on billets and ingots during continuous casting. These defects can negatively affect fatigue strength and hydrogen resistance.

[0194] It is advantageous to select a niobium content of 0.001 to 0.1 wt.%, preferably 0.001 to 0.095 wt.%, particularly preferably 0.001 to 0.092 wt.%, and more preferably 0.001 to 0.09 wt.%.

[0195] In small quantities, nitrogen can help prevent excessive coarsening of the austenite grains during steel heat treatment. Furthermore, the formation of carbonitrides allows for the inclusion of hydrogen. As an austenite former, nitrogen can partially substitute nickel and carbon. In boron-alloyed steels, nitrogen binds boron through the formation of boron nitrides, thus negating boron's beneficial effect on the steel's hardenability. Therefore, the nitrogen content in boron-alloyed steels is limited to 0.01 wt.%.

[0196] It is advantageous if a nitrogen content of 0.0001 to 0.05 wt.%, preferably 0.0001 to 0.045 wt.%, particularly preferably 0.0001 to 0.042 wt.%, and further particularly preferably 0.0001 to 0.04 wt.% is selected.

[0197] The effects of phosphorus and sulfur are particularly detrimental in heat-treatable steels, as these elements inhibit hydrogen recombination, leading to a higher concentration of atomic hydrogen in the material and increasing the risk of delayed fracture. Furthermore, phosphorus and sulfur cause segregation at grain boundaries (risk of grain boundary cracking) and increase the risk of hot cracking. Therefore, phosphorus and sulfur content must be kept very low.

[0198] It should be noted that the harmful effects of influencing elements are particularly critical in combination with one another, and their origin lies in corresponding input material contamination (in the input mix used to create the melt). International patent application

[0199] Voestalpine Tubulars Gmbh & Co KG; Voestalpine Stahl Donawitz GmbH

[0200] 240917WO

[0201] When using melting technologies with increased amounts of secondary raw materials, greater fluctuations in material properties, especially mechanical properties, can occur due to the inevitably increased load of influencing elements.

[0202] The invention thus relates to a method for producing heat-treatable steels for oilfield applications with specified material properties, which are ensured by a target alloy, wherein at least one primary metallurgical unit leads to a first melt, wherein at least one analysis of the elemental content is carried out from the first melt, wherein at least one actual value of the melt analysis is transmitted to a control system, wherein a distinction is made between influencing and compensating elements, wherein influencing elements are elements that have an influence on at least one material property of an end product, and compensating elements are elements that have an influence on the at least one material property and compensate for the influence of the influencing elements.wherein the magnitude of the influence of at least one actual value of the respective influencing and compensating elements on at least one material property of the final product is known, wherein the at least one actual value is recorded with respect to those influencing and compensating elements which have an influence on at least one material property of the final product, wherein at least one compensating element is determined for at least one material property of the final product which adjusts the at least one material property, wherein one or more compensating elements are added to the melt in an amount which brings the at least one material property into a target range and compensates for the influence of one or more influencing elements on the at least one material property,and where two components are used in the control system for this purpose: a forecasting model and a correction model, wherein the forecasting model calculates the influence of the influencing and compensating elements on the at least one material property of the final product and the correction model calculates corrected target values ​​of the compensating elements in order to bring the at least one material property into a target range.

[0203] The quantity of added compensating elements can also be zero in accordance with the invention if this is deemed necessary to compensate for the effect or influence of the influencing elements. International patent application

[0204] Voestalpine Tubulars Gmbh & Co KG; Voestalpine Stahl Donawitz GmbH

[0205] 240917WO

[0206] Further training stipulates that the material properties include Hollomon-Jaffe parameters, hardenability indices, one or more carbon equivalents, yield strength YS and tensile strength TS.

[0207] Further training stipulates that the analysis is carried out by means of sampling according to EN ISO 14284.

[0208] Further training stipulates that the subsequent post-treatment steps following steel production are carried out unchanged until the final product is obtained.

[0209] Further training stipulates that the predictive model and / or correction model is generated using one, several, or all of the following models: linear regression models, polynomial regression models, decision tree-based regression models, random forest regression models, nearest neighbor models, neural network models, support vector machine models, ADA boost models, regression boost models, HIST boost models, XGBOOST models, generalized additive models, and symbolic regression models.

[0210] Further training stipulates that the forecasting model and / or correction model is generated using linear regression models, polynomial regression models, decision tree-based regression models, random forest regression models, nearest neighbor models, neural network models, support vector machine models, ADA boost models, regression boost models, HIST boost models, XGBOOST models, generalized additive models and / or symbolic regression models.

