Reservoir Characterization and Modelling with Diagenetic Trends of carbonates of the Kawagarh Formation: A Section exposed in the Kala-Chitta Range, Pakistan

Present study is focused on the diagenetic studies and reservoir characterization of the Cretaceous KawagarhFormation exposed in the Gandab village, Kala-Chitta range, north-western Himalayan Fold-and-Thrust belt, Pakistan.The formation is composed of argillaceous limestone and dark grey marls. A total of thirty-three representativecarbonate rock samples were collected at equal intervals of three meters. Various diagenetic features includingcementation, micritization, pyrite precipitation, neomorphism, fracturing, sparitization and stylolitization were observedin the studied rocks which occur in the marine, meteoric and deep burial diagenetic environments respectively. Suchdiagenetic features control the reservoir quality of the rock unit. Porosity types include mostly vuggy and fracture,while minor stylolitic porosity were noted with quantity ranging from 2.66% to 3.88%. The carbonates of KawagarhFormation are highly fractured, but the filling of these fractures due to precipitation of calcite or micritic mud hasgreatly reduced its reservoir potential, while some unfilled fractures, stylolites and vuggs are the dominant factors thatenhance the reservoir potentiality of the Kawagarh Formation. However, the porosity values still do not mark the levelof reservoir rock. These diagenetic studies revealed very less chances for hydrocarbon accumulation as no significantporosity values have been observed and overall reservoir potential is characterized as poor

Relationship between Solar Flux and Sunspot Activity Using Several Regression Models

This study examines the correlation and prediction between sunspots and solar flux, two closely related factors associated with solar activity, covering the period from 2005 to 2022. The study utilizes a combination of linear regression analysis and the ARIMA prediction method to analyze the relationship between these factors and forecast their values. The analysis results reveal a significant positive correlation between sunspots and solar flux. Additionally, the ARIMA prediction method suggests that the SARIMA model can effectively forecast the values of both sunspots and solar flux for a 12-period timeframe. However, it is essential to note that this study solely focuses on correlation analysis and does not establish a causal relationship. Nonetheless, the findings contribute valuable insights into future variations in solar flux and sunspot numbers, thereby aiding scientists in comprehending and predicting solar activity's potential impact on Earth. The study recommends further research to explore additional factors that may influence the relationship between sunspots and solar flux, extend the research period to enhance the accuracy of solar activity predictions and investigate alternative prediction methods to improve the precision of forecasts