METHOD FOR CALCULATING THE COVER EFFECT IN COMPUTER-READABLE PETROLEUM SYSTEM AND STORAGE MEDIA MODELING

Abstract

The present invention relates to a method for calculating the cover effect in the modeling of petroleum systems, comprising: obtaining input lithospheric and sedimentary data; discretizing the model differently in the sedimentary and lithospheric domains; starting the calculation of the cover effect; verifying whether the deposition time corresponding to each sedimentary layer is greater than the present time and whether the basin age is greater than the deposition time corresponding to each sedimentary layer, by refraining from carrying out the method;the verification of whether the deposition time corresponding to each sedimentary layer is less than or equal to the present time and whether the age of the basin is less than or equal to the deposition time corresponding to each sedimentary layer and the verification of whether it is in the collapse period, in which: if it is in the collapse period, the calculation of the collapse; if it is not in the collapse period or if it is after the collapse calculation stage, the calculation of the sedimentation; in the collapse period, the calculation of the advective vertical displacement velocity due to lithospheric thinning for each XY coordinate; the calculation of the fluid flux; the use of finite elements to perform calculations at each instant in time; the performance of the addition of the thermal effect of the lithospheric and sedimentary domains at each time stage.

Description

Title of the invention: METHOD FOR CALCULATING THE COVERING EFFECT IN THE MODELING OF OIL AND SUPPORT SYSTEMS COMPUTER-READABLE STORAGE Scope of the invention

[0001] The present invention relates to the technical field of petroleum system modeling. In particular, the present invention relates to a method for calculating the blanket effect in computer-readable petroleum system and storage media modeling. Background of the invention

[0002] In the study of sedimentary basins and petroleum systems, with the aim of better assessing geological risks in the exploration of new areas, it is increasingly necessary to obtain more accurate predictive results for temperature and heat flow. These predictive results allow for the analysis of potential new areas, especially in remote regions, where data obtained from wells are becoming increasingly scarce.

[0003] In order to obtain more accurate predictive results for temperature and heat flow, geological process simulations are often carried out, where backstripping is calculated, which consists of the removal of sedimentary layers and their decompaction for each geological event, obtaining paleogeometric estimates during the geological evolution of the sedimentary section.

[0004] Normally, 3D petroleum system analysis software calculates backstripping using several 1D equations, considering geological basins under the influence of local isostasy. In other software applications, the implemented model calculates backstripping in a more refined way, by coupling the flexural isostasy effects in the 3D basin and thus approximating the conditions observed in nature due to the flexural effects of the lithospheric layer. The flexural response allows for a more precise determination of the paleogeometries of the basement and sedimentary layers and is directly related to the thermal state of the lithosphere, which, in turn, controls the heat flow in the basement of the sedimentary basin at each time step.

[0005] To determine the heat flux to be used as a lower boundary condition in simulations within the sedimentary basin, it is necessary to quantify the thermal evolution resulting from the geothermal gradient and lithospheric stretching. (collapse) and radiogenic heat present in the upper portion of the crust.

[0006] Nevertheless, the transient thermal effect linked to the deposition and compaction of cold sediments, known as the cover effect, is not currently measured, a cover effect which can act during and after sedimentation, causing alterations such as: reduction of the geothermal gradient of the crust and, consequently, reduction of the heat flux in the basement and heating at the end of each phase of deposition by the process of transient heat diffusion, for the thermal rebalancing of the temperature field of the lithosphere, which depends on the thermal conductivity, the thickness and the sedimentation rate of the sedimentary arrangement. State of the art

[0007] The paper entitled “Impacto do efeito blanketing na histôria térmica de bacias sedimentares: modelos sintéticos e estudo de caso na Bacia de Santos” (Impact of the blanketing effect on the thermal history of sedimentary basins: synthetic models and a case study in the Santos Basin), by Cleriston Ferreira Silva (available at https: / / pantheon.ufrj.br / handle / 11422 / 13673?mode=full) provides an in-depth study of the effect of cold sediment deposition (blanking) on ​​heat fluxes in the upper part of the basement, taking into account or not the collapse effect (lithospheric thinning). Specifically, this paper describes only specific tests and a one-dimensional (1D) scope for the blanketing effect.

[0008] The paper “Thermal evolution of the intracratonic Paris Basin: insights from 3D basin modelling” by Martina Torelli, Renaud Traby, Vanessa Teles, and Mathieu Ducros (available at https: / / www.sciencedirect.com / science / article / abs / pii / S0264817220302701?via%3Dihub) includes a 3D model of a basin, identifying parameters that affect the temperature distribution over time, and showing the evolution of sedimentary basins over time. However, this paper does not teach the application of the cover effect. Brief description of the invention

[0009] The present invention, according to a preferred embodiment thereof, defines a method for calculating the hedging effect in the modeling of petroleum systems comprising: • obtaining input lithospheric and sedimentary data; • the discretization of the model differently in the sedimentary domain and in the lithospheric domain; • the start of the calculation of the hedging effect; • checking whether the deposition time corresponding to each sedimentary layer is greater than the present time and whether the age of the basin is greater than the deposition time corresponding to each sedimentary layer, by refraining from carrying out the process; • verification of whether the depositional time corresponding to each sedimentary layer is less than or equal to the present time and whether the age of the basin is less than or equal to the depositional time corresponding to each sedimentary layer, and verification of whether it is within the collapse period, in which: • if it is in the collapse period, the calculation of the collapse; • if it is not in the collapse period or if it is after the collapse calculation stage, the sedimentation calculation; • the calculation of the advective vertical displacement velocity due to collapse for each XY coordinate; • the calculation of fluid flow; • the use of finite elements to perform 1 calculation at each instant in time; • the realization of the addition of the thermal effect of the lithospheric and sedimentary domains at each time step.