[0211] Further training stipulates that, when a material property is considered, at least one recorded actual value of the analysis is assigned to at least one prediction model and / or correction model using the square root of the mean square deviation of the material property, whereby the square root of the mean square deviation of the material property is determined for all prediction models and / or correction models for the at least one actual value, and the prediction model and / or correction model with the highest accuracy is selected based on the results.

[0212] Further training stipulates that, when several material properties are considered, at least one recorded actual value of the analysis should be used to calculate the mean and / or the sum of the square roots of the mean square deviations of the International Patent Application.

[0213] Voestalpine Tubulars Gmbh & Co KG; Voestalpine Stahl Donawitz GmbH

[0214] 240917WO

[0215] material properties are assigned to at least one prediction model and / or correction model, whereby for the at least one actual value the mean value and / or the sum of the square roots of the mean square deviations of the material properties for all prediction models and / or correction models is determined and based on the results that the prediction model and / or correction model with the highest accuracy is chosen.

[0216] Further training stipulates that the forecasting model and / or correction model is generated using multiple linear regression analysis.

[0217] Further training stipulates that the tensile strength TS and the yield strength YS are calculated in a forecast and / or correction model based on multiple linear regression analysis according to the following formulas:

[0218] T

[0219]

[0220] S = a0+ x X r + ax X2+ — I- a n x X n ;

[0221] TS = ßo + ßi x Yi + ß2x X2+ — I- ß n x X n ,

[0222] where

[0223] ao and ßo basic factors of tensile strength TS and yield strength YS,

[0224] ai- an and ßi- ßn regression coefficients and

[0225] Xi-Xn element contents in wt.% are given.

[0226] Further training stipulates that the influencing elements, whose influence on the material properties of the final product is to be compensated, include one, several or all from the group of Ni, Mo, Cu.

[0227] Further training stipulates that the influencing elements, whose influence on the material properties of the final product is to be compensated, include Ni, Mo and / or Cu.

[0228] Further development stipulates that in Ni-alloyed heat-treatable steels, Mo and Cu are influencing elements; in Mo-alloyed heat-treatable steels, Ni and Cu are influencing elements; and in Ni-Mo-alloyed heat-treatable steels, Cu is influencing elements, whereby in these cases the aforementioned alloying elements are also suitable as compensating elements. International patent application

[0229] Voestalpine Tubulars Gmbh & Co KG; Voestalpine Stahl Donawitz GmbH

[0230] 240917WO

[0231] Further training stipulates that one, several or all of the elements from the group of C, Si, Mn, Cr are selected as compensatory elements.

[0232] Further training stipulates that C, Si, Mn and / or Cr are selected as compensatory elements.

[0233] Further training stipulates that at least one of the following formulas is used to calculate the carbon equivalent depending on standards and / or specifications of a specific grade of heat-treated steel:

[0234] wt.% Mn wt.% Cr + wt.% Mo + wt.% V CEV (Carbon Equivalent Value) = wt. — %C +

[0235]

[0236] 6 5

[0237] wt.%Ni + wt.%Cu_

[0238] 15

[0239] wt.-%Mn+wt.-%Mo wt.-%Cr+wt.-%Cu CET (Carbon Equivalent Thyssen) = wt.-%C

[0240]

[0241] io 20

[0242] wt% Ni

[0243] 40

[0244] wt.% Si wt.% Mn + wt.% Cu + wt.% Cr Pcm (Critical Metal Parameter) = wt. — %C +

[0245]

[0246] 30 20

[0247] wt.%Mo, wt.%Ni, wt.%V, r > >

[0248] - 1 - 1 - I- 5 X Weight — %B

[0249] 15 60 10

[0250] where wt.%i is the content of the respective element i in wt.%.

[0251] Further training stipulates that the analysis is carried out at least in the first melt of the last primary metallurgical aggregate of a production route, in particular from a tapping of crude steel, before or after a first addition of alloying elements and at least after a second addition of alloying elements.

[0252] A further development provides that if a first element is introduced by a precursor in a proportion below a desired target range defined by the target alloy, the first element, provided it is a desired alloying element, is added to the extent necessary to reach the target range; or, if the first element is introduced by a precursor in a proportion already within the target range, the first element is no longer added; or, if the first element is introduced by a precursor in a proportion above the target range, the first element is compensated for by a reduced alloying proportion of a second, similarly acting element or an increased alloying proportion of an opposing third element. International patent application

[0253] Voestalpine Tubulars Gmbh & Co KG; Voestalpine Stahl Donawitz GmbH

[0254] 240917WO

[0255] Further training stipulates that the correction model used establishes a ranking of the different compensation elements according to resolution- and output-specific as well as economic considerations.

