scholarly journals Dynamic Variation of Water Saturation and Its Effect on Aqueous Phase Trapping Damage During Tight Sandstone Gas Well Production

ACS Omega ◽  
2021 ◽  
Vol 6 (8) ◽  
pp. 5166-5175
Author(s):  
Juan Miao ◽  
Chuanrong Zhong
Keyword(s):  
Aqueous Phase ◽  
Water Saturation ◽  
Tight Sandstone ◽  
Gas Well ◽  
Dynamic Variation ◽  
Well Production

Stress Sensitivity of Low Permeable and Water-Bearing Gas Reservoir without Gas Slippage Effect

2014 ◽  
Vol 962-965 ◽  
pp. 570-573
Author(s):  
Jian Yan ◽  
Xiao Bing Liang ◽  
Qian Wu ◽  
Qing Guo
Keyword(s):  
Water Saturation ◽  
Stress Sensitivity ◽  
Testing Methods ◽  
Gas Reservoirs ◽  
Gas Reservoir ◽  
Gas Well ◽  
Well Production ◽  
Gas Slippage ◽  
Slippage Effect ◽  
Function Relationship

Because of the gas slippage, the testing methods of stress sensitivity for gas reservoir should be different from that for oil reservoir. This text adopts the method that imposing back pressure on the outlet of testing core to weaken the gas slippage effect and tests the stress sensitivity of low permeability gas reservoirs, then analyzes the influence of permeability and water saturation on stress sensitivity. The results show that: low permeable and water-bearing gas reservoirs have strong stress sensitivity; the testing permeability has the power function relationship with net stress, compared to the exponential function, the fitting correlation coefficient is larger and more suited to the actual; the lower the permeability is and the higher water saturation is, the stronger the stress sensitivity is. The production of gas well is affected when considering the stress sensitivity, so the pressure dropping rate should be reasonable when low permeable gas reservoirs are developed. The results provide theoretical references for analyzing the well production and numerical simulation.

Economic benefit of shale gas exploitation based on back propagation neural network

2020 ◽  
Vol 39 (6) ◽  
pp. 8823-8830
Author(s):  
Jiafeng Li ◽  
Hui Hu ◽  
Xiang Li ◽  
Qian Jin ◽  
Tianhao Huang
Keyword(s):  
Neural Network ◽  
Shale Gas ◽  
Bp Neural Network ◽  
Large Scale ◽  
Linear Prediction ◽  
Back Propagation ◽  
Back Propagation Neural Network ◽  
Economic Benefits ◽  
Gas Well ◽  
Well Production

Under the influence of COVID-19, the economic benefits of shale gas development are greatly affected. With the large-scale development and utilization of shale gas in China, it is increasingly important to assess the economic impact of shale gas development. Therefore, this paper proposes a method for predicting the production of shale gas reservoirs, and uses back propagation (BP) neural network to nonlinearly fit reservoir reconstruction data to obtain shale gas well production forecasting models. Experiments show that compared with the traditional BP neural network, the proposed method can effectively improve the accuracy and stability of the prediction. There is a nonlinear correlation between reservoir reconstruction data and gas well production, which does not apply to traditional linear prediction methods

Analysis and Comparison of Seal Ability of Premium Tubing Connections under Axial Alternating Load

2013 ◽  
Vol 423-426 ◽  
pp. 2035-2039
Author(s):  
Long Cang Huang ◽  
Yin Ping Cao ◽  
Yang Yu ◽  
Yi Hua Dou
Keyword(s):  
Contact Pressure ◽  
Oil And Gas ◽  
Element Analysis ◽  
Gas Well ◽  
Cycle Number ◽  
Compression Load ◽  
Well Production ◽  
Maximum Contact ◽  
Contact Pressures ◽  
Better Than

In the process of oil and gas well production, tubing connection stand the axial alternating load during open well, shut well and fluid flow. In order to know premium connection seal ability under the loading, two types of P110 88.9mmx6.45mm premium tubing connections which called A connection and B connection are performed with finite element analysis, in which contact pressures and their the regularities distribution on sealing surface are analyzed. The results show that with the increasing of cycle number, the maximum contact pressures on sealing surface of both A connection and B connection are decreased. The decreasing of the maximum contact pressures on B connection is greater than those on A connection. With the increasing of cycle number of axial alternating compression load, the maximum contact pressure on sealing surface of A connection is decreased, and the maximum contact pressure on sealing surface of B connection remains constant. Compared the result, it shows that the seal ability of A connection is better than B connection under axial alternating tension load, while the seal ability of B connection is better than type A connection under axial alternating compression load.