[0010] Specifically, according to another preferred embodiment of the present invention, the lithospheric and sedimentary data comprise at least one of: • dimensions of the area; • Thermophysical parameters, such as: crustal conductivity (W / m / K); crustal density (kg / m3); crustal specific heat (J / kg / K); crustal radiogenic heat (qW / m3); lithospheric mantle conductivity (W / m / K); lithospheric mantle density (kg / m3); lithospheric mantle specific heat (J / kg / K); lithospheric mantle radiogenic heat (qW / m3); water density (kg / m3); water conductivity (W / m / K); water specific heat (J / kg / K); asthenosphere density (kg / m3); elasticity coefficient (N / m2); Poisson's ratio; coefficient of thermal expansion (1 / °C); acceleration due to gravity (m / s2); • boundary conditions in the lithosphere, such as surface temperature and core temperature; • Lithospheric data, corresponding to the number of layers and the thermophysical properties of the layer, including at least one of the following: thickness (m); density (kg / m3); specific heat (J / kg / K); conductivity (W / m / K); radiogenic heat (W / m3*le-6); • Horizon and lithofacies maps for each sedimentary layer; in which salt and igneous maps are optional, depending on the region of interest; • Values ​​for the discretization of the numerical model, in which the values ​​can be defined by the user, in the "number of steps" or "separation" column for temporal discretization; and in the "number of elements" or "separation" columns for spatial discretization in the x, y, and z dimensions. A larger discretization is suggested: 1) in the collapse period (thousands of years) and 2) in the sedimentary part (tens or hundreds of meters in the z-thickness, corresponding to the maximum depth of the basin); for other periods and areas, a discretization of between 2,000 and 3,000 meters will ensure convergence and good results); • age of the pelvis (in millions of years - mya.); • time and period of the collapse (in millions of years - mya.); • values ​​or maps of the lithosphere stretching factors (|3) or of the crust and mantle (ô and |3).

[0011] Furthermore, according to another preferred embodiment of the present invention, the collapse calculation step, if it falls within the collapse period, includes the calculation of the transient heat due to lithospheric thinning, which causes variations in the heat flux, from the advective thermal model:

[0012] / v W / yx / v \ +(pr)(d) VxgQ \ A / \ / ' \ f

[0013] where:

[0014] vs denotes the speed of the solid particles;

[0015] 0 is the porosity;

[0016] q is the density;

[0017] c is the decay constant;

[0018] and 2 is the conductivity; • the calculation of the crustal value θ and the mantle value [3] within the collapse, according to:

[0019] p = • the calculation of the thicknesses and horizons of the sediment layers as a function of the value of the crust θ and the value of the mantle [3; • the quantification of radiogenic heat in the upper portion of the crust.

[0020] Furthermore, according to another preferred embodiment of the present invention, the sedimentation calculation step includes calculating the covering effect due to sediment deposition, by means of an advective model comprising: • the decompaction of sediment layers (backstripping); • the stacking and compaction of sediment layers up to the corresponding deposition time and according to the thermal parameters recalculated at depth; • the new calculation of the base depth; • the calculation of radiogenic heat in the sedimentary portion.

[0021] Furthermore, according to another preferred embodiment of the present invention, the step of calculating the vertical advective displacement velocity due to collapse for each XY coordinate corresponds to the calculation of vbulk = G*(hz) for each z coordinate, where vbulk = average velocity of the asthenosphere's uplift due to collapse, varying linearly with z; G = magnitude of the vertical velocity gradient along the lithosphere h, indicating how much the fluid velocity (asthenosphere) moves vertically along the thickness defined as "h" in the formulation; h = limit of the lithosphere's depth. Once this calculation is performed, the advective velocities are added to the sedimentation velocity, in which the greater the compaction, the slower the uplift due to collapse.

[0022] Furthermore, according to another preferred embodiment of the present invention, the fluid flow calculation step includes the definition of thermal properties in the nodes of the 3D digital mesh, comprising at least one of conductivity, radiogenic heat, density*specific heat of the solid part (hc_bulk), density*specific heat of the fluid part (hc_water).

[0023] In addition, the process of the present invention further includes the step of generating outputs for the corresponding deposition time, comprising the generation of maps, sections and well profiles with thermal and structural information of the sedimentary basin.

[0024] Furthermore, according to another preferred embodiment of the present invention, a computer-readable storage medium is defined comprising, stored therein, a set of computer-readable instructions which, when executed by a computer, perform the method for calculating the hedging effect in the modeling of petroleum systems of the present invention. Brief description of the figures

[0025] In order to complete the present description and to better understand the features of the present invention, and according to a preferred embodiment thereof, a set of figures is presented herein, where its preferred embodiment is represented in a representative, but not limiting, manner.