[0256] The term "dissolution" refers to the dissolution of the raw materials in the melt. In this context, this means that, in case of doubt, an element is unlikely to be considered as a compensating element if its dissolution in the melt takes too long and would, in particular, delay the entire process.

[0257] The term "output" refers to yield.

[0258] Further training stipulates that the target alloy must comprise the following target alloy composition in wt.%:

[0259] C 0.05-1.2

[0260] Si 0.001-1.9

[0261] Mn 0.1-3.5

[0262] in addition, iron and unavoidable impurities,

[0263] where optionally one, several or all of the following elements are included in wt.%:

[0264] P < 0.1

[0265] S <0.35

[0266] Cr 0.001-15

[0267] Cu 0.001-0.5

[0268] Mon 0.001-1.5

[0269] Ni 0.001^.0

[0270] N 0.0001-0.05

[0271] Sn 0.001-0.03

[0272] V 0.001-0.4

[0273] Nb 0.001-0.1

[0274] Ti 0.001-0.08

[0275] AI 0.0005-0.1

[0276] B 0.0005-0.01. International patent application

[0277] Voestalpine Tubulars Gmbh & Co KG; Voestalpine Stahl Donawitz GmbH

[0278] 240917WO

[0279] Further training stipulates that the target alloy must comprise the following target alloy composition in wt.%:

[0280] C 0.05-1.2

[0281] Si 0.001-1.9

[0282] Mn 0.1-3.5

[0283] in addition, iron and unavoidable impurities,

[0284] the following elements are optionally included in wt.%:

[0285] P < 0.1

[0286] S <0.35

[0287] Cr 0.001-15

[0288] Cu 0.001-0.5

[0289] Mon 0.001-1.5

[0290] Ni 0.001^.0

[0291] N 0.0001-0.05

[0292] Sn 0.001-0.03

[0293] V 0.001-0.4

[0294] Nb 0.001-0.1

[0295] Ti 0.001-0.08

[0296] AI 0.0005-0.1 and / or

[0297] B 0.0005-0.01.

[0298] The invention further relates to a control system for the production of heat-treatable steels for oilfield applications with specified material properties, which are ensured by a target alloy, and for carrying out the method according to the invention, wherein the control system comprises two components: a prediction model and a correction model, wherein the prediction model is designed to calculate an effect of influencing elements and compensation elements on at least one material property of the heat-treatable steel, and the correction model is designed to calculate corrected target values ​​of compensation elements in order to bring the at least one material property into a target range.

[0299] Further training stipulates that the forecasting model and / or correction model can be generated using one, several, or all of the following models: linear international patent application

[0300] Voestalpine Tubulars Gmbh & Co KG; Voestalpine Stahl Donawitz GmbH

[0301] 240917WO

[0302] Regressionsmodelle, polynomiale Regressionsmodelle, Decision-Tree-Based Regressionsmodelle, Random-Forest-Regressionsmodelle, Nearest-Neighbour-Modelle, Neuronal-Network-Modelle, Support-Vector-Machine-Modelle, ADA-Boost-Modelle, Regression-Boost-Modelle, HIST-Boost-Modelle, XGBOOST-Modelle, Generalized-Additive- Modelle, Symbolic-Regression-Model le.

[0303] Further training stipulates that the forecasting model and / or correction model can be generated using linear regression models, polynomial regression models, decision tree-based regression models, random forest regression models, nearest neighbor models, neural network models, support vector machine models, ADA boost models, regression boost models, HIST boost models, XGBOOST models, generalized additive models and / or symbolic regression models.

[0304] Further training stipulates that the material properties tensile strength TS and yield strength YS can be calculated in a prediction and / or correction model based on multiple linear regression analysis according to the following formulas:

[0305] TS = a0+ x X r + ax X2+ — I- a n x X n ;

[0306]

[0307] ys = ß0+ xx } + ß2x x2+ — i- ß n xxn ,

[0308] where

[0309] ao and ßo basic factors of tensile strength TS and yield strength YS,

[0310] ai- an and ßi- ßn regression coefficients and

[0311] Xi-Xn element contents in wt.% are given.

