Research on the Inversion Method and Application of Random Mechanical Parameters for Arch Dam and Its Nearby Mountain Structure

First, prior distribution of the mechanical parameters of arch dam body and its nearby mountain rock mass was determined according to the meso-modelling of dam concrete and test data of its nearby mountain rock mass, and a finite element model of the arch dam and its nearby mountain was established. Based on Bayesian theory, random inversion objective function was established. Afterwards, inversion analysis of mechanical parameters was conducted with Differential Evolution Adaptive Metropolis (DREAM(SZ)) on the basis of Markov chain random theory, for the inversion of random distribution parameters of the elasticity modulus of dam concrete and overall deformation modulus. This method was applied to some high-arch dam project, and it was verified to be effective by the results.

Inversion Analysis of Seepage Parameters Based on Improved Shuffled Frog Leaping Algorithm

Aiming at overcoming the defects such as slow searching speed and easily trapping into local extremum at anaphase of the shuffled frog leaping algorithm (SFLA), based on the Evolutionary Exploration strategy, a more effective shuffled frog leaping algorithm, Improved Shuffled Frog Leaping Algorithm (ISFLA), which can be applied to the inverse analysis of seepage parameters to dams, is proposed. With the introduction of the threshold value selection in the local search of the original initial population to improve the best frogs in memeplex, the improved algorithm overcomes the shortcomings of traditional SFLA which can easily fall into a local optimum. By comparative analysis between the laboratory test and numerical simulation, the effectiveness and accuracy of ISFLA are demonstrated by the application to the inversion analysis of seepage parameters of earth dams. Furthermore, the inversion analysis of seepage parameters to the earth dam in Lianyungang China is studied by the ISFLA. Moreover, the seepage characteristics of the dam are evaluated; thus, the suggestion that the dam should be reinforced is put forward. All the results show that ISFLA in an inverse analysis of seepage parameters of dams has excellent value to hydropower engineering.

Integration of sequence stratigraphy, rock physics and AI inversion to determine the prospective reservoir in the shelf environment of the Tarakan Basin, Indonesia

The Tarakan Basin is one hydrocarbon basin in Indonesia with approximately 40 discoveries and more than 1000 MBOE reserves. This study discusses an approach to integrate the sequence stratigraphy, rock physics and acoustic impedance (AI) inversion analysis to determine the prospective reservoirs in the basin. PRG-1 well data is used in the sequence stratigraphy and rock physic analysis. The sequence stratigraphy analysis of PRG-1 shows that there are three system tracts: transgressive, low stand tract and high stand system tracts. The integration of sequence stratigraphy, rock physics and log data analysis show that the prospective reservoir interval in PRG-1 well is located at a depth of 4730-4780 feet. It is characterized by low gamma ray, low NPHI, low density and high resistivity. The prospective interval was deposited in early Pliocene as Tarakan Formation in the low stand system tract of shelf depositional environment. The AI map shows that the distribution of the prospective is around the PRG-1 and in the eastern part of the area.

New 3-D Combined Inversion Scheme Using Response Functions Free From Galvanic Distortion

The combined inversion using distortion-free response functions is an effective approach to robustly estimate the 3-D electrical resistivity structure against the distortions caused by near-surface resistivity anomalies. However, previous combined inversion analyses have presented a significant dependency of the inversion results on initial and prior models. Therefore, in this study, we evaluated the effectiveness of the following two new types of 3-D combined inversion using distortion-free response functions: one uses the phase tensor and the vertical and inter-station horizontal magnetic transfer functions, while the other uses the Network-MT response functions, in addition to the former. Because long dipoles are used, the Network-MT response function is negligibly affected by galvanic distortion. To access the combined inversion approach, we developed a novel 3-D inversion scheme combining the response functions of the usual magnetotelluric measurements and the Network-MT response function. The synthetic inversion analysis demonstrated that both of the proposed combined inversions can recover the characteristic resistivity distributions of the target model without a significant dependence on the initial models, at least in the shallow part. These results demonstrate that the combined inversions using only distortion-free response functions have the potential to estimate subsurface resistivity more robustly than what was previously thought. Furthermore, we confirmed that the combined inversion using the Network-MT response function can make the resultant resistivity structure closer to the actual one and enhance the stability of the inversion. This result suggests that the combined use of the Network-MT response function is the preferred approach.

1-D inversion analysis of a shallow landslide triggered by the 2018 Eastern Iburi earthquake in Hokkaido, Japan

Destructive landslides were triggered by the 6.7 Mw Eastern Iburi earthquake that struck southern Hokkaido, Japan, on 6 September 2018. In this study, we carried out 1-D inversion analysis of one of the shallow landslides near the epicenter using a Bing debris-flow model. At this site, the slope failure comprised cover soil with an initial down-slope length of ~ 80 m and a thickness of ~ 7 m on a slope with < 20° dip. The landslide moved southeastward with a run-out distance of ~ 100 m. Inversion analysis of the post-failure deposit geometry was conducted with the Markov Chain Monte Carlo method (MCMC) to optimize the Bingham rheological parameters of the debris. The analysis reproduced several features of the deposit geometry with a yield stress of ~ 1500 Pa and dynamic viscosity of 800–3000 Pa s. The results suggest that the shallow landslide can be approximated by the flow of a viscoplastic fluid with high-mobility debris and a maximum frontal velocity of 6–9 m/s, with a flow duration of 2–4 min.

Hydrocarbon Mapping on Reservoir Carbonate Using AVO Inversion Method

Amplitude Versus Offset (AVO) inversion has been applied for reservoir analysis focused on the horizon carbonate Peutu and Belumai. Simultaneous inversion analysis is used to determine gas anomaly inside carbonate-rocks and it’s spread laterally around target zones. It is based on the fact that small Vpand Vs value changes are going to show the better anomaly to identify reservoir fluid content. The AVO inversion method applies angle gather data as the input and then it is inverted to produce P impedance (Zp) and S impedance (Zs). Zp and Zs are derived to produce Lambda-Rho and Mu-Rho that are sensitive to fluid and lithology. Value of Mu-Rho between 44–65 Gpa gr/cc while value of Lambda-Rho smaller than 10 Gpa gr/cc (for carbonate-rock filled by fluid). This research found that Lambda-Rho is the best parameter to show the existence of hydrocarbon in the case of gas. While Mu-Rho is the best parameter to show the differences in lithology.