[0026] [Fig-1] The [Fig. 1] illustrates a flowchart of the process for calculating the cover effect in the modeling of petroleum systems.

[0027] [Fig.2] Fig.2 shows a flowchart of the numerical solution process of the method of the present invention.

[0028] [Fig. 3] [Fig. 3] illustrates a screen of an application for entering dimensions of the area under study, thermophysical parameters and thermal boundary conditions.

[0029] [Fig.4] Fig.4 shows an interface of an application for introducing the characteristics of the lithosphere, the number of layers and thermophysical properties.

[0030] [Fig.5] [Fig.5] shows a screen of an application for inserting cards, lithofacies, saline and igneous layers, the definition of the lithofacies library is illustrated.

[0031] [Fig. 6] [Fig. 6] shows a screen of an application for entering values for the discretization of the numerical model, the age of the basin and time, the period of collapse, values ​​or maps of the stretching factors of the lithosphere, or crust and mantle.

[0032] [Fig.7] Fig.7 shows examples of maps used as input for data.

[0033] [Fig.8] The [Fig.8] represents the domain for a simplified 1D model.

[0034] [Fig.9] Fig.9 is a schematic drawing of the collapse process lithospheric.

[0035] [Fig. 10] The [Fig. 10] shows the schematic model for updating the properties in the nodes of the finite element mesh.

[0036] [Fig. 11] The [Fig. 11] illustrates the division of the finite element mesh.

[0037] [Fig. 12a] The [Fig. 12a] shows heat flux maps for all sedimentary deposition times.

[0038] [Fig. 12b] The [Fig. 12b] illustrates effective elastic thickness maps.

[0039] [Fig. 12c] Fig. 12c presents paleogeometries of the basement and layers sedimentary.

[0040] [Fig.l2d] Fig.l2d shows a graph with heat flux results.

[0041] [Fig. 13a] Figure 13a shows a graph illustrating the coupling of the effect of cover, when the effect of the sedimentation rate and the sedimentary deposition process are taken into account.

[0042] [Fig. 13b] Fig. 13b presents a graph that shows a basin scenario with sediments (lithofacies map) and collapse (beta map).

[0043] [Fig. 13c] Fig. 13c presents a graph that shows a sediment-free basin scenario.

[0044] [Fig.l3d] Fig.l3d illustrates a graph of a scenario where the conductivity of sediments is equal to 2.5 W / m / K and the conductivity of the crust is equal to 2.5 W / m / K.

[0045] [Fig. 13e] The [Fig. 13e] illustrates a graph of a scenario where the conductivity of sediments is equal to 1.25 W / m / K and the conductivity of the crust is equal to 2.5 W / m / K.

[0046] [Fig. 13f] Figure 13f illustrates a graph of a scenario where the sediment conductivity is equal to 5 W / m / K and the crust conductivity is equal to 2 W / m / K. Detailed description of the invention

[0047] Fig. 1 illustrates a flowchart of the process for calculating the cover effect in the modeling of petroleum systems, according to an embodiment of the present invention, and its respective description presented below explains the steps and calculations involved in the 3D simulation of thermal and structural processes in sedimentary basins, taking into account the implementation of the cover effect, which will have a significant influence on the thermal evolution of the analyzed areas over geological time.

[0048] The method for calculating the cover effect in petroleum system modeling involves coupling thermal events of sedimentary and lithospheric origin, generating refined results of temperatures, heat fluxes, and paleogeometries of sedimentary basins in the form of 3D maps. The method includes incorporating the effect of sediment deposition into the basin thermal results through coupling the lithospheric and sedimentary portions in the computational thermal model, thereby improving the accuracy of the results compared with well data, especially those concerning temperature and vitrinite.

[0049] The results obtained using the method of the present invention can be used as thermal and structural boundary conditions for integration with other petroleum system modeling software and also for direct thermal calibration, by comparing the results obtained from the model with well data from a region or basin under study.

[0050] In particular, the covering effect is resolved in the time loop by combining the lithospheric and sedimentary effects, respectively. In particular, the method calculates: a) the thermal diffusion process; b) the advection effects due to the collapse of the lithosphere; c) the advection effects due to d) sediment deposition (covering effect); d) radiogenic heat generation.

