Systematic prediction of the gas content, fractures, and brittleness in fractured shale reservoirs with TTI medium

The main objective is to optimize the development of shale gas-rich areas by predicting seismic sweet spot parameters in shale reservoirs. We systematically assessed the fracture development, fracture gas content, and rock brittleness in fractured gas-bearing shale reservoirs. To better characterize gas-bearing shale reservoirs with tilted fractures, we optimized the petrophysical modeling based on the equivalent medium theory. Based on the advantages of shale petrophysical modeling, we not only considered the brittle mineral fraction but also the combined effect of shale porosity, gas saturation, and total organic carbon(TOC) when optimizing the brittleness index. Due to fractures generally functioning as essential channels for fluid storage and movement, fracture density and fracture fluid identification factors are critical geophysical parameters for fractured reservoir prediction. We defined a new fracture gas indication factor(GFI) to detect fracture-effective gas content. A new linear PP-wave reflection coefficient equation for a tilted transversely isotropic(TTI) medium was rederived, realizing the direct prediction of anisotropic fracture parameters and the isotropic elasticity parameters from offset vector tile(OVT)-domain seismic data. Synthetic seismic data experiments demonstrated that the inversion algorithm based on the L_P quasinorm sparsity constraint and the split-component inversion strategy exhibits high stability and noise resistance. Finally, we applied our new prediction method to evaluate fractured gas-bearing shale reservoirs in the Sichuan Basin of China, demonstrating its effectiveness.

A study of wavelet transforms applied for fracture identification and fracture density evaluation

Combining wavelet transforms with conventional log differential curves is used to identify fractured sections is a new idea.In this paper,we first compute the mother wavelet transform of conventional logs and the wavelet decomposed signals are compared with fractures identified from image logs to determine the fracture-matched mother wavelet.Then the mother wavelet-based decomposed signal combined with the differential curves of conventional well logs create a fracture indicator curve,identifying the fractured zone.Finally the fracture density can be precisely evaluated by the linear relationship of the indicator curve and image log fracture density.This method has been successfully used to evaluate igneous reservoir fractures in the southern Songnan basin and the calculated density from the indicator curve and density from image logs are both basically consistent.

Estimation of fracture density and orientation from azimuthal elastic impedance difference through singular value decomposition

Accurate estimation of fracture density and orientation is of great significance for seismic characterization of fractured reservoirs.Here,we propose a novel methodology to estimate fracture density and orientation from azimuthal elastic impedance(AEI)difference using singular value decomposition(SVD).Based on Hudson's model,we first derive the AEI equation containing fracture density in HTI media,and then obtain basis functions and singular values from the normalized AEI difference utilizing SVD.Analysis shows that the basis function changing with azimuth is related to fracture orientation,fracture density is the linearly weighted sum of singular values,and the first singular value contributes the most to fracture density.Thus,we develop an SVD-based fracture density and orientation inversion approach constrained by smooth prior elastic parameters.Synthetic example shows that fracture density and orientation can be stably estimated,and the correlation coefficient between the true value and the estimated fracture density is above 0.85 even when an S/N ratio of 2.Field data example shows that the estimated fracture orientation is consistent with the interpretation of image log data,and the estimated fracture density reliably indicates fractured gas-bearing reservoir,which could help to guide the exploration and development of fractured reservoirs.

