Study and Application of the Directional Drilling Technique in Long-Distance Crude Oil Pipeline River-Crossing Engineering

2011 ◽  
Author(s):  
Lixin Wei ◽  
Renshan Pang ◽  
Zhihua Wang ◽  
Peng Li
Keyword(s):  
Crude Oil ◽  
Directional Drilling ◽  
Long Distance ◽  
Oil Pipeline ◽  
Drilling Technique

scholarly journals Safety Study on Wax Deposition in Crude Oil Pipeline

Processes ◽  
2021 ◽  
Vol 9 (9) ◽  
pp. 1572
Author(s):  
Bin Yao ◽  
Deyin Zhao ◽  
Zhi Zhang ◽  
Cheng Huang
Keyword(s):  
Crude Oil ◽  
Cloud Point ◽  
Freezing Point ◽  
Development Trend ◽  
Wax Deposition ◽  
Scanning Calorimetry ◽  
Long Distance ◽  
Wax Precipitation ◽  
Oil Pipeline ◽  
Precipitation Characteristics

The Shunbei crude oil pipeline is prepared to use the unheated transportation process to transport waxy crudes. However, the wax formation in the pipeline is unknown. In order to predict the wax deposition of the pipeline, the physical property experiment of Shunbei crude oil was carried out through field sampling. The density, freezing point, hydrocarbon composition, and viscosity–temperature characteristics of crude oil are obtained. The cloud point and wax precipitation characteristics of the crude oil were obtained using the differential scanning calorimetry (DSC) thermal analysis method. Then, the wax deposition rate of the pipeline was predicted by two methods: OLGA software and wax deposition kinetic model. Finally, the optimal pigging cycle of the pipeline was calculated on this basis. The results show that: Shunbei crude oil is a light crude oil with low wax content, a low freezing point, and a high cloud point. Comparing the OLGA simulation results with the calculation results of the Huang Qiyu model, the development trend of wax deposition along the pipeline was the same under different working conditions. The relative error of the maximum wax layer thickness was 6%, proving that it is feasible for OLGA to simulate wax deposition in long-distance crude oil pipelines. Affected by the wax precipitation characteristics of Shunbei crude oil, there was a peak of wax precipitation between the pipeline section where crude oil temperature was 9.31–13.31 °C and the recommended pigging cycle at the lowest throughput was 34 days in winter and 51 days in spring and autumn.

Oil Temperature Prediction of Long-Distance Hot-Crude-Oil Pipeline Based on GA-BP Optimization

2020 ◽  
Author(s):  
Tao Yu ◽  
Peng Dong ◽  
Yang Yu ◽  
Jinzhou Song ◽  
Jie Zhang
Keyword(s):  
Prediction Model ◽  
Crude Oil ◽  
Pour Point ◽  
Theoretical Formula ◽  
Production Data ◽  
Influence Coefficient ◽  
Long Distance ◽  
Temperature Prediction ◽  
Oil Pipeline ◽  
Actual Production

Abstract Due to the high pour point of the oil products transported in the long-distance high wax crude oil pipeline, in order to ensure the operation safety, it is necessary to adopt heating transmission technology, so as to ensure that the oil temperature along the pipeline is 3–5 °C higher than the pour point, that is to say, the oil temperature is the most important operation parameter of the long-distance hot oil pipeline, and the accurate prediction and control of the oil temperature is the premise of the pipeline safety optimization. Aiming at the problems of large prediction error and poor applicability of the previous theoretical formula, this paper studies the establishment of oil temperature prediction model by using data mining algorithms such as Back Propagation (BP) neural network, and improves the prediction efficiency and accuracy of the model by using Genetic Algorithm (GA) optimization. The correlation coefficient formula is used to calculate the influence coefficient of oil temperature, ground temperature, pipeline transportation and other parameters on the inlet oil temperature of the downstream station, so as to obtain the input parameters of the model. The actual production data training model is downloaded through SCADA system, and the prediction accuracy of the control model is ±0.5 °C. Compared with BP model and other theoretical formulas, the accuracy and efficiency of GA-BP oil temperature prediction model are greatly improved, and the adaptability is better. The GA-BP oil temperature prediction model trained according to the actual production data can be effectively applied to the future pipeline big data platform, which lays a theoretical foundation for the intelligent control of the pipeline.

