Zhang Jinliang

Fine description of structure and sedimentary microfacies of Li32 block of Lijin oilfield, Dongying depression, China

Considering that available data in Li32 block is limited, log phase method and core analysis were used to divide sedimentary facies and sequence, the former is principal, and two short-term cycles, five middle term cycles, and fifteen short-term cycles were divided. Combined seismic interpretation with fault point and fault rod, the instantaneous phase profile explained small fault more clearly and accurately. The sever faults were analyzed, and integrated structure was constructed. Lithofacies in cored wells were observed; the grain-size probability curves mainly are suspension and jumping transport; grain size is mainly for the siltstone and fine sandstone; the color of mud in the second segment of Shahejie formation (ES2) is mainly gray–green, gray to dark gray, these reflect that sediment environment is delta front, which included underwater distributary channel, mouth bar, distal bar, and so on. Well data and structural maps were integrated to build 3D structure model and sedimentary microfacies model of Li32 reservoirs using stochastic simulations with geometry data. The integrated 3D geological model is a valuable tool of reflecting geologic body with great reality and can accurately represent and describe the complex reservoir heterogeneity.

Based on Wavelet-Boltzman Neural Network and Kernel Density Estimation Model Predict International Crude Oil Prices

International crude oil prices are very complex nonlinear time series, which are not only affected by the domination of objective economic laws, but also by politics and other factors. Therefore it is difficult to establish an effective prediction model based on the general time series analysis. In this paper, based on wavelet transform, the international oil prices time series is decomposed into approximate components and random components. The approximate components, which represented the trend of oil price, are predicted with Boltzmann neural network; the random components are predicted with Gaussian kernel density estimation model. In this paper, we analyzed the time-frequency structure of dubieties wavelet transform coefficient modulus for crude oil price time series, and predicted the oil price with Boltzmann neural network and Gaussian kernel density estimation model.The results show that the model has higher prediction accuracy.

Diagenesis and Diagenetic Evolution of Deltaic and Neritic Gas‐Bearing Sandstones in the Lower Mingyuefeng Formation of Paleogene, Lishui Sag, East China Sea Shelf Basin: Implications for Depositional Environments and Sequence Stratigraphy Controls

Gas-bearing deposits in the Lower Mingyuefeng Formation of Paleogene, Lishui Sag, East China Sea Shelf Basin consist of shoreface sandstones of the highstand systems tract (HST) and transgressive systems tract (TST), and deltaic sandstones of the lowstand systems tract (LST) and falling stage systems tract (FSST). Detailed petrographic observations suggest that the diagenetic features and related evolution of these deposits cannot be simply characterized and demonstrated in the depth domain. However, the occurrence of diagenetic minerals systematically depends on the studied interval within the HST, TST, LST, and FSST; therefore, diagenesis in this region can be better constrained when studied in the context of the depositional environments and sequence stratigraphic framework. The eogenetic processes in such settings include: (1) microcrystalline siderite precipitated as concretions in almost all environments and systems tracts, which inhibited further mechanical compaction; (2) grain dissolution and kaolinitization occurred in shoreface HST sandstones and deltaic LST and FSST sandstones; (3) glaucony was locally observed, which did not clearly reflect the controls of facies or sequence stratigraphy; and (4) cementation by pyrite aggregates occurred in the shoreface HST sandstones and deltaic LST sandstones. The mesogenetic diagenesis includes: (1) partial conversion of kaolinite into dickite in deltaic LST sandstones, and minor chlorite cementation in deltaic FSST sandstones; (2) transformation of kaolinite into illite and quartz cementation in deltaic LST and FSST sandstones; (3) frequent precipitation of ankerite and ferroan calcite in shoreface TST sandstones and early HST sandstones, forming baffles and barriers for fluid flow, with common calcite in shoreface HST sandstones as a late diagenetic cement; and (4) formation of dawsonite in the deltaic LST and FSST sandstones, which is interpreted to be a product of the invasion of a CO2-rich fluid, and acts as a good indicator of CO2-bearing reservoirs. This study has thus constructed a reliable conceptual model to describe the spatial and temporal distribution of diagenetic alterations. The results may provide an entirely new conceptual framework and methodology for successful gas exploration in the continental margins of offshore China, thus allowing us to predict and unravel the distribution and quality evolution of clastic reservoirs at a more detailed and reliable scale.

Fracture modelling based on the stochastic extended finite element method

Because a large number of oil and gas reservoirs are naturally fractured, they play an important role in hydrocarbon exploration and production. To fully extract and model the fracture system features of reservoirs, a new fracture modelling method, called the stochastic extended finite element (SEFE) method, is presented in this paper. This method couples fracture mechanics and the kriging method with a multi-field trend in an attempt to benefit from the advantages of each method: compliance with fracture mechanics equations and the reproduction of the fracture’s observed data, respectively. Based on the SEFE simulation method, we wrote a fracture modelling system software and built a fracture propagation model and a fracture distribution model of the Upper Cretaceous Formation in the Daqingzi region. A parallel study was performed to verify the fracture propagation pattern and boundary conditions in the proposed model based on a geomechanical analogue experiment. The results of these studies demonstrate that fracture modelling based on the SEFE method may improve the precise characterization of fractured reservoirs.

