Thermal maturity and burial history modelling of shale is enhanced by use of Arrhenius time-temperature index and memetic optimizer

Thermal maturity indices and modelling based on Arrhenius-equation reaction kinetics have played an important role in oil and gas exploration and provided petroleum generation insight for many kerogenrich source rocks.Debate continues concerning how best to integrate the Arrhenius equation and which activation energies(E)and frequency factors(A)values to apply.A case is made for the strong theoretical basis and practical advantages of the time-temperature index(∑TTIARR)method,first published in 1998,using a single,carefully selected E-A set(E?218 kJ/mol(52.1 kcal/mol);A?5.45Et26/my)from the well-established A-E trend for published kerogen kinetics.An updated correlation between ∑TTIARR and vitrinite reflectance(Ro)is provided in which the P TTIARR scale spans some 18 orders of magnitude.The method is readily calculated in spreadsheets and can be further enhanced by visual basic for application code to provide optimization.Optimization is useful for identifying possible geothermal gradients and erosion intervals covering multiple burial intervals that can match calculated thermal maturities with measured Ro data.A memetic optimizer with firefly and dynamic local search memes is described that flexibly conducts exploration and exploitation of the feasible,multi-dimensional,thermal history solution space to find high-performing solutions to complex burial and thermal histories.A complex deep burial history example,with several periods of uplift and erosion and fluctuating heat flow is used to demonstrate what can be achieved with the memetic optimizer.By carefully layering in constraints to the models specific insights to episodes in their thermal history can be exposed,leading to better characterization of the timing of petroleum generation.The objective function found to be most effective for this type of optimization is the mean square error(MSE)of multiple burial intervals for the difference between calculated and measure Ro.The sensitively-scaled P TTIARR methodology,coupled with the memetic optimizer,is well suited for rapidly conducting basin-wide thermal maturity modelling involving multiple pseudo-wells to provide thermal maturity analysis at fine degrees of granularity.

A detailed reconstruction of changes in the factors and parameters of soil erosion over the past 250 years in the forest zone of European Russia(Moscow region)

Accelerated soil erosion is a major threat to soil,and there are great variations in the rate of soil erosion over time due to natural and human-induced factors.The temperate forest zone of Russia is character-ized by complex stages of land-use history(i.e.active urbanization,agricultural development,land abandonment,etc.).We have for the first time estimated the rates of soil erosion by the WaTEM/SEDEM model(rainfall erosion)and by a regional model(snowmelt erosion)over the past 250 years(from 1780 to 2019)for a 100-km2 study site in the Moscow region of Russia.The calculations were made on the basis of a detailed historical reconstruction of the following factors:the location of the arable land,crop rotation,the rain erosivity factor,and the maximum snow water equivalent.The area of arable land has decreased more than 3.5-fold over the past 250 years.At the end of the 20th century,the rates of gross erosion had declined more than 5.5-fold(from 28×10^(3) to 5×10^(3) t·ha^(-1)yr^(-1))in comparison with the end of the 18th century.Changes in the boundaries of arable land and also the relief features had led to a significant intra-slope accumulation of sediments.As a result of sediment redeposition within the arable land,the variation in net soil erosion was significantly lower than the variation in gross soil erosion.The changes in arable land area and in crop composition are the factors that have to the greatest extent determined the changes in soil erosion in this territory.

The development of U.S.soil erosion prediction and modeling

Soil erosion prediction technology began over 70 years ago when Austin Zingg published a relationship between soil erosion(by water)and land slope and length,followed shortly by a relationship by Dwight Smith that expanded this equation to include conservation practices.But,it was nearly 20 years before this work's expansion resulted in the Universal Soil Loss Equation(USLE),perhaps the foremost achievement in soil erosion prediction in the last century.The USLE has increased in application and complexity,and its usefulness and limitations have led to the development of additional technologies and new science in soil erosion research and prediction.Main among these new technologies is the Water Erosion Prediction Project(WEPP)model,which has helped to overcome many of the shortcomings of the USLE,and increased the scale over which erosion by water can be predicted.Areas of application of erosion prediction include almost all land types:urban,rural,cropland,forests,rangeland,and construction sites.Specialty applications of WEPP include prediction of radioactive material movement with soils at a superfund cleanup site,and near real-time daily estimation of soil erosion for the entire state of Iowa.