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Abstract:
To improve the low milling rate and rapid wearing of conventional milling shoes, the cutting mechanism, structure, materials, and operating parameters of milling tools were investigated, and a novel high-efficiency milling tool was designed. The results showed that the cutter design with cutting angles of 5°−10° and a dip angle of 5° delivers the optimal cutting performance; the application with imported alloy materials is associated with the least wear rate; the milling efficiency is the highest, with alloy materials designed as multiple rhombi. Moreover, based on the downhole complex issues, three mill shoe structures were proposed, namely the flat, concave and pilot mill shoes. The field testing confirmed that the application of high-efficiency milling tools improves the average milling efficiency by 40% and the invention has the potential for application promotion.
To improve the low milling rate and rapid wearing of conventional milling shoes, the cutting mechanism, structure, materials, and operating parameters of milling tools were investigated, and a novel high-efficiency milling tool was designed. The results showed that the cutter design with cutting angles of 5°−10° and a dip angle of 5° delivers the optimal cutting performance; the application with imported alloy materials is associated with the least wear rate; the milling efficiency is the highest, with alloy materials designed as multiple rhombi. Moreover, based on the downhole complex issues, three mill shoe structures were proposed, namely the flat, concave and pilot mill shoes. The field testing confirmed that the application of high-efficiency milling tools improves the average milling efficiency by 40% and the invention has the potential for application promotion.
, Available online , doi: 10.13639/j.odpt.2020.03.021
Abstract:
Offshore gas wells are characterized by large depth, complex scale removing operation and high operation cost, so it is imperative to predict and control the scaling in the wells of deepwater gas wells. In this paper, laboratory experiment and theoretical calculation were combined to evaluate the scaling risks in the wells during the production of four typical deepwater gas wells in the South China Sea Gasfield, predict scaling velocities and scaling positions in the wells of gas wells in the process of production and analyze the scaling characteristics and laws. It is indicated that the scaling type of gas well is controlled by the compositions of formation water and the scaling velocity in the production process of gas well is mainly dependent on the deposition velocity of stable scale after the surface deposition period. The scaling difference at different well depths in the production process of deepwater gas well is mainly dominated by the temperature distribution along the well, and the scale control shall focus on the middle and lower parts of the well and the conditions of high gas production rate and high water/gas ratio. Compared with onshore gas wells, deepwater gas wells are affected more by the scaling in wells, so to keep the efficient and safe production of deepwater gas wells, it is quite important to take the scale control measures in time to prevent the formation of scale and control the scale deposition in the allowable range.
Offshore gas wells are characterized by large depth, complex scale removing operation and high operation cost, so it is imperative to predict and control the scaling in the wells of deepwater gas wells. In this paper, laboratory experiment and theoretical calculation were combined to evaluate the scaling risks in the wells during the production of four typical deepwater gas wells in the South China Sea Gasfield, predict scaling velocities and scaling positions in the wells of gas wells in the process of production and analyze the scaling characteristics and laws. It is indicated that the scaling type of gas well is controlled by the compositions of formation water and the scaling velocity in the production process of gas well is mainly dependent on the deposition velocity of stable scale after the surface deposition period. The scaling difference at different well depths in the production process of deepwater gas well is mainly dominated by the temperature distribution along the well, and the scale control shall focus on the middle and lower parts of the well and the conditions of high gas production rate and high water/gas ratio. Compared with onshore gas wells, deepwater gas wells are affected more by the scaling in wells, so to keep the efficient and safe production of deepwater gas wells, it is quite important to take the scale control measures in time to prevent the formation of scale and control the scale deposition in the allowable range.
, Available online , doi: 10.13639/j.odpt.2022.03.019
Abstract:
The macro management chart on the working condition of water injection wells is an important map that reflects the working condition of water injection wells. The construction of digital oil field provides massive data for the dynamic monitoring of water injection wells. Based on the massive data samples from water injection wells, by using the K-means clustering algorithm, macro working conditions of water injection wells, that is, the macro management chart composed the area to be reformed, the under-injection area, the normal injection area, the over-injection area, and the pending area was established. The regional boundary line was determined by using the support vector machine (SVM), and a control chart model on working condition management of injection wells was established. Using this model, the drawing method and application process of block macro management chart and single well dynamic management chart were formed. The field application shows that the macro control chart model constructed based on the big data method can reflect the relationship between the production dynamic characteristics, water injection intensity, water absorption capacity and injection completion rate of the research block and single well, which provides a decision-making basis for the next implementation of measures on water injection wells.
The macro management chart on the working condition of water injection wells is an important map that reflects the working condition of water injection wells. The construction of digital oil field provides massive data for the dynamic monitoring of water injection wells. Based on the massive data samples from water injection wells, by using the K-means clustering algorithm, macro working conditions of water injection wells, that is, the macro management chart composed the area to be reformed, the under-injection area, the normal injection area, the over-injection area, and the pending area was established. The regional boundary line was determined by using the support vector machine (SVM), and a control chart model on working condition management of injection wells was established. Using this model, the drawing method and application process of block macro management chart and single well dynamic management chart were formed. The field application shows that the macro control chart model constructed based on the big data method can reflect the relationship between the production dynamic characteristics, water injection intensity, water absorption capacity and injection completion rate of the research block and single well, which provides a decision-making basis for the next implementation of measures on water injection wells.
