Assessment of the contribution of the air-vapor mixture volume exceeding over the volumes injected to oil and petroleum product losses from evaporation

В настоящее время при экспериментальном определении потерь нефтепродуктов от «больших дыханий» резервуаров используют формулу Черникина - Валявского. При этом «однако» не учитывается, что объем вытесняемой в атмосферу паровоздушной смеси, как правило, превышает объем закачиваемой нефти (нефтепродукта). Соответствующий параметр - коэффициент превышения, - по экспериментальным данным, может принимать значения более 8. До недавнего времени не до конца были ясны даже причины этого явления, соответственно, эмпирические зависимости для расчета коэффициента превышения не учитывали всех влияющих факторов. Авторами статьи на основе уравнения Менделеева - Клапейрона в дифференциальной форме получено аналитическое выражение для вычисления среднего коэффициента превышения. Установлено, что данная величина зависит от молярной массы и температуры паровоздушной смеси в начале и конце закачки, а также от соотношения объемов газового пространства резервуара и закачиваемого продукта. Для анализа полученной зависимости был спланирован и проведен вычислительный эксперимент, предусматривающий изменение определяющих параметров в широком диапазоне. Расчеты выполнялись для нефти и бензина. По результатам 25 вычислительных «опытов» определено, что при операциях с бензином средний коэффициент превышения (за одну операцию заполнения резервуара) в исследованном диапазоне температур принимает значения от 1,029 до 1,678, а при операциях с нефтью - от 1,016 до 1,338, то есть, как правило, превышает погрешность инструментальных замеров потерь нефти (нефтепродуктов) от испарения. Математическое ожидание рассматриваемой величины при операциях с бензином составляет 1,26, с нефтью - 1,16. Таким образом, учет среднего коэффициента превышения при обработке результатов инструментальных измерений потерь углеводородов от испарений вследствие «больших дыханий» резервуаров является обязательным. Currently, the Chernikin - Valyavsky formula is used in the experimental determination of petroleum product losses from “large breaths” of reservoirs. However, it does not take into account that the volume of air-vapor mixture displaced into the atmosphere usually exceeds the volume of pumped oil/petroleum product. The corresponding parameter, the excess ratio, according to the experimental data can have values of more than 8. Until recently, even the causes of this phenomenon were not completely clear, and thus, the empirical dependencies for calculating the excess ratio did not take into account all the influencing factors. Based on the Mendeleev-Clapeyron equation in differential form, the analytic expression to calculate the average excess ratio was obtained. It was found that this value depends on the molar mass and temperature of the air-vapor mixture at the beginning and the end of the injection, as well as on the ratio of the tank gas space volume and the injected product volume. To analyze the resulting dependency, a computational experiment involving changes in the defining parameters over a wide range was planned and conducted. The calculations were performed for oil and gasoline. According to the results of 25 computational experiments, it was determined that during operations with gasoline the average excess ratio (per one tank filling operation) in the investigated temperature range has values from 1.029 to 1.678, and during operations with oil - from 1.016 to 1.338; that generally exceeds the instrument error of oil/petroleum product losses from vaporization measurement. The mathematical expectation of the value in question during operations with gasoline is 1.26, it is 1.16 with oil. It is therefore mandatory to take into account the average excess ratio when processing the results of instrumental measurements of hydrocarbon losses from evaporation due to “large breaths” of reservoirs.

About Identification of Instrument Error Parameters for a Gravity Gradiometer

The article presents the description of two algorithms used for processing of the raw data of a gravity gradiometer. These algorithms are intended for estimation of some instrument errors. The first algorithm is applicable for the instrument operation in its stationary mode, the second proposes the use of a special test bench. Rotary gravity gradiometer of the accelerometric type was taken as a prototype for relevant mathematical models. Nowadays this type of gradiometer is brought to the stage of practical implementation and serial production.

Technical Note: Possible errors in flux measurements due to limited digitalization

Recently reported trends of carbon dioxide uptakes pose the question if trends may results of the digitalization of gas analysers and sonic anemometers used in the 1990s. Simulating a 12-bit digitalization and the instrument error reported for the R2 and R3 sonic anemometers elsewhere, the influence of these deficits in comparison to the 16-bit digitalization were quantified. Both issues have an effect only on trace gas fluxes of small magnitude, mainly for the carbon rather than for the water vapour fluxes. The influence on the annual net ecosystem exchange is negligible.

Optimizing Data Collection in the Home Lab

Many of the projects currently under investigation in biological research labs focus on macromolecules that are difficult to crystallize such as: complexes, multi-domain and membrane proteins. Typically, crystallization trials can produce small, weakly diffracting crystals that may also have other challenging attributes. Recent hardware and software developments have improved in-house data quality on a wide range of samples. Small and highly focused x-ray beams allow one to select the best diffracting portion of a larger crystal and reduce background scatter for much smaller samples. Shutterless data collection helps to reduce instrument error resulting from shutter jitter and allows fine slicing of data runs without frame to frame dead time penalties while the practice of dealing with multiple, cracked or twinned crystals has improved greatly due to software enhancements. Results from in-house data collection including: shutterless operation, optimization of crystal orientation and collection parameters will be discussed.