[0051] The method for calculating the hedging effect in petroleum system modeling comprises the following steps: • Obtaining input lithospheric and sedimentary data 1, in which the lithospheric and sedimentary data include at least one of: • dimensions of the area; • Thermophysical parameters, such as: crustal conductivity (W / m / K); crustal density (kg / m³); crustal specific heat (J / kg / K); crustal radiogenic heat (qW / m³); lithospheric mantle conductivity (W / m / K); lithospheric mantle density (kg / m³); lithospheric mantle specific heat (J / kg / K); lithospheric mantle radiogenic heat (qW / m³); water density (kg / m³); water conductivity (W / m / K); water specific heat (J / kg / K); asthenosphere density (kg / m³); elasticity coefficient (N / m²); Poisson's ratio; coefficient of thermal expansion (1 / °C); acceleration due to gravity (m / s²); isothermal temperature for Te (°C); • boundary conditions in the lithosphere, such as surface temperature and core temperature; • lithospheric data, corresponding to the number of layers and the thermophysical properties of the layer, including at least one of: thickness (m); density (kg / m3); specific heat (J / kg / K); conductivity (W / m / K); radiogenic heat (qW / m3); • Horizon and lithofacies maps for each sedimentary layer; in which salt and igneous maps are optional, depending on the region of interest; • values ​​for the discretization of the numerical model, in which the values ​​can be freely defined by the user in the "number of steps" or "separation" column for temporal discretization; and in the "number of elements" or "separation" columns for spatial discretization in the x, y, and z dimensions (as illustrated in [Fig. 6]). Larger discretization is suggested: 1) in the collapse period (thousands of years) and 2) in the sedimentary part (tens or hundreds of meters in the z-thickness corresponding to the maximum depth of the basin); for other periods and areas, a discretization of between 2,000 and 3,000 meters will ensure convergence and good results. • age of the pelvis (in millions of years - mya);

[0052] • time and period of the collapse (in millions of years - mya); • values ​​or maps of the lithosphere stretching factors (|3) or of the crust and mantle (o and |3); • the discretization of the numerical model, including the discretization of the model differently in the sedimentary domain and in the lithospheric domain 2; • the start of the calculation of the hedging effect 3; • checking whether the deposition time corresponding to each sedimentary layer t is greater than the present time and whether the age of the basin is greater than the deposition time corresponding to each sedimentary layer 14 and refraining from carrying out process 5; • verification of whether the deposition time corresponding to each sedimentary layer t is less than or equal to the present time and whether the age of the basin is less than or equal to the deposition time corresponding to each sedimentary layer 14 and verification of whether it is in the collapse period 6, in which: • if it is in the collapse period, the calculation of the collapse period 7, including the calculation of the transient heat due to lithospheric thinning, which causes variations in the heat flux, from the advective thermal model: / 4¾ +(1 -«H / X = Wfl + 0*0 ( «0 VxeQ / \ / \ ) \ ' i

[0053] (Equation 1)

[0054] where:

[0055] vs denotes the speed of the solid particles;

[0056] 0 is the porosity;

[0057] q is the density;

[0058] c is the decay constant;

[0059] and A is the conductivity; • the calculation of the crustal value θ and the mantle value [3] within the collapse, according to equation 2:

[0060] fi = (Equation 2) • the calculation of the thicknesses and horizons of the sediment layers as a function of the value of the crust θ and the value of the mantle [3; • the quantification of radiogenic heat in the upper portion of the crust. if it is not within the collapse period or if it is after the collapse calculation step 7, the sedimentation calculation 8, including the calculation of the cover effect due to sediment deposition, by means of an advective model, comprising: the decompaction of sediment layers (backstripping); the stacking and compaction of sediment layers up to the corresponding deposition time and according to the thermal parameters recalculated at depth; the new calculation of the base depth; the calculation of radiogenic heat in the sedimentary portion; The calculation of the vertical advective displacement velocity due to collapse, for each XY coordinate, using the formula vbulk = G*(hz) for each z coordinate, where vbulk = average velocity of asthenosphere uplift due to collapse, varying linearly with z; G = magnitude of the vertical velocity gradient along the lithosphere h, indicating how much the fluid velocity (asthenosphere) moves vertically along the thickness defined as "h" in the formulation; h = depth limit of the lithosphere. Once this calculation is performed, the advective velocities are added to the sedimentation velocity, in which the greater the compaction, the slower the uplift due to collapse. the calculation of fluid flow 10, including the definition of thermal properties in the nodes of the 3D digital mesh, including conductivity, radiogenic heat, density*specific heat of the solid part (hc_bulk), density*specific heat of the fluid part (hc_water) the use of finite elements to perform calculations at a given moment H; the realization of the addition of the thermal effect of the lithospheric and sedimentary domains at each time step 12; the generation of outputs for the corresponding deposition time 13, including the generation of maps, sections and well profiles with thermal and structural information of the sedimentary basin; In particular, the step of using finite elements to perform calculations at a given time 11 involves the use of the PCG process - default tolerance of the solver: le-07 and distributed processing, using OpenMP directly in the code.

[0061] Figure 3 illustrates a screen of an application which implements the method of the present invention to enter the dimensions of the area under study, the thermophysical parameters and the thermal boundary conditions.

[0062] Fig. 4 shows an interface of an application which implements the method of the present invention to input the characteristics of the lithosphere, the number of layers and the thermophysical properties.

[0063] Figure 5 shows a screen of an application which implements the method of the present invention to introduce maps, lithofacies, salt and igneous layers; the definition of the lithofacies library is illustrated.

[0064] Figure 6 shows a screen of an application which implements the method of the present invention to input values ​​for the discretization of the numerical model, basin age and time, collapse period, values ​​or maps of the stretching factors of the lithosphere (|3) or of the crust and mantle (δ and P).

