Application of Well Test in Daqing Oil Field

1997 ◽  
Vol 5 (01) ◽  
pp. 93-99 ◽  
Author(s):  
Chen Yongsheng ◽  
Wang Yaozu
Keyword(s):  
Oil Field ◽  
Well Test ◽  
Daqing Oil Field

Gulong Oilfield Putaohua Oil Layer in the Gu 83 Block Sequence and Sandstone Characteristics Research

2013 ◽  
Vol 395-396 ◽  
pp. 459-462
Author(s):  
Lu Qi Li ◽  
Cheng Zhi Liu ◽  
Yan Chun Liu
Keyword(s):  
High Resolution ◽  
Research Area ◽  
Oil Field ◽  
Combination Method ◽  
Well Test ◽  
Stratigraphic Framework ◽  
Daqing Oil Field ◽  
Production Increase ◽  
High Resolution Sequence Stratigraphy ◽  
Production Company

Gu 83 wellblock is the center of the Gulong reserves, the well test oil yield is high, the oil-bearing area shall, as reserves and production increase nine oil production company of Daqing oil field replacement area. On the basis of high resolution sequence stratigraphy theory, strata as the instruction, the trunk section and the well combination method is used to contrast layer and multiple well profile compared to small layer, establish high resolution stratigraphic framework. The Putaohua reservoir is divided into three sandstone under the group, which, subdivided three eight small layers for sandstone. Through well combine to determine the sequence division of the interface, divided into Putaohua reservoir. Considering lithology, curve characteristics of shaft vibration, even the well profile correlation research area according to the principle, method, sequence division division, in the Putaohua oil layer, three sets of sandstone under the group; On the segmentation, each group sandstone, upper sandstone will eventually set is divided into two layers of P11, P12; middle sandstone is divided into P13, P14, P15 three small layer; under sandstone under group is divided into P16, P17, P18 three small layer.

A Back Allocation Methodology to Estimate the Real-Time Flow and Assist Production Monitoring

2021 ◽  
Author(s):  
Gabriela Chaves ◽  
Danielle Monteiro ◽  
Virgilio José Martins Ferreira
Keyword(s):  
Real Time ◽  
Input Data ◽  
Oil Field ◽  
Well Testing ◽  
Well Test ◽  
Time Data ◽  
Time Flow ◽  
Well Model ◽  
Operational Information ◽  
The Individual

Abstract Commingle production nodes are standard practice in the industry to combine multiple segments into one. This practice is adopted at the subsurface or surface to reduce costs, elements (e.g. pipes), and space. However, it leads to one problem: determine the rates of the single elements. This problem is recurrently solved in the platform scenario using the back allocation approach, where the total platform flowrate is used to obtain the individual wells’ flowrates. The wells’ flowrates are crucial to monitor, manage and make operational decisions in order to optimize field production. This work combined outflow (well and flowline) simulation, reservoir inflow, algorithms, and an optimization problem to calculate the wells’ flowrates and give a status about the current well state. Wells stated as unsuited indicates either the input data, the well model, or the well is behaving not as expected. The well status is valuable operational information that can be interpreted, for instance, to indicate the need for a new well testing, or as reliability rate for simulations run. The well flowrates are calculated considering three scenarios the probable, minimum and maximum. Real-time data is used as input data and production well test is used to tune and update well model and parameters routinely. The methodology was applied using a representative offshore oil field with 14 producing wells for two-years production time. The back allocation methodology showed robustness in all cases, labeling the wells properly, calculating the flowrates, and honoring the platform flowrate.

A Novel Well Test Data Analyzer and Process Optimizer Using Artificial Intelligence and Machine Learning Techniques

2021 ◽  
Author(s):  
Nagaraju Reddicharla ◽  
Subba Ramarao Rachapudi ◽  
Indra Utama ◽  
Furqan Ahmed Khan ◽  
Prabhker Reddy Vanam ◽  
...  
Keyword(s):  
Artificial Intelligence ◽  
Machine Learning ◽  
Real Time ◽  
Test Data ◽  
Oil Field ◽  
Well Testing ◽  
Well Test ◽  
Time Data ◽  
Real Time Data ◽  
Well Tests