[0312] Further training stipulates that at least one of the following formulas can be used to calculate a carbon equivalent depending on standards and / or specifications of a specific grade of heat-treated steel:

[0313] wt.% Mn wt.% Cr + wt.% Mo + wt.% V CEV (Carbon Equivalent Value) = wt. — %C +

[0314]

[0315] 6 5

[0316] wt.%Ni + wt.%Cu_

[0317] 15

[0318] wt.-%Mn+wt.-%Mo wt.-%Cr+wt.-%Cu GET (Carbon Equivalent Thyssen) = wt. - %C +

[0319]

[0320] 10 20

[0321] wt%Ni,

[0322] 40 'International patent application'

[0323] Voestalpine Tubulars Gmbh & Co KG; Voestalpine Stahl Donawitz GmbH

[0324] 240917WO

[0325] wt.% Si wt.% Mn + wt.% Cu + wt.% Cr Pcm (Critical Metal Parameter) = wt. — %C +

[0326] 30 20

[0327] wt.%Mo, wt.%Ni, wt.%V, r > >

[0328] - 1 - 1 - I- 5 X Weight —%B,

[0329]

[0330] i E an in '

[0331] where wt.%i is the content of the respective element i in wt.%.

[0332] Further training stipulates that the target alloy must comprise the following target alloy composition in wt.%:

[0333] 0.05-1.2

[0334] 0.001-1.9

[0335] 0.1-3.5

[0336] in addition, iron and unavoidable impurities,

[0337] where optionally one, several or all of the following elements are included in wt.%:

[0338] P < 0.1

[0339] S <0.35

[0340] Cr 0.001-15

[0341] Cu 0.001-0.5

[0342] Mon 0.001-1.5

[0343] Ni 0.001^.0

[0344] N 0.0001-0.05

[0345] Sn 0.001-0.03

[0346] V 0.001-0.4

[0347] Nb 0.001-0.1

[0348] Ti 0.001-0.08

[0349] AI 0.0005-0.1

[0350] B 0.0005-0.01.

[0351] Further training stipulates that the target alloy must comprise the following target alloy composition in wt.%:

[0352] C 0.05-1.2

[0353] Si 0.001-1.9

[0354] Mn 0.1-3.5 International patent application

[0355] Voestalpine Tubulars Gmbh & Co KG; Voestalpine Stahl Donawitz GmbH

[0356] 240917WO

[0357] in addition, iron and unavoidable impurities,

[0358] the following elements are optionally included in wt.%:

[0359] P < 0.1

[0360] S <0.35

[0361] Cr 0.001-15

[0362] Cu 0.001-0.5

[0363] Mon 0.001-1.5

[0364] Ni 0.001^.0

[0365] N 0.0001-0.05

[0366] Sn 0.001-0.03

[0367] V 0.001-0.4

[0368] Nb 0.001-0.1

[0369] Ti 0.001-0.08

[0370] AI 0.0005-0.1 and / or

[0371] B 0.0005-0.01.

[0372] The invention further relates to a metallic hollow body, in particular a seamless steel tube for oilfield applications made of a heat-treated steel, produced according to the inventive method.

[0373] The invention is illustrated by way of example with a drawing. The drawing shows:

[0374] Figure 1 shows the process flow of dynamic alloying;

[0375] Figure 2 shows exemplary lower limits or minimum contents (Min), standard deviations (SD), average values ​​(Avg.) and upper limits or maximum contents (Max) for yield strength, tensile strength, influencing and compensation elements;

[0376] Figure 3 shows exemplary tensile strength and yield strength values ​​as well as element contents within the framework of the dynamic alloying according to the invention, showing the compensation of the effects of the influencing elements by adapting the compensation element contents;

[0377] Figure 4 PCA (Principal Component Analysis) for estimating the influence of the individual elements for example L80-1 (API 5-CT); International patent application

[0378] Voestalpine Tubulars Gmbh & Co KG; Voestalpine Stahl Donawitz GmbH

[0379] 240917WO

[0380] Figure 5 Example L80-1 - Application of regression to training data: predicted YS values ​​(YS-prog.) vs. observed or measured YS values ​​(YS-beob.);

[0381] Figure 6 Example L80-1 - Application of regression to the population:

[0382] predicted YS values ​​(YS - prog.) vs. observed or measured YS values ​​(YS - beob.);

[0383] Figure 7 Example L80-1 - Application of regression to training data: predicted TS values ​​(TS - prog.) vs. observed or measured TS values ​​(TS - beob.);

[0384] Figure 8 Example L80-1 - Application of regression to the population:

[0385] predicted TS values ​​(TS - prog.) vs. observed or measured TS values ​​(TS - beob.);

[0386] Figure 9 Example L80-1 - Comparison between forecast and observation or measurement;

[0387] Figure 10 PCA (Principal Component Analysis) for estimating the influence of the individual elements for the example PI 10 (API 5-CT);

[0388] Figure 11 Example P110 - Application of regression to training data: predicted YS values ​​(YS - prog.) vs. observed or measured YS values ​​(YS - beob.);

[0389] Figure 12 Example PI 10 - Application of regression to the population:

[0390] predicted YS values ​​(YS - prog.) vs. observed or measured YS values ​​(YS - beob.);

[0391] Figure 13 Example P110 - Application of regression to training data: predicted TS values ​​(TS - prog.) vs. observed or measured TS values ​​(TS - beob.);

[0392] Figure 14 Example PI 10 - Application of regression to the population:

[0393] predicted TS values ​​(TS - prog.) vs. observed or measured TS values ​​(TS - beob.);

[0394] Figure 15 Example P110 - Comparison between forecast and observation or measurement.