[0065] The lithofacies library is created to define the lithologies distributed in each sedimentary layer. The library includes an ID, used to identify the lithofacies in the horizon maps, and corresponding properties, associated with the ID, as shown in Table 1:

[0066] Table 1: Properties of the lithologies that will compose each sedimentary layer Density (kg / m³) Surface porosity (%) Compaction coefficient (1 / m) Diffusivity (m² / s) Conductivity (W / m / K) Radiogenic heat (qW / m³)

[0067] Regarding the maps, a plurality of maps can be used as data input: horizons, lithofacies, boundary conditions, salt deposit thickness, stretching factors, properties, among others. The maps are provided as files, typically in .xyz format (coord, x., coord, y., z-value). Figure 7 shows examples of maps used as data input in the process of the present invention.

[0068] More specifically, what characterizes the cover effect or cover effect is the implementation where the parameters of equation 1, 0, q, c and 2 (porosity, density, decay constant and conductivity, respectively) vary according to the porosity / depth relationship of the sedimentary matrix.

[0069] According to Athy's law (Athy LF, 1930, "Density, porosity, and compaction of sedimentary rocks", AAPG Bulletin, v. 14, no. 1, pp. 1-24), the variation of porosity S with depth z is given by equation 3 below:

[0070]

[0071] (Equation 3),

[0072] where is the surface porosity and c is the compaction coefficient of the sedimentary matrix.

[0073] With this, the other parameters of equation 1 will vary according to porosity / depth values ​​given as a function of the variable 0.

[0074] The effective conductivity of the sedimentary matrix is ​​obtained from the geometric mean between the conductivity of the solid phase X_s and the conductivity of the water that fills the porous part, X_w, in other words: [°°75i

[0076] (Equation 4).

[0077] The effective specific heat (pc) is obtained by the weighted average between the solid part (pc)s and the fluid part (pc)w, that is:

[0078] - ( 1 - 3^pc^ +

[0079] (Equation 5).

[0080] The effective radiogenic heat (pr) is obtained only by weighting the solid part, that is to say:

[0081] =

[0082] (Equation 6).

[0083] Furthermore, the advective velocities of the solid part and the fluid part corresponding to the sediments are obtained from the law of conservation of mass applied to the sedimentary layers. The formulation for the 1D case with only one sedimentary layer is developed for a domain, according to [Fig. 8], which is the representation of the domain for a simplified 1D model, taken and adapted into French from Hutchison, L, 1985; The effects of sedimentation and compaction on oceanic heat flow, Geophysical Journal of the Royal Astronomical Society 82 (3) 439-459. doi:10.1111 / j.l365-246X.1985.tb05145.x.3.

[0084] The deposition rate at z=0 is:

[0085] , _ 0-0)

[0086] (Equation 7).

[0087] Furthermore, the velocity of the base at z=B is: [OOSS] M W / ÜW)) [00S9] (Equation S).

[0090] Then, the velocity of the base for any t, any z, will be given by:

[0091] v / A w\4 7 (14b)) e ■■ '

[0092] (Equation 9).

[0093] The complete methodology is given by adding the effect of sedimentary deposition, the effect of covering, to the collapse process in the lithosphere and radiogenic heat, in the lithospheric and sedimentary domains, which are inserted into the thermal diffusion / advection equation in a 3D solid medium (equation 1).

[0094] Collapse is the process of narrowing / thinning of the lithosphere and displacement of asthenosphere material in the vertical direction, as shown in [Fig. 9]. [Fig. 9] schematically represents the lithospheric collapse process. On the left, the lithosphere is in a normal configuration. On the right, the lithosphere has become thin by a parameter (3) and there is a consequent uplift of asthenospheric material.

[0095] This is how the asthenosphere is lifted, from the depth limit ^x, j) = 0, in order to fill the space left by the exit of lithospheric material because of its thinning and this is represented in the advective term of equation 1, with the sedimentary deposition process (vertical velocity).

[0096] The effect of sediment cover and advection due to collapse are vertically competing processes, so that the greater the compaction, the slower the uplift rate due to lithospheric thinning.

[0097] 3D numerical solution of the transient heat transport problem in finite elements: [009S] The numerical solution of the presented methodology for quantifying the blanketing effect coupled with other thermal processes was developed using finite elements. The solution for the three-dimensional case is obtained by evaluating the compaction independently at each node of the finite element mesh.

[0099] The numerical model uses HS hexahedral elements, with 8 nodes for the solution in the xy direction and elements with 12 H12 nodes, in the z direction.

[0100] Sediment deposition and collapse cause changes in the geological properties of each finite element over time, i.e., the mesh elements are subject to variations in the geological properties of their domains ([Fig.11]).

[0101] In the implementation, it is assumed that the properties are interpolated by the same shape functions of the element concerned.

[0102] Figure 10 shows the schematic model for updating the properties in the nodes of the finite element mesh. In Figure 10, (.); denotes the nodal values ​​of the geological properties obtained from the exact shape of the domain at the relevant time.

[0103] In general, the code receives as input data the spatial distribution (in x, y) of the thicknesses of the sedimentary layers and their corresponding deposition times.

[0104] During the simulation, the thickness of each layer z_i is evaluated according to the current time. Once the current thicknesses have been evaluated, the porosity of each node of the finite element mesh is calculated from Athy's law and the thermal properties are then evaluated according to the equations for the variation of thermal properties.

[0105] Once the nodal properties have been obtained, the finite element model is defined, by interpolating the thermal properties with the same shape functions of the selected element, to generate the mesh.