Abstract Well testing is one of the vital process as part of reservoir performance monitoring. As field matures with increase in number of well stock, testing becomes tedious job in terms of resources (MPFM and test separators) and this affect the production quota delivery. In addition, the test data validation and approval follow a business process that needs up to 10 days before to accept or reject the well tests. The volume of well tests conducted were almost 10,000 and out of them around 10 To 15 % of tests were rejected statistically per year. The objective of the paper is to develop a methodology to reduce well test rejections and timely raising the flag for operator intervention to recommence the well test. This case study was applied in a mature field, which is producing for 40 years that has good volume of historical well test data is available. This paper discusses the development of a data driven Well test data analyzer and Optimizer supported by artificial intelligence (AI) for wells being tested using MPFM in two staged approach. The motivating idea is to ingest historical, real-time data, well model performance curve and prescribe the quality of the well test data to provide flag to operator on real time. The ML prediction results helps testing operations and can reduce the test acceptance turnaround timing drastically from 10 days to hours. In Second layer, an unsupervised model with historical data is helping to identify the parameters that affecting for rejection of the well test example duration of testing, choke size, GOR etc. The outcome from the modeling will be incorporated in updating the well test procedure and testing Philosophy. This approach is being under evaluation stage in one of the asset in ADNOC Onshore. The results are expected to be reducing the well test rejection by at least 5 % that further optimize the resources required and improve the back allocation process. Furthermore, real time flagging of the test Quality will help in reduction of validation cycle from 10 days hours to improve the well testing cycle process. This methodology improves integrated reservoir management compliance of well testing requirements in asset where resources are limited. This methodology is envisioned to be integrated with full field digital oil field Implementation. This is a novel approach to apply machine learning and artificial intelligence application to well testing. It maximizes the utilization of real-time data for creating advisory system that improve test data quality monitoring and timely decision-making to reduce the well test rejection.

An Alkaline Bio-Surfactant Polymer Flooding Pilots in Daqing Oil Field

1999 ◽  
Author(s):  
Wang Demin ◽  
Cheng Jiecheng ◽  
Li Qun ◽  
Li Lizhong ◽  
Zhao Changjiu
Keyword(s):  
Polymer Flooding ◽  
Oil Field ◽  
Daqing Oil Field

scholarly journals Analysis of the Energy Return on Investment (EROI) of the Huge Daqing Oil Field in China

2011 ◽  
Vol 3 (12) ◽  
pp. 2323-2338 ◽  
Author(s):  
Yan Hu ◽  
Lianyong Feng ◽  
Charles C.S. Hall ◽  
Dong Tian
Keyword(s):  
Return On Investment ◽  
Oil Field ◽  
Energy Return On Investment ◽  
Daqing Oil Field

The Mechanism of PCP Wells' Tubing and Rod Wear Issue in Polymer Flooding in Daqing Oil Field

2008 ◽  
Author(s):  
He Liu ◽  
Pei Xiaohan ◽  
Peng Baiqi ◽  
Hou Yu ◽  
Wang Yumei ◽  
...  
Keyword(s):  
Polymer Flooding ◽  
Oil Field ◽  
Daqing Oil Field

Review of Practical Experience by Polymer Flooding at Daqing

2009 ◽  
Vol 12 (03) ◽  
pp. 470-476 ◽  
Author(s):  
Dongmei Wang ◽  
Huanzhong Dong ◽  
Changsen Lv ◽  
Xiaofei Fu ◽  
Jun Nie
Keyword(s):  
Oil Production ◽  
Polymer Flooding ◽  
Oil Field ◽  
High Permeability ◽  
Sweep Efficiency ◽  
Molecular Weights ◽  
Well Spacing ◽  
Polymer Flood ◽  
Daqing Oil Field ◽  
Water Cut