Analysis of Hot Oil Pipeline Stress Influencing Factors

2014 ◽  
Vol 887-888 ◽  
pp. 899-902
Author(s):  
Xiao Nan Wu ◽  
Shi Juan Wu ◽  
Hong Fang Lu ◽  
Jie Wan ◽  
Jia Li Liu ◽  
...  
Keyword(s):  
Crude Oil ◽  
High Viscosity ◽  
Analysis Model ◽  
Long Distance ◽  
Oil Pipeline ◽  
Software Analysis ◽  
Key Points ◽  
Temperature And Pressure ◽  
Pressure Changes ◽  
The Impact

In order to reduce the viscosity of crude oil for transport, we often use the way of heating delivery for high pour point, high wax, and high viscosity oil. Crude oil at high temperature, through long-distance transmission, the temperature and pressure changes on the piping stress greater impact. In this paper, in order to explore the main factor of hot oil pipeline stress and the location of key points, we build the XX hot oil pipeline stress analysis model used CAESAR II software, analysis of the impact of changes in temperature and pressure on piping stress when hot oil pipeline running, draw hot oil pipeline stress distribution, clearly identifies the location of key points of stress concentration, and we have come to that temperature is a major factor in generating pipe stress.

Thermal Characteristics Simulation of the Commissioning Process for New Buried Heated Oil Pipelines

2011 ◽  
Vol 301-303 ◽  
pp. 610-616 ◽  
Author(s):  
Guo Qun Chen ◽  
Ming Hua Zhao ◽  
Bo Xu
Keyword(s):  
Temperature Field ◽  
Crude Oil ◽  
Thermal Characteristics ◽  
Hot Water ◽  
Waxy Crude Oil ◽  
Long Distance ◽  
Warm Up ◽  
Oil Pipeline ◽  
Heated Oil ◽  
Oil Pipelines

For a new buried heated oil pipeline, the temperature field of the surrounded soil is natural. Therefore the temperature is usually low in this case. For the waxy crude oil whose pour point is higher than the ground temperature, if the new pipeline transports such oil directly after heating, crude oil may gel in pipeline because its temperature decrease dramatically due to heat exchange between the fluid and the surrounded soil. Hence, in practical situation hot water is often used to warm up the pipelines for most of the new long-distance buried pipelines. Crude oil transportation is determined after the soil temperature field around the pipeline is sufficiently high and the inlet water temperature meets the requirement.

Optimizing the Steady Operation of an Double Oil Pipeline System by Decompostion Method

2004 ◽  
Author(s):  
Changchun Wu ◽  
Guotai Shao
Keyword(s):  
Crude Oil ◽  
Programming Problem ◽  
Large Scale ◽  
Optimization Problem ◽  
Petroleum Industry ◽  
Pipeline System ◽  
Long Distance ◽  
Oil Pipeline ◽  
Discharge Temperature ◽  
Decision Variables