An intelligent prediction method of fractures in tight carbonate reservoirs

An intelligent prediction method for fractures in tight carbonate reservoir has been established by upgrading single-well fracture identification and interwell fracture trend prediction with artificial intelligence,modifying construction of interwell fracture density model,and modeling fracture network and making fracture property equivalence.This method deeply mines fracture information in multi-source isomerous data of different scales to reduce uncertainties of fracture prediction.Based on conventional fracture indicating parameter method,a prediction method of single-well fractures has been worked out by using 3 kinds of artificial intelligence methods to improve fracture identification accuracy from 3 aspects,small sample classification,multi-scale nonlinear feature extraction,and decreasing variance of the prediction model.Fracture prediction by artificial intelligence using seismic attributes provides many details of inter-well fractures.It is combined with fault-related fracture information predicted by numerical simulation of reservoir geomechanics to improve inter-well fracture trend prediction.An interwell fracture density model for fracture network modeling is built by coupling single-well fracture identification and interwell fracture trend through co-sequential simulation.By taking the tight carbonate reservoir of Oligocene-Miocene AS Formation of A Oilfield in Zagros Basin of the Middle East as an example,the proposed prediction method was applied and verified.The single-well fracture identification improves over 15%compared with the conventional fracture indication parameter method in accuracy rate,and the inter-well fracture prediction improves over 25%compared with the composite seismic attribute prediction.The established fracture network model is well consistent with the fluid production index.

Fracture characterization of Asmari Formation carbonate reservoirs in G Oilfield, Zagros Basin, Middle East

The Asmari Formation in the G oilfield on the Iran-Iraq border is a fractured-porous multi-lithology mixed reservoir, for which fracture is an important factor affecting oil productivity and water cut. The characterization and modeling of fractures in the carbonate reservoir of G oilfield are challenging due to weak conventional well log responses of fractures and a lack of specific logs, such as image logs. This study proposes an integrated approach for characterizing and modeling fractures in the carbonate reservoir. The features, formation mechanism, influencing factors, and prediction methods of fractures in the Asmari Formation carbonate reservoirs of G oilfield were studied using core observation, thin section, image log, cross-dipole acoustic log (CDAL), geomechanics numerical simulation (GNS), and production data. According to CDAL-based fracture density interpretation, GNS-based fracture intensity prediction between wells, and DFN-based rock fracture properties modeling, the quantitative fracture characterization for G oilfield was realized. This research shows that the fractures in the Asamri Formation are mainly medium-to high-angle shear fractures. The substantial compression stress during the Miocene played a major role in the formation of the prominent fractures and determined their trend in the region, with primary trends of NNW-SSE and NNE-SSW. The fracture distribution has regularity, and the fractures in zone A dolomites are more highly developed than that in zone B limestones vertically. Horizontally, fractures intensity is mainly controlled by faults and structural location. The results of this study may benefit the optimization of well design during field development. From 2019 to 2021, three horizontal wells pilot tests were deployed in the fractures belt in zone A, and these fractures prominently increased the permeability of tight dolomite reservoirs. The initial production of the wells is four to five times the average production of other wells in the area, showing a good development effect. Meanwhile, the updated numerical simulation validates that the history match accuracy of water cut based on the dual-porosity model is significantly improved, proving the fracture evaluation and prediction results to be relatively reliable and applicable.

Estimation of 2-D and 3-D Fracture Densities from 1-D Data-Experimental and Field Results

2-D and 3-D densities of fractures are commonly used in mining safety design, natural gas and oil production in fractured reservoirs, and the characterization of subsurface flow and transportation systems in fractured rocks. However, many field data sets are collected in 1-D frequency (f) (e.g., scanlines and borehole data). We have developed an ARC/ INFO-based technology to calculate fracture frequency and densities for a given fracture network. A series of numerical simulations are performed in order to determine the optimal orientation of a scanline, along which the maximum fracture frequency of a fracture network can be obtained. We calculated the frequency (f) and densities (both D1 and D2) of 36 natural fracture trace maps, and investigated the statistical relationship between fracture frequency and fracture density D1, i.e. D1=1.340f+ 0.034. We derived analytical solutions for converting dimensional density (D1) to non-dimensional densities (D2 and D3) assuming that fracture length distribution follows an exponential or power law. A comparison between observed and calculated results based on the equations we developed shows that (1) there exists a linear relationship between fracture frequency and fracture density (D1), and this relationship can be used to estimate fracture density (D1) if the fracture frequency is determined from a scanline survey or from borehole data; (2) the analytical solutions we derived can accurately determine the non-dimensional 2-D fracture density (D2) in practice and 3-D fracture density (D3) in theory if the fracture length distribution function is assumed.