Summary This paper describes successful practices applied during polymer flooding at Daqing that will be of considerable value to future chemical floods, both in China and elsewhere. On the basis of laboratory findings, new concepts have been developed that expand conventional ideas concerning favorable conditions for mobility improvement by polymer flooding. Particular advances integrate reservoir-engineering approaches and technology that is basic for successful application of polymer flooding. These include the following:Proper consideration must be given to the permeability contrast among the oil zones and to interwell continuity, involving the optimum combination of oil strata during flooding and well-pattern design, respectively;Higher polymer molecular weights, a broader range of polymer molecular weights, and higher polymer concentrations are desirable in the injected slugs;The entire polymer-flooding process should be characterized in five stages--with its dynamic behavior distinguished by water-cut changes; -Additional techniques should be considered, such as dynamic monitoring using well logging, well testing, and tracers; effective techniques are also needed for surface mixing, injection facilities, oil production, and produced-water treatment; andContinuous innovation must be a priority during polymer flooding. Introduction China's Daqing oil field entered its ultrahigh-water-cut period after 30 years of exploitation. Just before large-scale polymer-flooding application, the average water-cut was more than 90%. The Daqing oil-field is a large river-delta/lacustrine facies, multilayered with complex geologic conditions and heterogeneous sandstone in an inland basin. After 30 years of waterflooding, many channels and high-permeability streaks were identified in this oil field (Wang and Qian 2002). Laboratory research began in the 1960s, investigating the potential of enhanced-oil-recovery (EOR) processes in the Daqing oil field. After a single-injector polymer flood with a small well spacing of 75 m in 1972, polymer flooding was set on pilot test. During the late 1980s, a pilot project in central Daqing was expanded to a multiwell pattern with larger well spacing. Favorable results from these tests--along with extensive research and engineering from the mid-1980s through the 1990s--confirmed that polymer flooding was the preferred method to improve areal- and vertical-sweep efficiency at Daqing and to provide mobility control (Wang et al. 2002, Wang and Liu 2004). Consequently, the world's largest polymer flood was implemented at Daqing, beginning in 1996. By 2007, 22.3% of total production from the Daqing oil field was attributed to polymer flooding. Polymer flooding boosted the ultimate recovery for the field to more than 50% of original oil in place (OOIP)--10 to 12% OOIP more than from waterflooding. At the end of 2007, oil production from polymer flooding at the Daqing oil field was more than 10 million tons (73 million bbl) per year (sustained for 6 years). The focus of this paper is on polymer flooding, in which sweep efficiency is improved by reducing the water/oil mobility ratio in the reservoir. This paper is not concerned with the use of chemical gel treatments, which attempt to block water flow through fractures and high-permeability strata. Applications of chemical gel treatments in China have been covered elsewhere (Liu et al. 2006).

scholarly journals Numerical Well Test Analysis for Polymer Flooding considering the Non-Newtonian Behavior

2015 ◽  
Vol 2015 ◽  
pp. 1-10
Author(s):  
Jia Zhichun ◽  
Li Daolun ◽  
Yang Jinghai ◽  
Xue Zhenggang ◽  
Lu Detang
Keyword(s):  
Transient Response ◽  
Polymer Concentration ◽  
Shear Thinning ◽  
Polymer Flooding ◽  
Oil Field ◽  
Well Test ◽  
Well Test Analysis ◽  
Test Analysis ◽  
Pressure Transient ◽  
Thinning Effect

Well test analysis for polymer flooding is different from traditional well test analysis because of the non-Newtonian properties of underground flow and other mechanisms involved in polymer flooding. Few of the present works have proposed a numerical approach of pressure transient analysis which fully considers the non-Newtonian effect of real polymer solution and interprets the polymer rheology from details of pressure transient response. In this study, a two-phase four-component fully implicit numerical model incorporating shear thinning effect for polymer flooding based on PEBI (Perpendicular Bisection) grid is developed to study transient pressure responses in polymer flooding reservoirs. Parametric studies are conducted to quantify the effect of shear thinning and polymer concentration on the pressure transient response. Results show that shear thinning effect leads to obvious and characteristic nonsmoothness on pressure derivative curves, and the oscillation amplitude of the shear-thinning-induced nonsmoothness is related to the viscosity change decided by shear thinning effect and polymer concentration. Practical applications are carried out with shut-in data obtained in Daqing oil field, which validates our findings. The proposed method and the findings in this paper show significant importance for well test analysis for polymer flooding and the determination of the polymer in situ rheology.

Application of Geological Modeling and Reservoir Simulation to the West Saertu Area of the Daqing Oil Field

1991 ◽  
Vol 6 (01) ◽  
pp. 99-106 ◽  
Author(s):  
Osmar Abib ◽  
F.J. Moretti ◽  
Cen Mei ◽  
Yuzhe Yang
Keyword(s):  
Reservoir Simulation ◽  
Oil Field ◽  
Geological Modeling ◽  
The West ◽  
Daqing Oil Field
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