Notice of Retraction Effects simulation of international natural gas prices on crude oil prices based on WBNNK model

International crude oil prices are very complex nonlinear time series, which are not only affected by the domination of objective economic laws, but also by politics and pricing system. Therefore it is difficult to establish an effective prediction model based on the general time series analysis. So we need to understand the effects of international natural gas prices on crude oil prices to get more accuracy prediction of crude oil prices. In this paper, we build up WBNNK (wavelet-based Boltzmann cooperative neural network and kernel density estimation) model. The international natural gas ad crude oil prices time series is decomposed into approximate components and random components. International natural gas prices could affect the entire world pricing system. The approximate components, which represented the trend of oil price, are predicted with Boltzmann neural network, which is cooperative with international natural gas prices; the random components are predicted with Gaussian kernel density estimation model. In this paper, we analyzed the time-frequency structure of dubieties wavelet transform coefficient modulus for crude oil price time series, and predicted the oil price with Boltzmann neural network and Gaussian kernel density estimation model. The results show that the model has higher prediction accuracy.

Effects simulation of international gold prices on crude oil prices based on WBNNK model

International gold prices could affect the entire world pricing system. And as International crude oil prices are very complex nonlinear time series, which are not only affected by the domination of objective economic laws, but also by politics and pricing system. Therefore it is difficult to establish an effective prediction model based on the general time series analysis. So we need to understand the effects of international gold prices on crude oil prices to get more accuracy prediction of crude oil prices. In this paper, we build up WBNNK (wavelet-based Boltzmann cooperative neural network and kernel density estimation) model. The international gold ad crude oil prices time series is decomposed into approximate components and random components. The approximate components, which represented the trend of oil price, are predicted with Boltzmann neural network, which is cooperative with international gold prices; the random components are predicted with Gaussian kernel density estimation model. In this paper, we analyzed the time-frequency structure of dubieties wavelet transform coefficient modulus for crude oil price time series, and predicted the oil price with Boltzmann neural network and Gaussian kernel density estimation model. The results show that the model has higher prediction accuracy.

Composition and Provenance of Sandstones and Siltstones in Paleogene, Huimin Depression, Bohai Bay Basin, Eastern China

This study was conducted to distinguish the compositions and provenance of sandstones and siltstones in the Ek1–Es3 members of Huimin depression. The samples have been analyzed for petrographic, major element and selected trace element compositions (including REE). The results show that the sandstones from the first member of Kongdian Formation (Ek1) have higher quartz compositions than those from the fourth member (Es4) and the third member (Es3) of Shahejie Formation. The alkali feldspar/plagioclase ratio in the A-CN-K diagrams decreases in the order Ek1>Es4>Es3, which suggests that the Ek1 member had a more alkali feldspar-rich granitoid source and more intense weathering of the source than the Es4 and Es3 members. The mineral distributions in the A-CN-K diagrams also indicate that the sandstones and siltstones in the three members underwent K-metasomatism. Extrapolation of the sandstones and siltstones back to the plagioclase-alkali feldspar line in the A-CN-K diagram suggests a high average plagioclase to alkali feldspar ratio in the provenance (tonalite to granite). In addition, the chemical index of weathering (CIW) and chemical index of alteration (CIA) parameters of the sandstones and siltstones suggest that the weathering of the first cycle material was intense, and the CIW decreases in the order Ek1>Es4>Es3. Trace element ratios suggest all the sedimentary rocks were mostly derived from granitoids. Elemental ratio plots (e.g., Th/Sc vs. Eu/Eu*) of sandstones and siltstones suggest a mix of a granodiorite-tonalite source as a source of the sandstones and siltstones. The sandstones and siltstones of Es3 and Es4 members also contain higher Eu/Eu* and lower Th/Sc ratios than the sandstones and siltstones of Ek1 member. As is consistent with the petrography, it suggests that the sandstones and siltstones of Es3 and Es4 members are derived from a source with less granite and more granodiorite-tonalite than the sandstones and siltstones of Ek1 member.

Application of facies-controlling stochastic modeling technique in heterogeneity reservoir and its effective application analysis

Many oilfield have gone into the intermediary or later stage of development, with the raise of the development level, reservoir geologic research urgently need some new practical technique method to describe reservoir properties accurately and carefully. Basing on principles of sedimentology and quantitative analysis of well logging interpretation, carrying out micro-phase study, and using the research results of micro-facies to constrain the spatial distribution of reservoir parameters. Establishing a fine reservoir geological model, and solve the problem of sedimentary facies modeling can not effective combination in the process of modeling. Practices have proved that this method is feasible, especially in the heterogeneity reservoirs. Application of phase control modeling technique not only provide a more accurate reservoir property model, but also can provide a geological basis for the remaining petroleum development and development adjustment.

Diagenesis of Chang6 Formation of Hu2 block, Huanjiang oilfield, Ordos Basin

ABSTRACT Three mian diagenetic processes, compaction, cementation and dissolution of Chang6 sandstone in Hu2 block of Huanjiang oilfield were identified and their impact on the tight reservoir quality were analyzed. Four pore types, intergranular, intragranular, moldic and micropores were identified. Porosity and permeability of low-energy facies with high level of muddy content were generally lower. A rapid loss of primary porosity was caused by compaction, proved by the abrupt change tendency at approximate depth of 2130m. Calcite was the dominant cement which plugged the intergranular pores, whereas other minerals like secondary overgrowth, kaolinite and illite also contributed to tightening the reservoir.

A New Approach to Fracture Modeling Based on the Extended Finite Element Simulation Method and Kriging Method

Abstract The authors proposed one new fracture modeling method called the stochastic extended finite element method based on fracture mechanics and the kriging method with multifield trend as an attempt to benefit from the advantage of each method: compliance with fracture mechanics equations and reproduction of fracture observed data respectably. Based on the stochastic extended finite element simulation method, we wrote a fracture modeling system software and built the fracture propagation model and fracture distribution model of Qingshankou Formation in Daqingzi region. Simulation results have shown that the fracture modeling method could improve the characterization precision of fractured reservoir.