Characterization of Complex Fracture System in Volume Fracturing of Shale Gas Reservoir

After volume fracturing of horizontal wells in shale gas reservoir, an extremely complex fracture system is formed. The space area of the fracture system is the reservoir reconstruction volume of shale gas reservoir. The geometric parameters such as crack length, crack width, crack height, and characteristic parameters such as crack permeability and fracture conductivity proposed for a single crack in conventional fracturing are insufficient to describe and characterize the complex network fracture system after volume fracturing. In this paper, the discrete fracture modeling method is used to establish the volume fracturing network fracture model of horizontal wells in shale gas reservoir by using the random modeling method within the determined reservoir space. The model is random and selective, and can fully provide different forms of volume fracturing fracture expansion, such as conventional fracture morphology, line network model and arbitrarily distributed network fractures. The research results provide a theoretical basis for the development plan and stimulation plan of shale gas reservoir, and have important reference value and significance for other unconventional gas reservoir fracturing.

Tensile properties of phase interfaces in Mg Li alloy: A first principles study

Employing density functional theory, we study the tensile and fracture processes of the phase interfaces in Mg–Li binary alloy. The simulation presents the strain–stress relationships, the ideal tensile strengths, and the fracture processes of three phase interfaces. The results show that the α/α and α/β interfaces have larger tensile strength than that of β/β interface. The fractures of both α/α and β/β interfaces are ductile fractures, while the α/β fractures abruptly._Further analyses show that the fracture of the α/β occurs at the interface.

Loss of bone mass after Colles’ fracture: a follow-up study

Background Colles’ fracture usually associated with osteoporosis is regarded as the predictor of subsequent osteoporotic fracture. However, it is not clear how the local changes of bone mass take place during the course of treatment and whether the changes are related to clinical practice. The objective of the current study was to investigate the local changes of bone mass in patients with Colles’ fractur e and their possible clinical relevance in a follow-up study.Methods The radiograms of the second metacarpal in 64 patients with Colles’ fracture were assessed for bone density immediately after fracture, 6 weeks, 6 months and 1 year after fracture, respectively. Functional results were evaluated at one year.Results Bone mass six weeks after Colles’ fracture was signifi cantly decreased without returning to normal at one year though increased bone mass had been identified 6 months after fracture (P< 0.05), (P< 0.01). At one year significant (P< 0.05) or highly significant (P< 0.01) correlations were observed between bo ne mass indices of metacarpal and functional results, indicating that poor function is associated with lower bone density. Significant differences (P< 0.05) between fracture patterns also suggested that patients with more severe fractures have a more pronounced bone loss.Conclusions Bone loss during the course of treatment will have a direct effect upon the prognosis, so different treatment should be proposed for different patterns of fractures. Active exercise should be made to improve the recovery of bone mass.

Amplitude variation with offset and azimuth inversion to predict and evaluate coal seam fracture parameters

Amplitude variation with offset and azimuth(AVOA)inversion is a mainstream method for predicting and evaluating fracture parameters of conventional oil and gas reservoirs.However,its application to coal seams is limited because of the specificity of the equivalent media model for coal—also,the traditional seismic acquisition system employed in coal fields falls within a narrow azimuth.In this study,we initially derived a P‒P wave reflection coefficient approximation formula for coal seams,which is directly expressed in terms of fracture parameters using the Schoenberg linear-slide model and Hudson model.We analyzed the P‒P wave reflection coefficient’s response to the fracture parameters using a two-layer forward model.Accordingly,we designed a twostep inversion workflow for AVOA inversion of the fracture parameters.Thereafter,high-density wide-azimuth pre-stack 3D seismic data were utilized for inverting the fracture density and strike of the target coal seam.The inversion accuracy was constrained by Student’s tdistribution testing.The analysis and validation of the inversion results revealed that the relative fracture density corresponds to fault locations,with the strike of the fractures and faults mainly at 0°.Therefore,the AVOA inversion method and technical workflow proposed here can be used to efficiently predict and evaluate fracture parameters of coal seams.