scholarly journals Flow Unit Model of Channel Sand Body and Its Effect on Remnant Oil Distribution: A Case Study of PI Formation in the Eastern Transition Zone of Daqing Oilfield

Geofluids ◽  
2020 ◽  
Vol 2020 ◽  
pp. 1-20
Author(s):  
Yue Zhang ◽  
You-liang Ji ◽  
Hui-jian Wen ◽  
Shi-zhong Ma ◽  
Dong-lai Bai ◽  
...  

To analyze the effect of various flow units in a channel sand body on remnant oil, we established a connection between various flow unit types and the remnant oil distribution. Using stratigraphic correlation and the characterization of sedimentary microfacies, we describe a single sand body, point bar, and narrow channel located at the injection-production well pattern of well B2-60-FB271 in the Eastern transition zone of the Daqing Placanticline. Architecture models of the point bar and narrow channel are also established using a series of parameters from different measurement methods. Four types of flow units (strong-current limiting, medium-current limiting, weak-current limiting, and none-current limiting) in the point bar sand body were identified, whereas one type, unshielded unit, was identified in the narrow channel. Geological parameters, such as porosity, permeability, and pore-throat radius (r50), were optimized to quantitatively characterize these various flow units. Samples were obtained from well B2-60-FB271 and analyzed by the freeze-fluorescence thin section technique. According to the displacement degree, the microscopic remnant oil was divided into three types: (1) free-state remnant oil, (2) semi-free-state remnant oil, and (3) bound-state remnant oil. We found that the strong-current limiting flow unit in the point bar is the enrichment area of free-state microscopic remnant oil and that the medium-current limiting and weak-current limiting flow units also have relatively high free microscopic remnant oil. These constitute the remaining oil enrichment areas in the study area.

2013 ◽  
Vol 838-841 ◽  
pp. 863-866
Author(s):  
Hong Zhao

The channel sand in PI3132 units of A area in Daqing oilfield is meandering river sand body. Although more than 90 percent of it is watering out, the serious heterogeneity in layers make it possible that there are plenty of remaining reserves in unwashed or low-washed segments in water flooded layers. All these two kinds of remaining oil are the main potential tapping objectives in later period of oilfield development.The writer deeply analyzed the point bar sand body of the meandering river, established the recognizing method of the abandoned channel and the lateral accretion body of point bar, understood the remaining oil distribution in the washed segments and unwashed segments of the thick oil layers. By implementing the Personalized treatments for individual wells,such as super-short radius horizontal wells drilling,waterflood depth profile controlling,cyclic injecting and producing, etc, the point bar sand body potential tapping technology for different formation cause has been established. And this has essential meaning to direct the oilfield development.


2021 ◽  
Author(s):  
Libing Fu ◽  
Jun Ni ◽  
Yuming Liu ◽  
Xuanran Li ◽  
Anzhu Xu

Abstract The Zhetybay Field is located in the South Mangyshlak Sub-basin, a delta front sedimentary reservoir onshore western Kazakhstan. It was discovered in 1961 and first produced by waterflooding in 1967. After more than 50 years of waterflooding development, the reservoirs are generally in the mid-to-high waterflooded stage and oil-water distribution becomes complicated and chaotic. It is very difficult to handle and identify so much logging data by hand since the oilfield has the characteristics of high-density well pattern and contains rich logging information with more than 2000 wells. The wave clustering method is used to divide the sedimentary rhythm of the logging curve. Sedimentary microfacies manifested as a regression sequence, with four types of composite sand bodies including the composite estuary bar and distributary channel combination, the estuary bar connected to the dam edge and the distributing channel combination, the isolated estuary bar and distributing channel combination, and the isolated beach sand. In order to distinguish the flow units, the artificial intelligence algorithm-support vector machine (SVM) method is established by learning the non-linear relationship between flow unit categories and parameters based on developing flow index and reservoir quality factor, summarizing permeability logarithm and porosity degree parameters in the sedimentary facies, and analyzing the production dynamic. The flow units in Zhetybay oilfield were classified into 4 types: A, B1, B2 and B3, and the latter three are the main types. Type A is distributed in the river, type B1 is distributed in the main body of the dam, type B2 is mainly distributed in the main body of the dam, and some of B2 is distributed in the dam edge, and B3 is located in the dam edge, sheet sand and beach sand. The results show that the accuracy of flow unit division by support vector machines reaches 91.1%, which clarifies the distribution law of flow units for oilfield development. This study is one of the significant keys for locating new wells and optimizing the workovers to increase recoverable reserves. It provides an effective guidance for efficient waterflooding in this oilfield.


