The New Interference Test: Reservoir Connectivity Information from Downhole Temperature Data

Hutchinson, David Anthony; Kuramshina, Najiya; Sheydayev, Ali; Day, Simon N.J.

doi:10.2523/11672-ms

Cited by 9 publications

(3 citation statements)

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“…Permanent bottom-hole pressure and temperature gauges are installed in all ACG wells to measure flowing bottom-hole temperature (FBHT), data from which is being used extensively for surveillance. These reveal water injectors that impact producers, interference among producers, and provide well performance diagnostics in ACG (Hutchinson et al, 2007). In [2006][2007], studies using Azeri 3D thermal simulation modelling was performed, which allowed confirmation of most of the processes and observations presented in this work.…”

Section: Re-allocation Of Gasmentioning

confidence: 79%

History of History Match in Azeri Field

Ibrahimov¹

2015

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Modern reservoir development could not happen without building and using 3-phase 3-D simulation models and predicting the future performance of the field using powerful computer technologies. Long term production and injection profile forecasts for the Azeri field have been carried out through usage of simulation models from 2001. Since production from 2005 Azeri models have been history matched on an annual basis. While matching the model data to the actual field observed data, surveillance and performance learnings have been an integral part of the process in order to obtain representative and satisfactory results.In the current work, the challenges and problems faced, as well as the success of the history match process for the Azeri field are described. Along with discussion of applied techniques and obtained results, recommendations on matching complex reservoir simulation models based on several years experience of history matching process in the Azeri field are offered.

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Section: Re-allocation Of Gasmentioning

confidence: 79%

History of History Match in Azeri Field

Ibrahimov¹

2015

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“…Zhao et al [24] proposed the Interwell Numerical Simulation Model (INSIM), which has less computational effort than before and could be used as a calculation tool to obtain the reservoir performance under waterflooding conditions. The reservoir numerical simulation method can quantitatively evaluate the connectivity and its dynamic changes, but it is time-consuming and complex to build the model, although there are other types of methods to analyze interwell connectivity, such as 4D-seismic data method [25], bottom-hole-temperature data method [26], and neural network(NN) method [27]. Due to the high cost of seismic surveys, high requirements for temperature monitors, and tedious calculation steps of a neural network, these methods cannot perfectly solve the problems of the oil field.…”

Section: Introductionmentioning

confidence: 99%

Analysis of Interwell Connectivity of Tracer Monitoring in Carbonate Fracture-Vuggy Reservoir: Taking T-Well Group of Tahe Oilfield as an Example

et al. 2021

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Carbonate fracture-vuggy reservoirs are one of the hot spots in oil and gas exploration and development. However, it is extremely difficult to describe the internal spatial structure of the fracture-vuggy unit and understand the interwell connection relationship. As a method to measure reservoir characteristics and feedback reservoir production information directly according to the detected concentration curve, interwell tracer technology provides a direct measure for people to understand the law of oil-water movement and reservoir heterogeneity and is widely used in various domestic oil fields. Based on the flow law of tracer and the CFD flow simulation basic model, this paper establishes the physical conceptual model and studies the influence of three physical parameters (the flow velocity of the fluid passing through the connected channel, diameter of the connected channel, and length of the connected channel) on the concentration curve at the outlet. In addition, the influence of different interwell connection modes on tracer concentration was studied and classified scientifically. According to the simulation, the tracer concentration curve can be classified into three types: unimodal curve, bimodal curve, and multimodal curve. Finally, the injection-production well group in the T-well area of the Tahe Oilfield is taken as an example, the connection mode between injection and production wells in this well area is further discussed and has been verified, which can be used as a reference for the connectivity analysis of similar carbonate reservoirs.

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“…However, well performance data along with pressure and later gas tracer data suggested Central Azeri (CA) gas injectors were infact also impacting the North Flank (NF) of East Azeri. The Bottom Hole Temperature (BHT) data from 4 EA producers closest to the CA sector showed decrease in BHT temperature of those wells nearest the gas injector once GI started-up ( Figure 6) (Hutchinson et al, 2007). It was noted that the injection rates into the closest water injectors and producers had remained relatively stable with no change in choke size.…”

mentioning

confidence: 97%

Surveillance Helps to Get a Better Understanding of Reservoir Connectivity in Azeri Part of ACG

Kuramshina¹,

Ibrahimov²

2015

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Accurate and timely information is essential to monitor, control and manage reservoir and well performance. At the present, production and reservoir engineers as well as production geologists have a challenging task of managing oil and gas reservoirs. This requires a broad knowledge of the reservoir supported by fit-for-purpose integrated technologies and real time access to relevant data. In the Azeri-Chirag-Gunashli (ACG) field development, downhole information is commonly acquired through uses of LWD (logging while drilling) tools to obtain a standard log suite and obtain formation pressure measurement, production logging and well testing. In addition, Downhole Temperature Sensors (DTS) has been installed on someACG wells to provide continuous temperature readings across the reservoir so as to obtain critical understanding of reservoir behaviour, connectivity and fluid distribution.ACG structure is located in the offshore of Azerbaijan part of the South Caspian Basin (Figure 1). The structure is an elongate anticline with 3 main accumulations ( Figure 2): 1). Shallow Water Gunashli (SWG) is in the northwest operated by SOCAR and on production since 1980; Deep Water Gunashli (DWG) extended from SWG to the east and became a part of ACG field operated by AIOC with production start-up in 2008; 2). Chirag situated in the centre of the structure that has been on production since 1997; 3). Azeri is in the south east which is in production since 2005(Wethington et al., 2002. ACG structure is complicated by the presence of several mud volcanoes and series of faults and seismic elements cutting field along the length. Development of field is under 30 years PSA that expires in 2024.This field contains 16 hydrocarbon-bearing reservoirs of Pliocene age. Each of the reservoirs is regionally identifiable, laterally extensive and correlatable within the long distance. They comprise stacked fluvial-deltaic sandstones deposited by the paleo-Volga delta, flowed from the north to the south into the lacustrine South Caspian Basin.The main producing interval in Azeri field is a Fasila reservoir that has been subdivided into 5 sublayers (Fasila A,B,C,D, & E) based on the first appraisal well stratigraphy. A stratigraphic section of Fasila reservoir from one of ACG wells shown on Figure 3 illustrates high net-to-gross (NTG) Fasila B and Fasila D sublayers separated by lower NTG Fasila A, C and Fasila E layers.Azeri development proceeds under crestal gas and peripheral water injection support. Therefore understanding of compartmentalization of the structure plays significant role in production efficiency.

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The New Interference Test: Reservoir Connectivity Information from Downhole Temperature Data

Cited by 9 publications

References 0 publications

History of History Match in Azeri Field

History of History Match in Azeri Field

Analysis of Interwell Connectivity of Tracer Monitoring in Carbonate Fracture-Vuggy Reservoir: Taking T-Well Group of Tahe Oilfield as an Example

Surveillance Helps to Get a Better Understanding of Reservoir Connectivity in Azeri Part of ACG

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