As a main channel for long distance transportation of Daqing crude oil, Daqing-Tieling oil pipeline system consists of two pipelines in parallel. With its capacity of 45 million tons per year, the system is the largest oil pipeline system in China and plays an important role in the petroleum industry and national economy of China. Due to the complicated interconnection between the two pipelines in the system, the optimization of steady operation of the system is much more difficult than a single pipeline so that it can be considered as an optimization problem on large scale system. Besides the interconnection of the two pipelines, because of high pour point of Daqing crude oil, another difficulty to solve the problem comes from the fact that the two pipelines are hot oil pipeline, of which the heating-pumping stations are equipped with some heaters to heat the crude oil so as to improve its flow ability. For the optimization problem, the basic decision variables can be divided into two types, the discharge temperature of each heating-pumping station and the 0–1 variable which assigns a pump online or offline, and they are dependent to each other. Under certain conditions, the problem can be decomposed into two relatively independent sub-problems, one being the optimization of the oil temperatures in the system, another being the optimization of the matching between a pump combination and the all pipe segments of the system. The first sub-problem has been modeled as a nonlinear programming problem with 55 decision variables and more than one hundred constraints. For simplifying the solving process of the sub-problem, it has been further decomposed into a set of sub-problems, again, each of which can be easily solved. The second sub-problem can be modeled as a dynamic programming problem. On the basis of the models and the algorithms proposed for the above-mentioned problem, a software QTOPT has been developed specially for the Daqing-Tieling oil pipeline system, and has been used in evaluating and optimizing the process design of the system. Also the software can be used to optimize the steady operation of the system.

Data Acquisition and Processing Methods of Modbus-Based Monitorial System of Long-Distance Crude-Oil Pipeline

2012 ◽  
Vol 546-547 ◽  
pp. 817-821
Author(s):  
Hui Li
Keyword(s):  
Crude Oil ◽  
Packet Transmission ◽  
Data Organization ◽  
Long Distance ◽  
Oil Pipeline ◽  
Modbus Protocol ◽  
Automation And Control ◽  
System Data ◽  
Data Acquisition And Processing ◽  
And Control

In order to solve the accurate collection and processing of crude oil long-distance pipeline monitoring system data and set the scene for packet transmission problem, we based on Modbus protocol settings for automation and control, data processing and analysis of the reliability of the final draw a line unit as the unit of data organization.

scholarly journals Geophysical investigations for stability and safety mitigation of regional crude-oil pipeline near abandoned coal mines

2021 ◽  
Vol 18 (1) ◽  
pp. 145-162
Author(s):  
B Butchibabu ◽  
Prosanta Kumar Khan ◽  
P C Jha
Keyword(s):  
High Resolution ◽  
Crude Oil ◽  
Seismic Refraction ◽  
High Resolution Imaging ◽  
Weak Zone ◽  
Near Surface ◽  
Oil Pipeline ◽  
Refraction Tomography ◽  
Geophysical Investigations ◽  
Resolution Imaging

Abstract This study aims for the protection of a crude-oil pipeline, buried at a shallow depth, against a probable environmental hazard and pilferage. Both surface and borehole geophysical techniques such as electrical resistivity tomography (ERT), ground penetrating radar (GPR), surface seismic refraction tomography (SRT), cross-hole seismic tomography (CST) and cross-hole seismic profiling (CSP) were used to map the vulnerable zones. Data were acquired using ERT, GPR and SRT along the pipeline for a length of 750 m, and across the pipeline for a length of 4096 m (over 16 profiles of ERT and SRT with a separation of 50 m) for high-resolution imaging of the near-surface features. Borehole techniques, based on six CSP and three CST, were carried out at potentially vulnerable locations up to a depth of 30 m to complement the surface mapping with high-resolution imaging of deeper features. The ERT results revealed the presence of voids or cavities below the pipeline. A major weak zone was identified at the central part of the study area extending significantly deep into the subsurface. CSP and CST results also confirmed the presence of weak zones below the pipeline. The integrated geophysical investigations helped to detect the old workings and a deformation zone in the overburden. These features near the pipeline produced instability leading to deformation in the overburden, and led to subsidence in close vicinity of the concerned area. The area for imminent subsidence, proposed based on the results of the present comprehensive geophysical investigations, was found critical for the pipeline.

scholarly journals Data Analysis and Discussion on the Reliability of the Control Principle of a Sealed Crude Oil Pipeline

2021 ◽  
Vol 1927 (1) ◽  
pp. 012021
Author(s):  
Junjiang Liu ◽  
Liang Feng ◽  
Dake Yang ◽  
Xianghui Li
Keyword(s):  
Data Analysis ◽  
Crude Oil ◽  
Oil Pipeline ◽  
Control Principle
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