[0395] The inventors recognized that it is particularly advantageous to distinguish between influencing and compensating elements. International patent application

[0396] Voestalpine Tubulars Gmbh & Co KG; Voestalpine Stahl Donawitz GmbH

[0397] 240917WO

[0398] The effect or influence of the influencing elements is compensated by adding compensating elements.

[0399] The effect or influence of the elements already present in the melt on the material properties, particularly the mechanical properties, of the heat-treated steel product is modeled using a predictive model. Any necessary correction is determined using a correction model.

[0400] Figure 1 illustrates the inventive method in a simplified manner. Based on a melt analysis, a decision is made as to whether the analysis lies within the specified limits for the influencing element content or deviates from them. If the influencing element content lies within the limits, the standard process is carried out, i.e., no dynamic alloying occurs. However, if the influencing element content lies outside the specified limits, the influence on at least one specified material property, in particular a mechanical property, is determined using the predictive model in order to ascertain whether the predicted property lies within or outside the target range defined by the desired quenched and tempered steel grade. If the property lies within the specified target range, the standard process is carried out, i.e., no dynamic alloying occurs.If the predicted property lies outside the specified target range, however, adapted alloying element contents are calculated using the correction model. By adding appropriate compensating elements, the effect of the influencing elements can be offset to bring the property within the specified target range. The standard process is then resumed. After dynamic alloying, actual values ​​from the analysis can be fed back into the predictive model if necessary. If the predicted property is within the specified target range, the standard process is then followed. If the predicted property is still outside the specified target range, dynamic alloying can be performed again.

[0401] Figure 2 shows exemplary lower limits or minimum contents (Min), standard deviations (SD), average values ​​(Avg.) and upper limits or maximum contents (Max) for yield strength, tensile strength, influencing and compensating elements.

[0402] The influencing elements include Ni, Mo, and Cu. The compensating elements are C, Si, Mn, and Cr. International patent application

[0403] Voestalpine Tubulars Gmbh & Co KG; Voestalpine Stahl Donawitz GmbH

[0404] 240917WO

[0405] Figure 3 shows tensile strength and yield strength values ​​as well as element contents for six exemplary cases of the dynamic alloying process according to the invention. To compensate for the influence of the variable influencing element contents, adapted compensation element contents are calculated using the correction model. With regard to the observed or measured TS and YS values, it becomes apparent that, due to the compensation of the effect of the influencing elements by adapting the compensation element contents, these values ​​can be maintained within the respective target range despite the variable influencing element contents.

[0406] The sufficient accuracy of the models used in the process according to the invention will below be illustrated by means of two specific examples, two different heat-treatable steel alloys.

[0407] Example 1: L80-1 (API 5-CT)

[0408] Figure 4 shows the result of the PCA (Principal Component Analysis). This verifies whether and how significantly a variable influences the result.

[0409] Formulas for the yield strength YS and tensile strength TS are determined through multiple linear regression analysis:

[0410] YS = 644 - 102 x wt -%C - 174 x wt -%Mn + 540 x wt -%Cr + 330 x wt -%Ni + 915 x wt -%Mo - 495 x wt -%Cu + 146 x wt -%S7;

[0411] TS = 543 + 955 x wt. —%C — 123 x wt. —%Mn + 112 x wt. —%Cr + 185 x wt. —%Ni + 1448 x wt. —%Mo + 324 x wt. —%Cu + 158 x wt. —%Si.

[0412] Figures 5 to 8 show plots of the predicted values ​​(prog.) against the observed or measured values ​​(beob.) of YS and TS, with Figures 5 and 7 relating to the training data and Figures 6 and 8 to the population. The regression line, in the context of multiple linear regression, is a line that describes the relationship between several independent variables and a dependent variable. This line minimizes the sum of the squared distances (residuals) between the actual data points and the predicted values. Multiple linear regression extends the concept of simple linear regression by considering multiple predictors to enable more accurate predictions. The circles represent the predicted values. The closer a circle is to the regression line, the better the prediction. [95% International Patent Application]

[0413] Voestalpine Tubulars Gmbh & Co KG; Voestalpine Stahl Donawitz GmbH

[0414] 240917WO

[0415] Confidence bands (dashed lines) of a prediction probability indicate the range within which 95% of future data points are expected to lie. These bands account for the uncertainty in the estimates of the regression parameters and provide a visual representation of the accuracy of the predictions. They are wider than simple confidence intervals because they consider the uncertainty across the entire range of the independent variables.