Machine Learning and Artificial Intelligence Provides Wolfcamp Completion Design Insight

2021 ◽  
Author(s):  
Robert Shelley ◽  
Oladapo Oduba ◽  
Howard Melcher
Keyword(s):  
Machine Learning ◽  
Water Saturation ◽  
Saturation Pressure ◽  
Ann Model ◽  
Permian Basin ◽  
Treatment Rate ◽  
Feed Forward Neural Network ◽  
Well Production ◽  
Reservoir Type ◽  
The Impact

Abstract The subject of this paper is the application of a unique machine learning approach to the evaluation of Wolfcamp B completions. A database consisting of Reservoir, Completion, Frac and Production information from 301 Multi-Fractured Horizontal Wolfcamp B Completions was assembled. These completions were from a 10-County area located in the Texas portion of the Permian Basin. Within this database there is a wide variation in completion design from many operators; lateral lengths ranging from a low of about 4,000 ft to a high of almost 15,000 ft, proppant intensities from 500 to 4,000 lb/ft and frac stage spacing from 59 to 769 ft. Two independent self-organizing data mappings (SOM) were performed; the first on completion and frac stage parameters, the second on reservoir and geology. Characteristics for wells assigned to each SOM bin were determined. These two mappings were then combined into a reservoir type vs completion type matrix. This type of approach is intended to remove systemactic errors in measuement, bias and inconsistencies in the database so that more realistic assessments about well performance can be made. Production for completion and reservoir type combinations were determined. As a final step, a feed forward neural network (ANN) model was developed from the mapped data. This model was used to estimate Wolfcamp B production and economics for completion and frac designs. In the performance of this project, it became apparent that the incorporation of reservoir data was essential to understanding the impact of completion and frac design on multi-fractured horizontal Wolfcamp B well production and economic performance. As we would expect, wells with the most permeability, higher pore pressure, effective porosity and lower water saturation have the greatest potential for hydrocarbon production. The most effective completion types have an optimum combination of proppant intensity, fluid intensity, treatment rate, frac stage spacing and perforation clustering. This paper will be of interest to anyone optimizing hydraulically fractured Wolfcamp B completion design or evaluating Permian Basin prospects. Also, of interest is the impact of reservoir and completion characteristics such as permeability, porosity, water saturation, pressure, offset well production, proppant intensity, fluid intensity, frac stage spacing and lateral length on well production and economics. The methodology used to evaluate the impact of reservoir and completion parameters for this Wolfcamp project is unique and novel. In addition, compared to other methodologies, it is low cost and fast. And though the focus of this paper is on the Wolfcamp B Formation in the Midland Basin, this approach and workflow can be applied to any formation in any Basin, provided sufficient data is available.

Energy distribution of weak deformed rock mass and its influence on gas well productivity

2019 ◽  
Vol 7 (2) ◽  
pp. T423-T435 ◽  
Author(s):  
Shuai Yin ◽  
Yi Wang ◽  
Jingzhou Zhao ◽  
Yan Wang ◽  
Weitao Wu ◽  
...  
Keyword(s):  
Energy Density ◽  
Strain Energy Density ◽  
Strain Energy ◽  
Production Capacity ◽  
Type I ◽  
Tight Sandstone ◽  
Tectonic Zone ◽  
Gas Well ◽  
Well Productivity ◽  
Low Amplitude