[0106] Numerical solution formulation: preconditioned conjugate gradient (PCG) method

[0107] The numerical solution of the method of the present invention uses the implicit / explicit time integration method, arriving at the following algebraic system of linear equations:

[0108] (M+ K^)+Mcf

[0109] (Equation 10).

[0110] where the matrix on the left side is a symmetric positive definite matrix.

[0111] Three main characteristics of this system of equations stand out: symmetry, hollowness and positive definite property.

[0112] Symmetry, in combination with the positive-definite property, allows the system to be solved generically by the conjugate gradient method (CGM). Since this is an iterative method (without modification of the system structure), it is possible to use sparse data structures to store the linear system. In the implementation of the model described in the present method, a variation of the CGM is used, namely the preconditioned conjugate gradient (PCG) method, which is a strategy for optimizing the traditional method, improving the conditioning of the matrix A of the linear system (equation 10), by first multiplying the system by a matrix that is close to A but can be easily inverted.

[0113] Then, the following equivalent system can be solved:

[0114] MaAx= M^b

[0115] (Equation 11).

[0116] The new matrix MaA exhibits better conditioning than A. The inverse matrix is ​​obtained by inverting each of the elements of the main diagonal of matrix A and this is known as the Jacobi technique, used in the implemented numerical simulator to solve the proposed process.

[0117] The numerical approximation of the thermal problem is therefore solved by using several iterations from an initial approximation, until convergence is reached as a function of the error tolerance defined between the current iteration and the previous iteration:

[0118] Initial approximation:

[0119] r(0; = b-Ax^ (Equation 12)

[0120] = AT^o) (Equation 13)

[0121] Subsequent iterations:

[0122] (Equation 14)

[0123] x^y = x^d® (Equation 15)

[0124] r(z+1) = r® - Ad^ (Equation 16)

[0125] (Equation 17)

[0126] d(M} = r{M}+ d^ (Equation 18).

[0127] The flowchart in [Fig.2] illustrates the process implemented for the numerical solution of the process of the present invention as presented, using the finite element approximation.

[0128] Parallelization of the code developed to implement the process of the present invention

[0129] To reduce the computation time of the simulation process for calculating the coverage effect, the most critical sections of the code were parallelized. The code was parallelized using the OpenMP library, which was integrated into the methodology presented.

[0130] Parallelism was implemented in two stages, to optimize the stages to which most of the processing time is devoted:

[0131] First, the calculation and assembly of the global matrices of the FEM are parallelized.

[0132] In the second step, the solution of the linear system of the heat transport problem is parallelized, more precisely, the multiplication of the global matrix in a sparse format within the iterative process of the PGC.

[0133] The parallelization of the entire system and the evaluation of the global matrices of the FEM were performed using a disjoint division of the finite element mesh. This strategy is essential for efficient code parallelization, without critical concurrency issues and without the need to create mutex-type locks.

[0134] Because of the mesh structure of the FEM mesh used in the process, the division was easily achieved by simply subdividing the vertical layers into even and odd layers, as shown in [Fig.1 1], which illustrates the division of the finite element mesh. Results of the process of the present invention

[0135] Using the process of the present invention, the following results are obtained, which can be used directly or as input for subsequent steps in the modeling of petroleum systems, as shown in Table 2 below.

[0136] Table 2: 1D, 2D and 3D results obtained from the process of the present invention Basement temperature (°C) Basin surface temperature (°C) Basement heat flux (mW / m²) Basin surface heat flux (mW / m²) Sedimentary thickness (m) Sedimentation rate (m / Mya) Effective elastic thickness - Te (m) Temperatures in each sedimentary layer (°C) Heat flux in each sedimentary layer (mW / m²) Moho heat flux (mW / m²) Moho temperature (°C) Isothermal depth maps (m) Paleobathymetry maps (m) Sedimentary layer depth maps at each depositional time (m) Basement restoration maps (depth) (m)

[0137] In addition, conventional results are generated in the form of maps of the region under study, such as the examples shown in [Fig. 12a], [Fig. 12b], [Fig. 12c], and [Fig. 12d]. [Fig. 12a] shows heat flux maps for all weather conditions. of sedimentary deposits. Figure 12b illustrates maps of effective elastic thickness (Te) as a function of temperature. Figure 12c presents paleogeometries of the basement and sedimentary layers. Figure 12d shows a graph with heat flux results: reduction in heat flux in the upper and lower parts of the basin (Qs and Qb), using the cover effect, in comparison with the traditional Jarvis & McKenzie model (Jarvis, GT, McKenzie DP, 1980; DP; "Sedimentary Basin Formation with Finite Extension Rates", Earth and Planetary Science Letters, 48, pp. 42-52).

[0138] Fig. 13a, Fig. 13b, Fig. 13c, Fig. 13d, Fig. 13e and Fig. 13f show some examples of heat flux results obtained from the implementation of the method of the present invention.

[0139] The thermal calculation without the cover effect results in the very simplified heat flux profile of [Fig. 13c], varying only according to the collapse process defined for the basin and no additional detail is observed in the thermal characteristics of the region under study.