[0416] Overall, given the good comparability of the observed or measured and predicted YS and TS values ​​(see Figure 9), it is evident that the forecasting and / or correction models used in the context of dynamic alloying enable precise predictions.

[0417] Example 2: P110 (API 5-CT)

[0418] Figure 10 shows the result of the PCA (Principal Component Analysis). This verifies whether and how significantly a variable influences the result.

[0419] Formulas for the yield strength YS and tensile strength TS are determined through multiple linear regression analysis:

[0420] YS = 1126 — 272 x wt. —%C — 97 x wt. —%Mn + 70 x wt. —%Cr + 114 x wt. —%Ni + 257 x wt. —%Mo — 211 x wt. —%Cu + 54 x wt. — %S ;

[0421] TS = 1240 + 786 x wt. —%C — 53 x wt. —%Mn + 103 x wt. —%Cr + 19 x wt. —%Ni + 38 x wt. —%Mo + 180 x wt. —%Cu + 102 x wt. —%Si.

[0422] Figures 11 to 14 show plots of the predicted values ​​(prog.) against the observed or measured values ​​(beob.) of YS and TS, with Figures 11 and 13 referring to the training data and Figures 12 and 14 to the population. The regression line, in the context of multiple linear regression, is a line that describes the relationship between several independent variables and a dependent variable. This line minimizes the sum of the squared distances (residuals) between the actual data points and the predicted values. Multiple linear regression extends the concept of simple linear regression by including multiple predictors to enable more accurate predictions. The circles represent the predicted values. The closer a circle is to the regression line, the better the prediction. [95% International Patent Application]

[0423] Voestalpine Tubulars Gmbh & Co KG; Voestalpine Stahl Donawitz GmbH

[0424] 240917WO

[0425] Confidence bands (dashed lines) of a prediction probability indicate the range within which 95% of future data points are expected to lie. These bands account for the uncertainty in the estimates of the regression parameters and provide a visual representation of the accuracy of the predictions. They are wider than simple confidence intervals because they consider the uncertainty across the entire range of the independent variables.

[0426] Overall, given the good comparability of the observed or measured and predicted YS and TS values ​​(see Figure 15), it is evident that the forecasting and / or correction models used in the context of dynamic alloying enable precise predictions.

[0427] The present method thus enables dynamic and flexible alloying, in which the influence or effect of the influencing elements is compensated by a targeted addition of the compensating elements.

[0428] The compensation elements can be selected taking into account, among other things, resolution- and output-specific as well as economic aspects, thus significantly increasing the cost efficiency of the overall process.

[0429] Furthermore, the present method makes it possible to reliably maintain the desired material properties despite the use of raw materials with an increased load of influencing elements.

Claims

1. International patent application Voestalpine Tubulars Gmbh & Co KG; Voestalpine Stahl Donawitz GmbH 240917WO Claims 1. A process for producing heat-treatable steels for oilfield applications with specified material properties, which are ensured by a target alloy, wherein at least one primary metallurgical unit leads to a first melt, wherein at least one analysis of the elemental content is carried out from the first melt, and wherein at least one actual value of the melt analysis is transmitted to a control system. characterized by the fact that A distinction is made between influencing and compensating elements, whereby Influencing elements are elements that have an influence on at least one material-related property of an end product, and compensating elements are elements that have an influence on at least one material-related property and compensate for the influence of the influencing elements, wherein the influencing elements whose influence on the material properties of the final product is to be compensated comprise one, several or all from the group of Ni, Mo, Cu, wherein as compensation elements one, several or all from the group of C, Si, Mn, Cr are selected, wherein the material properties include Hollomon-Jaffe parameters, hardenability indices, one or more carbon equivalents, yield strength YS and tensile strength TS, wherein the magnitude of the influence of at least one actual value of the respective influencing and compensating elements on at least one material-related property of the final product is known, wherein which at least one actual value is recorded with respect to those influencing and compensating elements which have an influence on at least one material-related property of the final product, wherein International Patent Application Voestalpine Tubulars Gmbh & Co KG; Voestalpine Stahl Donawitz GmbH 240917WO for at least one material-related property of the final product, at least one compensation element is determined which adjusts the at least one material-related property, wherein one or more compensating elements are added to the melt in an amount that brings the at least one material property into a target range and compensates for the influence of one or more influencing elements on the at least one material property, and wherein For this purpose, two components are used in the control system: a forecasting model and a correction model, whereby the forecasting model calculates the influence of the influencing and compensating elements on at least one material-related property of the final product, and the correction model calculates corrected target values ​​of the compensating elements in order to bring at least one material-related property into a target range.