Microfractures represent an important rupture type, but current studies on the construction of microscale rupture parameters and their impacts on oil and gas production capacity are relatively weak. Therefore, we constructed the strain energy density ([Formula: see text]) based on 3D finite-element method (FEM) for the tight sandstone reservoir of the Permian He8 segment in the western region of the Sulige gas field, Ordos Basin. It indicated that the [Formula: see text] values of the major production layers are mainly distributed between 0.12 and [Formula: see text]. High-[Formula: see text]-value regions ([Formula: see text]) are mainly distributed in local areas of the western, central, and eastern regions. The [Formula: see text] values are small in the northwestern part of the study area and are usually less than [Formula: see text]. There is a very good exponential correlation between the [Formula: see text] values and gas well productivity (the main controlling factor for the production capacity of the He8 tight sandstone is the gas content, and fracturing, as an engineering factor affecting capacity, has not been taken into account). The distribution of the strain energy densities also matches the low-amplitude tectonic zone well. We have developed the criterion for the discrimination of gas well productivity using the strain energy density. According to this criterion, the conformity rates of type I, type II, and type III wells are 92.3%, 73.0%, and 83.3%, respectively. The areas with [Formula: see text] values greater than [Formula: see text], especially for areas with [Formula: see text] values exceeding [Formula: see text], which should serve as the core exploration targets. The research results can effectively guide tight gas sandstone exploration in low-amplitude tectonic zones and reduce the risk of drilling.

Case Study: Single-Aqueous-Phase Retarded Acid Performance Offshore Sarawak

2021 ◽  
Vol 73 (11) ◽  
pp. 46-49
Author(s):  
J. Wu ◽  
J. Sickorez ◽  
J. Street ◽  
P. Tonmukayakul ◽  
J. Lee ◽  
...  
Keyword(s):  
Aqueous Phase ◽  
Acid Corrosion ◽  
Unit Cost ◽  
Performance Testing ◽  
Carbonate Reservoir ◽  
Surface Barrier ◽  
Program Cost ◽  
Well Production ◽  
Acid Fluid ◽  
Viable Approach

The purpose of acid stimulation of carbonate formations is to increase production. The essential component for these stimulation fluids is the carbonate-dissolving agent, which creates conductivity channels connecting the reservoir with the wellbore. Controlling the reactivity of hydrochloric acid (HCl), the most-used dissolving agent due to its high dissolving capacity, wide availability, and low unit cost, is the most viable approach to successfully stimulate a high-temperature carbonate reservoir. It is essential to retard the HCl-carbonate rock reaction to achieve the optimum balance between total fluid used and enhanced well production. It is well documented that the conventional emulsified acid exhibits high friction pressure, is cumbersome to prepare, and performs with sensitivity to a multitude of parameters. These drawbacks have prevented the industrywide adoption of this method. The recently developed single-aqueous-phase retarded acid (SAPRA) designed for primarily 15–25% HCl solutions represents a significant step forward. The first successful field implementation of SAPRA took place offshore the Malaysian state of Sarawak in early 2021. At Sarawak, the HCl reactivity was regulated and retarded by a single potent low- dosage additive, which is compatible with selected acid corrosion inhibitors, nonemulsifiers, H2S scavengers, other commonly used additives, and if necessary, friction reducers. Improving Acid Stimulation Efficiency The technical approach behind SAPRA is based on chemical technology that enables the reduction of the reaction rate and allows the control of the diffusion/mass transfer mechanism. This is key in designing the acid treatment to optimize chemical program cost and well production and has been extensively studied (Al Moajil et al. 2020; Czupski et al. 2020; Daeffler et al. 2018; and Abdrazakov et al. 2018). The technology was developed utilizing a surface barrier concept where transiently adsorbed retarder molecules adhere to a carbonate surface and thus, delay the hydrogen ion carbonate reaction over a range of acid concentrations and operating temperatures. Due to the complexity of the chemical interactions among all the additives in the acid fluid system, the selected additives must be screened to ensure mutual compatibility before conducting performance testing such as corrosion rate, calcite solubility capacity characterization, and coreflow measurements. Incompatible chemistry could lead to severe corrosion issues such as the examples shown in Table 1.

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