Boriding is a widely used thermochemical treatment to improve surface hardness and wear resistance in steels used in demanding mechanical applications. However, boronizing processes using new boron paste increase costs and generate waste, creating a need for more sustainable alternatives. In this context, the reuse of dehydrated boron paste has proven effective in the formation of Fe₂B layers on AISI 9254 steel. In this study, AISI 9254 steel was boronized using reused dehydrated boron paste at 1173 K, 1223 K, and 1273 K for 3600, 7200, 10,800, and 14,400 s. Optical microscopy revealed layer thicknesses ranging from 16.07 $\mathsf{\mu }\mathrm{m}$ to 69.35 $\mathsf{\mu }\mathrm{m}$ X-ray diffraction confirmed the formation of single-phase Fe₂B, while EDS indicated elemental redistribution within the layer. The Vickers microhardness profile characterized the mechanical behavior, and the adhesion force showed HF1-HF2 ratings. The activation energy for boron diffusion in Fe₂B was calculated at 106.567 kJ ${\mathrm{mol}}^{-1}$. Auto-affine analysis verified the fractal nature of interface growth, with a scale $\omega \left(d\right)$ according to $\omega \left(\delta \right)\sim {\delta }^H$. These results confirm that reused paste allows the formation of Fe₂B layers, supporting sustainable boronization strategies with controlled interfacial evolution.

This study evaluates flow capacity fluctuations in well cores from a southeastern Mexico formation using pdpk records. Petrophysical measurements provide wellbore wall flow capacity data, used to identify trends. Applying a dynamic scaling approach akin to the Family-Vicsek method, we analyze discrete kh* records. In particular, the order parameter structure function q was applied to the flow capacity records, and the exponents characterizing dynamic scaling α, β, z were identified, revealing self-affine scalings for fluctuations. Data collapse of flow capacities occurs in the northern zone with higher fractures and oil production, contrasting with the poorly collapsed flow capacity in the southern zone. This suggests superior flow capacity in fractal reservoir media compared to Euclidean counterparts.

This study focuses on a hydrocarbon reservoir located in southeastern Mexico. The analysis uses well log data derived from petrophysical evaluations of storage capacity. The structural complexity of the reservoir and observed heterogeneity in Cretaceous units motivate a fractal-based characterization of spatial fluctuations. The objective is to assess the fractal scaling of storage capacity fluctuations using the Family–Vicsek dynamic framework. Critical exponents α (roughness), β (growth), and z (dynamic) are obtained through structure function metrics. Data collapse techniques and local Hurst exponent distributions are used to explore long-range memory and spatial heterogeneity across wells. This study aims to classify storage capacity fluctuation records based on Euclidean or fractal geometries. This analysis allows a novel characterization of storage trends in the reservoir. The analysis reveals persistent scaling behavior, indicating long-range correlations in the storage capacity fluctuations. Multiscale patterns and variations in local Hurst exponents highlight the presence of multifractality and regional heterogeneity. Specifically, the spatial distribution of local Hurst exponents obtained in this study enables the inference of statistical properties in synthetic wells, providing key input for the structural and functional characterization of the reservoir’s geological model. This approach aims to identify preferential subsurface flow pathways for hydrocarbons, gas.

In this study we explore the application of the novel fractional calculus in fractal continuum (FCFC), together with the finite element method (FEM), in order to analize explicitly how these differential operators act in the process of discretizing the generalized fractional pressure diffusion equation for a three-dimensional anisotropic continuous fractal flow. The master finite element equation (MFEE) for arbitrary interpolation functions is obtained. As an example, MFEE for the case of a generic linear tetrahedron in $\mathbb{R}^3$ is shown. Analytic solution for the spatial variables is determined over a canonical tetrahedral finite element in global coordinates.

This study focuses on a hydrocarbon reservoir located in southeastern Mexico. The analysis uses well log data derived from petrophysical evaluations of storage capacity. The structural complexity of the reservoir and observed heterogeneity in Cretaceous units motivate a fractal-based characterization of spatial fluctuations. The objective is to assess the fractal scaling of storage capacity fluctuations using the dynamic Family–Vicsek framework. Critical exponents $\alpha$ (roughness), $\beta$ (growth), and z (dynamic) are obtained through structure function metrics. Data collapse techniques and local Hurst exponent distributions are used to explore long-range memory and spatial heterogeneity across wells. This study aims to classify storage capacity fluctuation records based on Euclidean or fractal geometries. This analysis allows a novel characterization of storage trends in the reservoir. The analysis reveals persistent scaling behavior, indicating long-range correlations in the storage capacity fluctuations. Multiscale patterns and variations in local Hurst exponents highlight the presence of multifractality and regional heterogeneity. Specifically, the spatial distribution of local Hurst exponents obtained in this study enables the inference of statistical properties in synthetic wells, providing key input for the structural and functional characterization of the reservoir’s geological model. This approach aims to identify preferential subsurface flow pathways for hydrocarbons and gas.