2015 ◽  
Vol 8 (1) ◽  
pp. 167-171
Author(s):  
Fangfang Wu ◽  
Jinchuan Zhang ◽  
Liuzhong Li ◽  
Jinlong Wu

Tight sand reservoir is usually characterized by high heterogeneity and complex pore structure, which makes the permeability calculation a big challenge and leads to difficulties in reservoir classification and productivity evaluation. First, five different Hydraulic Flow Units and respective Porosity-permeability relations were built based on core dataset from Kekeya block, Tuha Basin; and then with BP Neutron Network method, flow unit was classified for un-cored intervals using normalized logging data, and permeability was calculated accordingly. This improved the accuracy of permeability calculation and helped a lot on un-cored reservoir evaluation. In addition, based on porosity, permeability and flow unit type, a new reservoir grading chart was set up by incorporating the testing or production data, which provides important guidance for productivity prediction and reservoir development.


Author(s):  
Boris Edgar Moafo Wembe ◽  
Olivier Cots ◽  
Bernard Bonnard

Helhmoltz-Kirchhoff equations of motions of vortices of an incompressible fluid in the plane define a dynamics with singularities and this leads to a Zermelo navigation problem describing the ship travel in such a field where the control is the heading angle. Considering one vortex, we define a time minimization problem, geometric frame being the extension of Randers metrics in the punctured plane, with rotational symmetry. Candidates as minimizers are parameterized thanks to the Pontryagin Maximum Principle as extremal solutions of a Hamiltonian vector field. We analyze the time minimal solution to transfer the ship between two points where during the transfer the ship can be either in a strong current region in the vicinity of the vortex or in a weak current region. Analysis is based on a micro-local classification of the extremals using mainly the integrability properties of the dynamics due to the rotational symmetry. The discussion is complex and related to the existence of an isolated extremal (Reeb) circle due to the vortex singularity. Explicit computation of cut points where the extremal curves cease to be optimal is given and the spheres are described in the case where at the initial point the current is weak.


2002 ◽  
Vol 5 (02) ◽  
pp. 135-145 ◽  
Author(s):  
G.R. King ◽  
W. David ◽  
T. Tokar ◽  
W. Pape ◽  
S.K. Newton ◽  
...  

Summary This paper discusses the integration of dynamic reservoir data at the flow-unit scale into the reservoir management and reservoir simulation efforts of the Takula field. The Takula field is currently the most prolific oil field in the Republic of Angola. Introduction The Takula field is the largest producing oil field in the Republic of Angola in terms of cumulative oil production. It is situated in the Block 0 Concession of the Angolan province of Cabinda. It is located approximately 25 miles offshore in water depths ranging from 170 to 215 ft. The field consists of seven stacked, Cretaceous reservoirs. The principal oil-bearing horizon is the Upper Vermelha reservoir. This paper discusses the data acquisition and integration for this reservoir only. The reservoir was discovered in January 1980 with Well 57- 02X. Primary production from the reservoir began in December 1982. The reservoir was placed on a peripheral waterflood in December 1990. Currently, the Upper Vermelha reservoir accounts for approximately 75% of the production from the field. Sound management of mature waterfloods has been identified as a key to maximizing the ultimate recovery and delivering the highest value from the Block 0 Asset.1 Therefore, the objective of the simulation effort was to develop a tool for strategic and dayto- day reservoir management with the intent of managing and optimizing production on a flow-unit basis. Typical day-to-day management activities include designing workovers, identifying new well locations, optimizing injection well profiles, and optimizing sweep efficiencies. To perform these activities, decisions must be made at the scale of the individual flow units. In general, fine-grid geostatistical models are developed from static data, such as openhole log data and core data. Recent developments in reservoir characterization have allowed for the incorporation of some dynamic data, such as pressure-transient data and 4D seismic data, into the geostatistical models. Unfortunately, pressure-transient data are acquired at a test-interval scale (there are typically 3 to 4 test intervals per well, depending on the ability to isolate different zones mechanically in the wellbore), while seismic data are acquired at the reservoir scale. The reservoir surveillance program in the Takula field routinely acquires data at the flow-unit scale. These data include openhole log and wireline pressure data from newly drilled wells and casedhole log and production log (PLT) data from producing/injecting wells. Because of the time-lapse nature of cased-hole log and PLT data, they represent dynamic reservoir data at the flow-unit scale. To achieve the objectives of the modeling effort and optimize production on a flow-unit basis, these dynamic data must be incorporated into the simulation model at the appropriate scale. When these data are incorporated into a simulation model, it is typically done during the history match. There are, however, instances when these data are incorporated during other phases of the study. The objective of this paper, therefore, is to discuss the methods used to integrate the dynamic reservoir data acquired at the flow-unit scale into the Upper Vermelha reservoir simulation model. Reservoir Geology The geology of the Takula field is described in detail in Ref. 2. The aspects of the reservoir geology that are pertinent to this paper are elaborated in this section. Reservoir Stratigraphy. The Takula field consists of seven stacked reservoirs. The principal oil-bearing horizon is the Upper Vermelha reservoir. This reservoir contains an undersaturated, 33°API crude oil. For reservoir management purposes, 36 marker surfaces have been identified in the reservoir. Flow units were then identified as reservoir units separated by areally pervasive vertical flow barriers (nonreservoir rock). This resulted in the identification of 20 flow units. The thickness of these flow units ranges from 5 to 15 ft. Reservoir Structure. The reservoir structure is a faulted anticline that is interpreted to be the result of regional salt tectonics. Closure to the reservoir is provided by faults on the southwestern and northern flanks of the structure and by an oil/water contact (OWC) on the eastern, western, and southern flanks of the structure. A structure map of the reservoir is presented in Fig. 1. Data Acquisition in the Takula Field Openhole Log Program. Most original development wells were logged with a basic log suite of resistivity/gamma ray and density/ neutron logs. In addition, the vertical wells drilled from each well jacket were logged with a sonic log and, occasionally, velocity surveys. All wells drilled after 1993 were logged with long spacing sonic and spectral gamma ray logs. In many wells drilled after December 1997, carbon/oxygen (C/O) logs have been run in open hole to distinguish between formation and injected water.3 A few recent wells have been logged with nuclear magnetic resonance (NMR) logs. The NMR log data, when integrated with data from other logs, have been of value in distinguishing free water from bound water, formation water from injection water, and reservoir rock from nonreservoir rock.