[0140] When the cover effect is coupled, when the effect of the sedimentation rate and the sedimentary deposition process are taken into account ([Fig. 13a]), more detail is observed in the resulting heat flux profiles ([Fig. 13b], [Fig. 13d], [Fig. 13e], [Fig. 13f]). In these examples, variations in the heat profiles are observed due to the use of different sediment conductivity values, which is the main characteristic of the cover effect. Advantages and application of the present invention

[0141] The present invention proposes the integration of the blanket effect in the quantification of temperature and heat flux in sedimentary basins and is relevant in regions where sedimentary thicknesses exceed 3 km, thermal conductivities are less than 3.5 W / m / K, and sedimentation rates are greater than 200 m / Mya. Furthermore, variations in thermophysical properties resulting from salt deposition and compaction contribute to variations in the thermal structure of the region under study.

[0142] In this context, the application of the proposed method, through the use of a 3D model, which has the capacity to capture geological differences in a large area, will provide more accurate results with greater resolution and detail on a regional scale.

[0143] As an example, according to studies conducted in the proximal portion of the Santos Basin, it is estimated that the heat flux in the basement is reduced by 36% compared with models without the application of the cover effect presented in this document, given that sedimentation rates are high (approximately 200 m / Mya) in regions where the pre-salt and post- salt deposits are approximately 3.5 km and 4 km, respectively. In the distal portion of the Santos basin, where the thicknesses of the pre-salt and post-salt deposits are less than 1.5 km and the salt deposit thickness varies between 3 and 5 km, the cover effect is not significant, with a difference of approximately 2% being observed compared to the traditional extended collapse model.

[0144] In practice, the method described in this document has already been applied to analyses of basins such as Santos / Campos, Pelotas, the equatorial margin, Foz do Amazonas, and Namibia, providing excellent results for heat flow and temperatures. These results, obtained in the form of 3D maps, were compared with well data, with respect to paleotemperatures and vitrinite reflectances, and showed very good calibration. Tools used

[0145] The method for calculating the hedging effect in the modeling of petroleum systems of the present invention, implemented by means of a computer program, includes the following tools in a computer program environment to enable the use thereof: a numerical simulator with optimization of computation time; and a graphical interface for data input, execution of the numerical simulator and obtaining results.

[0146] The numerical simulator is responsible for coupling lithospheric events with sedimentary processes (cover effect) that were not previously quantified in the thermal calculation of the basin. With this, simulations carried out in simulation applications begin to quantify the transient thermal effect related to the deposition and compaction of cold sediments, known as the cover effect, integrating it with other processes existing in the model, such as the evolution of the geothermal gradient, lithospheric stretching (collapse) and radiogenic heat present in the upper portion of the crust.

[0147] A graphical interface can be specifically designed to allow the use of the method of the present invention, which is easy and intuitive to use. For example, a graphical interface can be developed to apply the algorithms that define the proposed sequence of processes, allowing the input of a large amount of data and the provision of results with a high level of detail on a regional scale, for the areas under study.

[0148] The method for calculating the cover effect in petroleum system modeling of the present invention produces improved results, with the coupling of lithospheric events with sedimentary processes (cover), which were not previously quantified in the thermal calculation of the basin. In other words, the simulations carried out in the simulation programs began to quantify the transient thermal effect linked to the deposition and compaction of cold sediments, known as the covering effect, integrating this with other processes existing in the model, such as the evolution of the geothermal gradient, lithospheric stretching (collapse) and radiogenic heat present in the upper portion of the crust.

[0149] This process, known as the blanket effect, filled one of the important gaps that were missing for the refinement of the thermal calculation of sedimentary basins. Graphical interface developed in C++ / QT

[0150] The digital simulator and the graphical interface can be developed in the C++ and QT languages, respectively, in addition to the use of public domain libraries, such as OpenMP, to optimize computation time, among other things.

[0151] To start the process, it is necessary to choose the type of simulation (“thermal” or “3D backstripping + thermal”) in the graphical interface.

[0152] The graphical interface developed in C++ / QT allows the application of the method of the present invention to real-world basin scenarios and the presentation of results in the form of heat flux and temperature maps. The graphical interface is designed and implemented specifically for the implementation of the method of the present invention and allows the development of thermomechanical models for basin simulation in an intuitive manner, presenting results with a high level of detail in the form of text files, which can be imported into visualization tools.

[0153] In addition, the present invention relates to a computer-readable storage medium, which includes, stored therein, a set of computer-readable instructions, in which, when the set of computer-readable instructions is executed by one or more processors, one or more processors implement the method of the present invention, as described above.

[0154] In particular, the computer-readable storage medium may be memory, in which the memory may be of a non-volatile type, such as a hard disk drive (HDD) or a solid-state drive (SSD), or it may be volatile memory, such as random access memory (RAM). Furthermore, the readable storage medium may be any other means or medium that can carry, store, or record the intended program code in the form of an instruction, a data structure, or a set of instructions, and which may be accessed by one or more computers or one or more processors, but it is not limited to this. Alternatively, the readable storage medium may be a circuit or any other device or means that can implement a storage, transport or recording function, such as a signal or carrier.

[0155] Specifically, the set of computer-readable instructions represents the algorithm or computer program code or data structure that implements the process of the present invention as described above.

[0156] The processor may be a general-purpose processor, which may be a microprocessor or any conventional or similar processor.