2. Method according to claim 1, characterized in that the analysis is carried out by means of sampling according to EN ISO 14284.

3. Method according to claim 1 or 2, characterized in that subsequent post-treatment steps following steel production are carried out unchanged until the final product is obtained.

4. A method according to any of the preceding claims, characterized in that the forecasting model and / or correction model is generated using one, several or all of the following models: linear regression models, polynomial regression models, decision tree-based regression models, random forest regression models, nearest neighbor models, neural network models, support vector machine models, ADA boost models, regression boost models, HIST boost models, XGBOOST models, generalized additive models, symbolic regression models.

5. Method according to one of the preceding claims, characterized in that, when a material property is considered, the at least one recorded actual value of the analysis is assigned to the at least one prediction model and / or correction model using the square root of the mean square deviation of the material property, wherein for the at least International Patent Application Voestalpine Tubulars Gmbh & Co KG; Voestalpine Stahl Donawitz GmbH 240917WO An actual value is determined by calculating the square root of the mean square deviation of the material property for all prediction models and / or correction models, and based on the results, the prediction model and / or correction model with the highest accuracy is selected.

6. Method according to one of the preceding claims, characterized in that, when several material properties are considered, the at least one recorded actual value of the analysis is assigned to the at least one prediction model and / or correction model using the mean value and / or the sum of the square roots of the mean square deviations of the material properties, wherein the mean value and / or the sum of the square roots of the mean square deviations of the material properties is determined for the at least one actual value for all prediction models and / or correction models, and the prediction model and / or correction model with the highest accuracy is selected based on the results.

7. Method according to one of the preceding claims, characterized in that the forecasting model and / or correction model is generated using multiple linear regression analysis.

8. Method according to one of the preceding claims, characterized in that the tensile strength TS and the yield strength YS are calculated in a prediction and / or correction model based on multiple linear regression analysis according to the following formulas: T S = a0+ x X r + ax X2+ — I- a n x X n ; TS = ßo + ßi x Yi + ß2x X2+ — I- ß n x X n , where ao and ßo basic factors of tensile strength TS and yield strength YS, ai- a n and ßi- ßn regression coefficients and Xi-Xn element contents in wt.% are shown. International patent application Voestalpine Tubulars Gmbh & Co KG; Voestalpine Stahl Donawitz GmbH 240917WO 9. Method according to one of the preceding claims, characterized in that influencing elements are Mo and Cu in Ni-alloyed heat-treatable steels, Ni and Cu in Mo-alloyed heat-treatable steels and Cu in Ni-Mo-alloyed heat-treatable steels, wherein in these cases the aforementioned alloying elements are also suitable as compensation elements.

10. Method according to one of the preceding claims, characterized in that at least one of the following formulas is used to calculate the carbon equivalent depending on standards and / or specifications of a specific grade of heat-treated steel: CEV (Carbon Equivalent Value) = Weight — %C + Gew -^ / oMn _|_ wt%Cr+wt%Mo+wt%V wt%Ni+wt%Cu_ 5 15 ' CET (Carbon Equivalent Thyssen) = wt. - %C + Gew' / oMn ^+ Gew - / oMo _|_ wt.% Cr + wt.% Cu wt.% Ni 20 40 ' Pcm (Critical Metal Parameter) = wt. - %C + GeW 30 / oS1 + wt.-%Mn+wt.-%Cu+wt.-%Cr, wt.-%Mo, wt.-%Ni, wt.-%V, " - 1 - 1 - 1 - F5 x wt. -%B, 20 15 60 10 ' where wt.%i is the content of the respective element i in wt.%.

11. Method according to one of the preceding claims, characterized in that the analysis is carried out at least in the first melt of the last primary metallurgical aggregate of a production route, in particular from a tapping of crude steel, before or after a first addition of alloying elements and at least after a second addition of alloying elements.

