Analysis and Correlation of Nitrogen and Lean-Gas Miscibility Pressure(includes associated paper 16463 )

Author:

Firoozabadi Abbas1,Khalid Aziz1

Affiliation:

1. Stanford U.

Abstract

Summary The vaporizing gas drive (VGD) process was modeled with the Peng-Robinson equation of state (PR-EOS) and a compositional simulator. The comparison of numerical results with available experimental data has shown that the PR-EOS overestimates the minimum miscibility pressure (MMP), but it correctly shows that the length required to achieve miscibility is different for N2 and methane. Experimental data and some simulation runs have been used to develop a simple and reliable correlation for the prediction of MMP. Introduction For some high-pressure oil reservoirs, N2or a lean hydrocarbon gas may be suitable for achieving miscibility conditions. These gases are particularly attractive because of the ease with which they can be handled and the potential they offer for establishing gravity-stabilized displacement in thick oil columns. Two field projects involving N2 and lean-gas injection are discussed. In the Devonian reservoir of Block 31 field in west Texas,1–4 the world's first large-scale high-pressure gas injection project has been under way since 1949. The reservoir rock consists of about 65 % tripolitic chert and 20% fine crystalline, sucrosic limestone. The remainder is variable amounts of lime mud, skeletal material, pellets, and quartz silt. The porosity is intercrystalline and averages 15%. The permeability averages 1 md, but is about 10 times this amount in the hairline fractures that are present. Lean-gas injection in Block 31 field started 3 1/2 years after field discovery, and the reservoir pressure was raised to the miscibility pressure in 1952. Since 1966, flue gas (88% N2 and 12% CO2) has been injected in one part of the field and N2-contaminated lean hydrocarbon gas has been reinjected in the rest of the field. Because of the high solubility of CO2 in the interstitial water, the displacing fluid was essentially N2. Even though the miscible wne seems to have difficulty in maintaining its integrity because of reservoir stratification, fractures, and an unfavorable (10:1)gas-to-oil mobility ratio, the ultimate recovery is expected to be greater than 65 % of the original oil in place (OOIP). A large part of Algeria's Hassi Messaoud field5is undergoing lean-gas miscible drive. The reservoir is made up of a highly siliceous, cemented quartzitic sandstone and is highly heterogeneous. Water is also injected in some parts of the field, and in other parts, water is alternated with gas. Ultimate recovery is expected to be about 50% of OOIP in the miscible gas injection area, about 33% of OOIP in the water injection area, and about 11% for naturally depleting areas. Stalkup6 provides details of several other VGD field projects. On the whole, the reservoirs undergoing high-pressure miscible drive have been rated successful;the recoveries usually exceed 50% of OOIP. In deep, volatile oil reservoirs, N2 and lean-gas miscible drive have the potential to recover oil that is unrecoverable by water injection alone. The most important parameter required for the design and evaluation of N2 or lean-gas miscible drive is the MMP. The literature does not contain any general correlation that can be used to provide an estimate of MMP for N2 or lean gases. In this paper we explore the potential of the PR-EOS to predict the MMP for the VGD process, discuss the effect of N2and lean gases on the MMP, and present a simple correlation for the estimation of VGD MMP. Review of Experimental Data Experimental data reported in the literature for VGD MMP are rather limited. Information on only eight reservoir fluids with known compositions was located. These data are briefly reviewed below.

Publisher

Society of Petroleum Engineers (SPE)

Subject

Process Chemistry and Technology

Cited by 40 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

1. Experimental Study on Improving Tight Oil Recovery by Injecting Natural Gas;Springer Series in Geomechanics and Geoengineering;2024

2. Regression;Artificial Intelligence for a More Sustainable Oil and Gas Industry and the Energy Transition;2024

3. Estimation of Minimum Miscibility Pressure in Impure/Pure N2 Based Enhanced Oil Recovery Process: A Comparative Study of Statistical and Machine Learning Algorithms;2023 6th International Conference on Robotics, Control and Automation Engineering (RCAE);2023-11-03

4. Study on Interaction Characteristics of Injected Natural Gas and Crude Oil in a High Saturation Pressure and Low-Permeability Reservoir;Processes;2023-07-19

5. Exploring the power of machine learning in analyzing the gas minimum miscibility pressure in hydrocarbons;Geoenergy Science and Engineering;2023-07

同舟云学术

1.学者识别学者识别

2.学术分析学术分析

3.人才评估人才评估

"同舟云学术"是以全球学者为主线,采集、加工和组织学术论文而形成的新型学术文献查询和分析系统,可以对全球学者进行文献检索和人才价值评估。用户可以通过关注某些学科领域的顶尖人物而持续追踪该领域的学科进展和研究前沿。经过近期的数据扩容,当前同舟云学术共收录了国内外主流学术期刊6万余种,收集的期刊论文及会议论文总量共计约1.5亿篇,并以每天添加12000余篇中外论文的速度递增。我们也可以为用户提供个性化、定制化的学者数据。欢迎来电咨询!咨询电话:010-8811{复制后删除}0370

www.globalauthorid.com

TOP

Copyright © 2019-2024 北京同舟云网络信息技术有限公司
京公网安备11010802033243号  京ICP备18003416号-3