[0157] A person skilled in the art will appreciate the teachings presented in this document and will be able to reproduce the invention in the embodiments presented and in other variations, encompassed by the scope of the attached claims.

Claims

Demands

1. A computer-implemented method for integrating the blanket effect into the quantification of temperature and heat flux in a sedimentary basin for petroleum system modeling, characterized in that it comprises the steps of: obtaining input lithospheric and sedimentary data (1); the discretization of the model differently in the sedimentary domain and in the lithospheric domain (2); the start of the calculation of the hedging effect (3); checking whether the deposition time corresponding to each sedimentary layer (t) is greater than the present time and whether the age of the basin is greater than the deposition time corresponding to each sedimentary layer (t) (4), refraining from carrying out the process (5); the verification of whether the deposition time corresponding to each sedimentary layer (t) is less than or equal to the present time and whether the age of the basin is less than or equal to the deposition time corresponding to each sedimentary layer (t) (4) and the verification of whether it is in the collapse period (6), in which: if it is in the collapse period, the calculation of the collapse (7); if it is not in the collapse period, or if it is in sequence with respect to the collapse calculation step (7), the calculation of sedimentation (8); the calculation of the advective vertical displacement velocity due to collapse (9) for each XY coordinate; the calculation of fluid flow (10); the use of finite elements to perform the calculation at each instant in time (11); the realization of the addition of the thermal effect of the lithospheric and sedimentary domains at each time step (12); the provision of heat flow and temperature results.

2.

3. A method according to claim 1, characterized in that the lithospheric and sedimentary data comprise at least one of: • dimensions of the area; • Thermophysical parameters, such as: crustal conductivity (W / m / K); crustal density (kg / m³); crustal specific heat (J / kg / K); crustal radiogenic heat (qW / m³); lithospheric mantle conductivity (W / m / K); lithospheric mantle density (kg / m³); lithospheric mantle specific heat (J / kg / K); lithospheric mantle radiogenic heat (qW / m³); water density (kg / m³); water conductivity (W / m / K); water specific heat (J / kg / K); asthenosphere density (kg / m³); elasticity coefficient (N / m²); Poisson's ratio; coefficient of thermal expansion (1 / °C); acceleration due to gravity (m / s²); isothermal temperature for Te (°C); • boundary conditions in the lithosphere, such as surface temperature and core temperature; • lithospheric data, corresponding to the number of layers and the thermophysical properties of the layer, including at least one of: thickness (m); density (kg / m3); specific heat (J / kg / K); conductivity (W / m / K); radiogenic heat (W / m3*le-6); • Horizon and lithofacies maps for each sedimentary layer; in which salt and igneous maps are optional, depending on the region of interest; • values ​​for the discretization of the numerical model; • age of the pelvis (in millions of years - mya.); • time and period of the collapse (in millions of years - mya.); • values ​​or maps of the stretching factors of the lithosphere (|3) or of the crust and mantle (δ and P)- A method according to claim 1, characterized in that, if it is in the collapse period, the calculation of the collapse (7) includes the calculation of transient heat due to lithospheric thinning, which causes variations in the heat flux, from the advective thermal model:

3. + (pr)(0) VxcQ where: vs denotes the velocity of solid particles; 0 is the porosity; g is the density; c is the decay constant; and A is the conductivity; • the calculation of the value of the crust ô and the value of the mantle [3 within the collapse, according to: fi = • the calculation of the thicknesses and horizons of the sediment layers as a function of the value of the crust ô and the value of the mantle [3; • the quantification of radiogenic heat in the upper portion of the crust.

4. A method according to claim 1, characterized in that the calculation of sedimentation (8) includes the calculation of the covering effect due to sediment deposition, by means of an advective model, comprising: • the backstripping of sediment layers; • the stacking and compaction of sediment layers up to the corresponding deposition time and according to the thermal parameters recalculated at depth; • the recalculation of the depth of the basement; • the calculation of the radiogenic heat in the sedimentary portion.

5. A method according to claim 1, characterized in that the calculation of the advective vertical displacement velocity due to collapse (9), for each XY coordinate, involves calculation using the formulation vbulk = G*(hz) for each vertical z coordinate, where vbulk = average velocity of the asthenosphere's uplift due to collapse, varying linearly in z; G = magnitude of the vertical velocity gradient along the lithosphere h, indicating how much the fluid velocity (asthenosphere) moves vertically along the thickness defined by "h" in the formulation; h = depth limit of the lithosphere; further including the addition of advective velocities to the sedimentation velocity, in which the greater the compaction, the slower the uplift due to collapse.

6. Method according to claim 1, characterized in that the calculation of the fluid flow (10) includes the definition of thermal properties in the nodes of the 3D digital mesh, comprising at least one of conductivity, radiogenic heat, density*specific heat of the solid part (hc_bulk), density*specific heat of the fluid part (hc_water).

7. A method according to claim 1, characterized in that it further comprises the step of generating outputs for the corresponding deposition time (13), comprising the generation of maps, sections and well profiles with thermal and structural information of the sedimentary basin.

8. A computer-readable storage medium, characterized in that it comprises, stored therein, a set of computer-readable instructions, which, when executed by a computer, carry out the method according to any one of claims 1 to 7.

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