12. Method according to one of the preceding claims, characterized in that, if a first element is introduced by a precursor in a proportion that lies below a desired target range defined by the target alloy, the first element, provided it is a desired alloying element, is added to the extent necessary to reach the target range, or, if the first element is introduced by a precursor in a proportion that already corresponds to the target range, the first element is no longer added, or, if the first element is introduced by a precursor in a proportion that exceeds the International Patent Application Voestalpine Tubulars Gmbh & Co KG; Voestalpine Stahl Donawitz GmbH 240917WO The target area is such that the first element is compensated by a reduced alloying element of a second similarly acting element or an increased alloying element of a counteracting third element.

13. Method according to one of the preceding claims, characterized in that the correction model used defines a sequence of the different compensation elements according to resolution- and output-specific as well as economic considerations.

14. Method according to one of the preceding claims, characterized in that the target alloy comprises the following target alloy composition in wt.%: C 0.05-1.2 Si 0.001-1.9 Mn 0.1-3.5 in addition, iron and unavoidable impurities, where optionally one, several or all of the following elements are included in wt.%: P < 0.1 S <0.35 Cr 0.001-15 Cu 0.001-0.5 Mon 0.001-1.5 Ni 0.001^.0 N 0.0001-0.05 Sn 0.001-0.03 V 0.001-0.4 Nb 0.001-0.1 Ti 0.001-0.08 AI 0.0005-0.1 B 0.0005-0.

01.

15. Tax system for the production of heat-treatable steels for oilfield applications with specified material properties, which are achieved through a target alloy. International patent application Voestalpine Tubulars Gmbh & Co KG; Voestalpine Stahl Donawitz GmbH 240917WO to ensure, and to carry out the method according to one of the preceding claims, characterized in that the control system comprises two components: a forecasting model and a correction model, wherein the forecasting model is designed to calculate an effect of influencing elements and compensation elements on at least one material property of the heat-treatable steel, and the correction model is designed to calculate corrected target values ​​of compensation elements in order to bring the at least one material property into a target range by adding at least one compensation element.

16. Control system according to claim 15, characterized in that the forecasting model and / or correction model can be generated using one, several or all of the following models: linear regression models, polynomial regression models, decision tree-based regression models, random forest regression models, nearest neighbor models, neural network models, support vector machine models, ADA boost models, regression boost models, HIST boost models, XGBOOST models, generalized additive models, symbolic regression models.

17. Control system according to claim 15 or 16, characterized in that the material properties tensile strength TS and yield strength YS can be calculated in a prediction and / or correction model based on multiple linear regression analysis according to the following formulas: T S = a0+ x X r + ax X2+ — I- a n x X n ; TS = ßo + ßix Yi + ß2x X2+ — I- ß n x X n , where ao and ßo basic factors of tensile strength TS and yield strength YS, ai- an and ßi- ßn regression coefficients and Xi-Xn element contents in wt.% are given.

18. Tax system according to one of claims 15 to 17, characterized in that the carbon equivalent is calculated depending on standards and / or International patent application Voestalpine Tubulars Gmbh & Co KG; Voestalpine Stahl Donawitz GmbH 240917WO Specifications of a particular grade of heat-treated steel require that at least one of the following formulas can be used: CEV (Carbon Equivalent Value) = Weight — %C + Gew -^ / oMn _|_ wt%Cr+wt%Mo+wt%V wt%Ni+wt%Cu_ 5 15 ' CET (Carbon Equivalent Thyssen) = wt. - %C + Gew ' / oMn ^+ Gew - / oMo _|_ wt.% Cr + wt.% Cu wt.% Ni 20 40 ' Pcm (Critical Metal Parameter) = wt. - %C + GeW 30 / oS1 + wt.-%Mn+wt.-%Cu+wt.-%Cr, wt.-%Mo, wt.-%Ni, wt.-%V, " - 1 - 1 - 1 - F 5 x wt. -%B, 20 15 60 10 ' where wt.%i is the content of the respective element i in wt.%.

19. Control system according to one of claims 15 to 18, characterized in that the target alloy comprises the following target alloy composition in wt.%: C 0.05-1.2 Si 0.001-1.9 Mn 0.1-3.5 in addition, iron and unavoidable impurities, where optionally one, several or all of the following elements are included in wt.%: P < 0.1 S <0.35 Cr 0.001-15 Cu 0.001-0.5 Mon 0.001-1.5 Ni 0.001^.0 N 0.0001-0.05 Sn 0.001-0.03 V 0.001-0.4 Nb 0.001-0.1 International patent application Voestalpine Tubulars Gmbh & Co KG; Voestalpine Stahl Donawitz GmbH 240917WO Ti 0.001-0.08 AI 0.0005-0.1 B 0.0005-0.

01. Metallic hollow body, in particular seamless steel pipe for oilfield applications made of a heat-treated steel, manufactured according to the method according to any one of claims 1 to 14.

Images