2012 ◽  
Vol 524-527 ◽  
pp. 217-220
Author(s):  
Min An Tang ◽  
Bao Ling Sun ◽  
Huan Yan Xu

Flow units are divided into E,G and P types for the Lower S2reservoir of Wen-X fault block in the Wenliu Oilfield, which are identificated based on six parameters including porosity, permeability, sandstone thickness, effective thickness, formation conductivity and flow index. A 3-D model for the flow units is established by sequential gaussian stochastic simulation approach. It is believed that type- E flow units are well exploited, with the distribution of the remaining oils related to fault as a barrier;type-G flow units are less exploited, with enrichment of remaining oil, due to the influence of interlayer or lateral heterogeneity;and type-P flow units are difficult to be exploited because of the poor percolation and a lower reserves abundance


2011 ◽  
Vol 361-363 ◽  
pp. 66-69
Author(s):  
Cong Jun Feng ◽  
Zhi Dong Bao ◽  
Ying Wang

In the case of Fourth Member of Quantou Formation (K1q4) in Well X5-16 of Fuyu Oilfield, it integrates the theory of reservoir architecture and methodology for flow-unit analysis to characterize the architectural units and their permeable features in reservoirs. As the research found, point bars are very developed in low-sinuosity meandering distributary channels. Therefore, parameter modeling for reservoirs, confined by reservoir architecture is firstly constructed from empirical formulas and integrating the data from closely-spaced wells in dense pattern area. At this basis, clustering analysis with optimized reservoir parameters help demarcate the classification of flow units and further the Kriging interpolation method is introduced for interwell flow unit prediction. Besides, the study also illustrates the relationship between the lateral accretion and the flow unit. Finally, the research achievements were confirmed by successfully matching the production data, so as to predict how the remaining oil distributes, or to adjust the development plan, as well as enhance the oil recovery.


1986 ◽  
Vol 123 (2) ◽  
pp. 105-112 ◽  
Author(s):  
P. E. Francis ◽  
P. Lyle ◽  
J. Preston

AbstractA tholeiitic andesite flow unit occurs in tholeiitic basalt lava in the Giant's Causeway region of North Antrim, Northern Ireland. It is the first example of an intermediate differentiate to be found among these quartz-normative basalts. Separate magma batches for the preceding and succeeding basalt formations are indicated by their Zr/P2O5 ratios, and by the differing fractionation trends shown by molecular proportion ratio plots. The tholeiitic andesite was probably extruded in a superheated condition with few crystal nuclei, and subsequent undercooling produced an unusual fasciculate/spherulitic texture in contrast to the very fine and even grain of the host basalt. A liquid–liquid interface between the flow units shows small-scale lava mixing.


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