Lost circulation materials for deep and ultra-deep wells: A review

Pu, Lei; Xu, Peng; Xu, Mingbiao; Song, Jianjian; He, Miao

doi:10.1016/j.petrol.2022.110404

Cited by 48 publications

(22 citation statements)

References 76 publications

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“…The basic construction of a neural network is network construction, transfer function, and training method [41]. Neural networks build these 6 Geofluids network structures from neurons, including an input layer, an output layer, and one or more hidden layers. There is no connection between neurons in the same layer and forward connection between neurons in different layers [42].…”

Section: Artificial Neural Networkmentioning

confidence: 99%

“…The logistic sigmoid and hyperbolic tangent transfer functions are considered to perform well for any problem involving fault diagnosis and feature classification. Logistic Sigmoid and hyperbolic tangent transfer functions are given by equations ( 5) and (6). Both functions are plotted in Figure 9.…”

Section: Artificial Neural Networkmentioning

confidence: 99%

“…The loss-stopping material establishes a dense, high-strength loss-stopping layer to balance the wellbore liquid column pressure, thereby preventing the propagation of fractures. Corrective borehole strengthening is a method to effectively improve the fracture resistance of the rock formation by improving the formation closure stress and increasing the hoop stress in the nearwellbore area [6]. In this process, the quality of the plugging layer is related to various factors.…”

Section: Introductionmentioning

confidence: 99%

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Prediction of the Control Effect of Fractured Leakage in Unconventional Reservoirs Using Machine Learning Method

Song

et al. 2022

Geofluids

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Bridging plugging is the most used method of plugging in unconventional oil reservoirs, and many factors affect the effect of bridging and plugging. Since the laboratory cannot simulate the actual leakage size of the lost formation and the corresponding leakage plugging process at the drilling site, the laboratory experiment results cannot reflect the actual leakage plugging construction effect. Aiming at the problem of frequent fracture leakage during drilling in Chepaizi block, Xinjiang, China, this paper proposes a set of machine learning methods based on a neural network. Three types of factors and 14 parameters with a strong correlation with the leakage control effect were screened out. Three categories of factors include construction parameters, choice of plugging material, and fluid properties of the carrier fluid. The training was carried out based on the collected field data, the appropriate activation function was set, and the deep well network structure was optimized. By improving the field plugging measures in the later period, the model was verified by these actual cases, and the results showed that the established model produced the highest R 2 of 0.974, has a good fit, and predicts well.

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Section: Artificial Neural Networkmentioning

confidence: 99%

Section: Artificial Neural Networkmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Prediction of the Control Effect of Fractured Leakage in Unconventional Reservoirs Using Machine Learning Method

Song

et al. 2022

Geofluids

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“…Lost-circulation is one of the common downhole complications during the drilling process. 1,2 It is a working condition that drilling fluid leaks into the formation during the drilling process. 3,4 Lost-circulation is mainly subject to the following factors:…”

Section: Introductionmentioning

confidence: 99%

“…7 The high-precision leakage pressure prediction is the basis for preventing lost-circulation. 2 At present, the research on leakage theory is not complete, and the traditional calculation models that treat formation fracture…”

Section: Introductionmentioning

confidence: 99%

Study on the Construction Method of Leakage Pressure Body in Fractured Formation

Xu¹

2023

TPE

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Lost-circulation is one of the major challenges in fractured formations limiting the optimized fast drilling, which is prone to huge economic and environmental losses. The leakage pressure prediction has been a major concern in the industry. To solve this problem, a method for the construction of leakage pressure body in fractured formations is proposed in this paper. First, a leakage pressure prediction model for different fracture scales is optimized. Secondly, a fitted relationship between leakage pressure differential and leakage rate is developed based on the leakage data of the actual drilled wells, which is used to correct the leakage pressure in the priority formation. Finally, a three-dimensional (3D) body of regional stratigraphic leakage pressure is established based on kriging interpolation. This paper presents an example analysis of a fractured formation in the Halfaya oil field. The result shows that the modified formation leakage pressure profile matches the field drilling conditions. The 3D visualization of the regional leakage pressure provides a more intuitive understanding of the distribution of leak-prone formations in the area, which can provide a targeted decision basis for leakage prevention and plugging in the area.

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Novel smart plugging material for high‐temperature gas well

Li¹,

Zhou

Liu³

2023

Polymer Engineering & Sci

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A novel smart material is developed, which is synthesized by succinic anhydride, epoxy resin, and zinc acetylacetone hydrate. The smart material has excellent properties of self‐healing, shape memory, and degradation. The experimental results of performance characterization show that the material has good thermal stability. The glass transition temperature is adjustable between 100 and 120°C, and the storage modulus can reach 20 GPa. The maximum thermal expansion at 50°C is less than 15%, the thermal expansion equilibrium time at 120°C is less than 5 min, and the maximum thermal expansion is 131%. The stress relaxation time at 120°C is more than 2 h, which can slowly self‐heal on the basis of maintaining the mechanical strength. When the NaOH content is 1.5%, the degradation equilibrium can be reached in about 3 h, and the maximum degradation rate is 86%. The comprehensive performance evaluation shows that after hot rolling at 120°C/16 h, the material has no effect on the rheology and filtration properties. When plugging the fracture width of 5 × 4 mm, the pressure bearing capacity reaches 10 MPa. Its main mechanism is temperature‐sensitive expansion, and the stress relaxation effect heals and blocks the micro pore throat.

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Lost circulation materials for deep and ultra-deep wells: A review

Cited by 48 publications

References 76 publications

Prediction of the Control Effect of Fractured Leakage in Unconventional Reservoirs Using Machine Learning Method

Prediction of the Control Effect of Fractured Leakage in Unconventional Reservoirs Using Machine Learning Method

Study on the Construction Method of Leakage Pressure Body in Fractured Formation

Novel smart plugging material for high‐temperature gas well

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