Rock Physics-Based Carbonate Reservoir Pore Type Evaluation by Combining Geological, Petrophysical and Seismic Data

Pore type variations account for complex velocity-porosity relationship and intensive permeability heterogeneity and consequently low oil and gas recovery in carbonate reservoir. However, it is a challenge for geologist and geophysicist to quantitatively estimate the influences of pore type complexity on velocity variation at a given porosity and porosity-permeability relationship. A new rock physics-based integrated approach in this study was proposed to quantitatively characterize the diversity of pore types and its influences on wave propagation in carbonate reservoir. Based on above knowledge, permeability prediction accuracy from petrophysical data can be improved compared to conventional approach. Two carbonate reservoirs with different reservoir features, one is a shallow carbonate reservoir with average high porosity (>10%) and another one is a supper-deep carbonate reservoir with average low porosity (<5%), are used to test the proposed approach. Paleokarst is a major event to complicate carbonate reservoir pore structure. Because of limited data and lack of appropriate study methods, it is a difficulty to characterize subsurface paleokarst 3D distribution and estimate its influences on reservoir heterogeneity. A method by integrated seismic characterization is applied to delineate a complex subsurface paleokarst system in the Upper San Andres Formation, Permian basin, West Texas. Meanwhile, the complex paleokarst system is explained by using a carbonate platform hydrological model, similar to modern marine hydrological environments within carbonate islands. How to evaluate carbonate reservoir permeability heterogeneity from 3D seismic data has been a dream for reservoir geoscientists, which is a key factor to optimize reservoir development strategy and enhance reservoir recovery. A two-step seismic inversions approach by integrating angle-stack seismic data and rock physics model is proposed to characterize pore-types complexity and further to identify the relative high permeability gas-bearing zones in low porosity reservoir (< 5%) using ChangXing super-deep carbonate reservoir as an example. Compared to the conventional permeability calculation method by best-fit function between porosity and permeability, the results in this study demonstrate that gas zones and non-gas zones in low porosity reservoir can be differentiated by using above integrated permeability characterization method

Selling the Data Product: Pricing Strategies and Welfare Implications

This paper examines the pricing and welfare implications of data as a factor of production with a stylized economic model. We introduce a generalized framework that specifies two types of data: 1) public data pricing, which maximizes social welfare, and 2) commercial data pricing, which maximizes the profit. The model reveals two takeaways: first, two prices may converge in the data economy. It is due to that data come from citizens and may be used to create value back to them. Therefore, a profit- seeking data seller might find it optimal to extend the user base, which is in line with the interest of the welfare maximizer. Second, the pricing gap between optimal prices does not change monotonically with the improvement of data quality. These findings shed new light on the current and future of data product operations, particularly in the understudied public sectors

Prevalence and Relevant Factors of Nocturia and Its Impact on Sleep Quality in Chinese University Students

The purpose of this study was to investigate the prevalence and relevant factors of nocturia and its impact on sleep quality in university students in Mainland China. A large-scale survey was conducted on 14,000 university students from 3 universities in Henan province, China by using an anonymous questionnaire. The questionnaire collected the information from the past six months. The relationships between the prevalence of nocturia and its relevant factors were evaluated. A total of 13,874 questionnaires were collected and 13,104 qualified for statistical analysis. A total of 659 students suffered from clinically relevant nocturia (CRN) (4.56% in male and 5.34% in female). Both univariate analysis and the logistic stepwise regression model showed that the prevalence of nocturia was significantly related to female, history of enuresis, ease of waking up, urgency, frequency and RUTI (P \u3c 0.05). The sleep quality and the university entrance score of CRN group was significantly lower than that of control group (P \u3c 0.05). Nocturia was common in Chinese university students and showed a negative impact on sleep and academic performance. Gender of female, history of enuresis, ease of waking up, urgency, frequency and RUTI were relevant factors for CRN

Paleokarst system development in the San Andres Formation, Permian Basin, revealed by seismic characterization

Paleokarst systems are one of the major factors resulting in carbonate reservoir heterogeneity and compartmentalization. Nevertheless, few effective workflows have been proposed to map the 3D distribution of such systems. We describe a detailed seismic characterization approach integrating core, well log and rock physics analysis, to reveal a complex subsurface paleokarst system in the San Andres Formation, Permian basin, West Texas. In the area of high volume production, the collapsed paleokarst system is characterized by irregularly developed crackle and fracture breccias, mosaic breccias and cave fillings in the Upper San Andres Formation, which are delineated using seismic acoustic impedance. Along the transition from platform to basin, the paleokarst system is marked by a linear collapse including sags and small vertical faults that are recognizable in seismic imaging. Production data indicates that tight paleokarst zones cause reservoir compartmentalization and influence fluid communication between wells. The complex paleokarst system development is explained using a carbonate platform hydrological model, an outcrop analogue similar to modern marine hydrological environments within carbonate islands. Our method of model development for complex subsurface paleokarst systems may be applicable to other paleoenvironments

An Alternative Adaptive Method for Seismic Data Denoising and Interpolation

Seismic data denoising and interpolation are generally essential steps for reflection processing and imaging workflow especially for the complex surface geologic conditions and the irregular acquisition field area. The rank-reduction method is a valid way for the attenuation of random noise and data interpolation by selecting the suitable threshold, i.e., the rank of the useful signals. However, it is difficult for the traditional rank-reduction method to select an appropriate threshold. In this paper, we propose an adaptive rank-reduction method based on the energy entropy to automatically estimate the rank as the threshold for seismic data processing and interpolation. This method considers the energy entropy into the traditional rank-reduction method. The energy entropy of signals can be used to indicate the energy intensity of a signal component in the total energy. The difference of the energy entropy between the useful signals and random noise is perceived as a measurement for selecting the appropriate threshold. Synthetic and field examples indicate that the proposed method can well achieve the attenuation of random noise and interpolation automatically without the estimation of the ranks and demonstrate the feasibility of the new adaptive method in seismic data denoising and interpolation

An NAM Domain Gene, GhNAC79, Improves Resistance to Drought Stress in Upland Cotton

Plant-specific NAC proteins comprise one of the largest transcription factor families in plants and play important roles in plant development and the stress response. Gossypium hirsutum L. is a major source of fiber, but its growth and productivity are limited by many biotic and abiotic stresses. In this study, the NAC domain gene GhNAC79 was functionally characterized in detail, and according to information about the cotton genome sequences, it was located on scaffold42.1, containing three exons and two introns. Promoter analysis indicated that the GhNAC79 promoter contained both basic and stress-related elements, and it was especially expressed in the cotyledon of Arabidopsis. A transactivation assay in yeast demonstrated that GhNAC79 was a transcription activator, and its activation domain was located at its C-terminus. The results of qRT-PCR proved that GhNAC79 was preferentially expressed at later stages of cotyledon and fiber development, and it showed high sensitivity to ethylene and meJA treatments. Overexpression of GhNAC79 resulted in an early flowering phenotype in Arabidopsis, and it also improved drought tolerance in both Arabidopsis and cotton. Furthermore, VIGS-induced silencing of GhNAC79 in cotton led to a drought-sensitive phenotype. In summary, GhNAC79 positively regulates drought stress, and it also responds to ethylene and meJA treatments, making it a candidate gene for stress studies in cotton