基于瞬时产量递减分析确定天然裂缝性油藏平均地层压力

以Warren和Root等提出的裂缝-孔隙双重介质模型为基础,拓展延伸了Mavor、Cinco-Ley和Daprat等的裂缝系统拟稳态-定产量生产的解及基质系统拟稳态-定压力生产的解,提出了根据天然裂缝性油藏定压开采的瞬时产量递减准确估算油藏平均压力的新方法。具体方法为:分别将基质产量方程和裂缝产量方程两端取自然对数,得到两条直线;再利用其斜率和截距确定弹性储容比、油藏总储容以及泄油面积,最后确定平均地层压力。经算例和实例验证,新方法简单实用,与物质平衡法和Tiab直接合成技术法得到的估算结果十分接近。     

An Integrated Reservoir Characterization Analysis in a Carbonate Reservoir: A Case Study

Abstract

Reservoir characterization is one of the most challenging subjects in carbonate reservoirs. In this study flow zone index (FZI), Winland, and initial water saturation methods were used to classify rock typing in an Iranian oil field. In addition, stratigraphic modified Lorenz plots were generated for the purpose of identifying the flow zone and barriers in each well. The results were consistent with Winland result and FZI. The scanning electron microscopy photomicrographs, pore throat radius, grain size distribution data, and thin section of the obtained rock type were studied and found to be consistent with the findings of this work.     

Asymptotic stabilizability of homogeneous polynomial systems of odd degree

We give some tools for the construction of the homogeneous feedback witch stabilizes a generic class of single input, two dimensional, homogeneous systems.     

Integrating the lot-sizing and sequencing decisions for scheduling a capacitated flow line

In this paper we consider a general problem of scheduling a single flow line consisting of multiple machines and producing a given set of jobs. The manufacturing environment is characterized by sequence dependent set-up times, limited intermediate buffer space, and capacity constraints. In addition, jobs are assigned with due dates that have to be met. The objectives of the scheduling are: (1) to meet the due dates without violating the capacity constraints, (2) to minimize the makespan, and (3) to minimize the inventory holding costs. While most of the approaches in the literature treat the problem of scheduling in flow lines as two independent sub-problems of lot-sizing and sequencing, our approach integrates the lot-sizing and sequencing heuristics. The integrated approach uses the Silver-Meal heuristic (modified to include lot-splitting) for lot-sizing and an improvement procedure applied to Palmer's heuristic for sequencing, which takes into account the actual sequence dependent set-up times and the limited intermedite buffer capacity. We evaluate the performance of the integrated approach and demonstrate its efficacy for scheduling a real world SMT manufacturing environment.     

An Experimental Investigation of Asphaltene Precipitation During Natural Production of Heavy and Light Oil Reservoirs: The Role of Pressure and Temperature

Abstract

Many oil reservoirs encounter asphaltene precipitation as a major problem during natural production. In spite of numerous experimental studies, the effect of temperature on asphaltene precipitation during pressure depletion at reservoir conditions is still obscure in the literature. To study their asphaltene precipitation behavior at different temperatures, two Iranian light and heavy live oil samples were selected. First, different screening criteria were applied to evaluate asphaltene instability of the selected reservoirs using pressure, volume, and temperature data. Then, a high pressure, high temperature filtration (HPHT) setup was designed to investigate the asphaltene precipitation behavior of the crude samples throughout the pressure depletion process. The performed HPHT tests at different temperature levels provided valuable data and illuminated the role of temperature on precipitation. In the final stage, the obtained data were fed into a commercial simulator for modeling and predicting purposes of asphaltene precipitation at different conditions. The results of the instability analysis illustrated precipitation possibilities for both reservoirs which are in agreement with the oil field observations. It is observed from experimental results that by increasing the temperature, the amount of precipitated asphaltene in light oil will increase, although it decreases precipitation for the heavy crude. The role of temperature is shown to be more significant for the light crude and more illuminated at lower pressures for both crude oils. The results of thermodynamic modeling proved reliable applicability of the software for predicting asphaltene precipitation under pressure depletion conditions. This study attempts to reveal the complicated role of temperature changes on asphaltene precipitation behavior for different reservoir crudes during natural production.     

Introducing a New Method for Predicting PVT Properties of Iranian Crude Oils by Applying Artificial Neural Networks

Abstract

In this study artificial neural networks (ANNs) have been applied for the prediction of main pressure, volume, and temperature (PVT) properties, bubble point pressure (P_b), and bubble point oil formation volume factor (B_ob) of crude oil samples from different wells of Iranian oil reservoirs. Via a detailed comparison, the great power of ANNs with respect to traditional methods of predicting PVT properties, like Standing, Vasquez and Beggs, and Al-Marhoun, with higher prediction precision up to R² = 0.990 has been illustrated and the obtained parameters of ANNs for the application of prediction of other crude oil samples has been presented. The applied PVT data set in this study consists of 218 crude oil samples from Iranian reservoirs and for assurance of the applicability of the ANN model the PVT data set has been divided into 2 training (190 samples) and cross validation (28 samples) data sets and obtained ANNs from applying the training data set has been tested on the cross validation data set which has not been seen by the network during the training process. The obtained results for both training and cross validation data sets confirm the great prediction power of ANNs, for both data sets with respect to traditional PVT correlations.