Predicting Strata Temperature Distribution from Drilling Fluid Temperature

Shuanhai, Xu; Ba, Junjie; XianFeng, Chen; Zheng, Ting; Yang, Yaochi; Guo, Liang

doi:10.18280/ijht.340227

Cited by 6 publications

(4 citation statements)

References 20 publications

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“…The C-M Structural Belt is formed through the collision between two microcontinents within the remnant Paleo-Tethys Ocean realm. Despite the complex tectonics, the internal structure of the structural belt can be clearly identified (Xu et al, 2016).…”

Section: Geological Backgroundmentioning

confidence: 99%

“…(Eq.1) where h is the elevation of sampling point; δG is the δ 18 O (δD) in the groundwater; δP is the δ 18 O (δD) in the meteoric water around the sampling point; k is the elevation gradient of δ 18 O (or δD) in the meteoric water (‰/100m). Using Equation (1), the H values of hot springs in the research area were computed with K=−2.6‰/100m and δD =−63.5‰ (Xu et al, 2016).…”

Section: Oxygen Isotope Shift and Water-rock Interactionmentioning

confidence: 99%

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Geochemical Features, Isotope Compositions and Environmental Impacts of Hot Springs in Kejie Fault and Changning-Menglian Structural Belt

Ba¹

2019

Appl. Ecol. Env. Res.

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To disclose the exact geochemical features of the hot springs in western Yunnan, China, this paper reviews the geological settings of Changning County, western Yunnan, and analyzes the geochemical features of local hot springs, which are controlled by Kejie Fault and Changning-Menglian (C-M) Structural Belt. On this basis, the author explored the isotopes of H, O, C, recharge source, recharge elevation circulation path and formation age of the geothermal flow, examined the main chemical process in the geothermal flow movement, especially in the mixing process, and determined the geochemical formation model and geological settings of the fault-controlled geothermal field in the research area. The results show that the hot springs are typical fault-controlled geothermal resources; the meteoric water is the main supply source of the hot springs; the hot springs are neither volcanic nor magmatic; despite the slight difference in activities and formation causes, the hot springs in both western and eastern parts of the research area were recharged by paleo-precipitation recharge before Late Pleistocene.

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Section: Geological Backgroundmentioning

confidence: 99%

Section: Oxygen Isotope Shift and Water-rock Interactionmentioning

confidence: 99%

Geochemical Features, Isotope Compositions and Environmental Impacts of Hot Springs in Kejie Fault and Changning-Menglian Structural Belt

Ba¹

2019

Appl. Ecol. Env. Res.

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“…In addition, the OBM showcases excellent filtration property as its filtrate volume is only 3.4-5.6 mL under hightemperature (150 C) and high-pressure (3.5 MPa). The hightemperature and high-pressure condition are usually encountered when drilling deep formation [14,15]. To better characterize the flat rheology of the proposed flat-rheology oil-based drilling fluid (FR-OBM), the author compares the rheological properties of the FR-OBM (1.8 g/cm 3 ) and those of the conventional OBM.…”

Section: Evaluation Of Rheological and Filtration Propertiesmentioning

confidence: 99%

Flat-rheology oil-based drilling fluid for deepwater drilling

Zhao¹,

Qiu²,

Xu³

et al. 2017

IJHT

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In offshore deepwater drilling, the temperature is rather low near the seabed. The resulting thickening of conventional oil-based drilling fluid causes increase in equivalent circulating density. When the density surpasses the formation fracture pressure gradient, a series of problems, including lost circulation, may occur, causing huge economic losses. A desirable drilling fluid is desperately needed to solve the rheology-related problems. In view of this, this paper analyzes how oil-based drilling fluid acquires the flat-rheology characteristics, and selects preferred additives, e.g. base oil, emulsifier, organic clay and weighting materials, based on their effects on the rheological properties of drilling fluid. On this basis, the author successfully synthetizes a rheology modifier and develops a flat-rheology oil-based drilling fluid. The performance of the proposed drilling fluid is experimentally evaluated. The results indicate that the variations of the yield point, 10-min gel and θ6 reading of the proposed drilling fluid are controlled within 25% in the temperature range of 4-75 ℃ when the density is below 2.1 g/cm 3 . Besides, the proposed drilling fluid boasts good shale inhibition and filtration performance as well as strong contamination resistance to NaCl, CaCl2 and drill cuttings. In this way, this paper provides a desirable solution to rheology-related problems in deepwater drilling.

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“…The prediction model was created to investigate the impact of the surrounding rock's radius of drilling activity. Last but not least, the difference in error between the measured temperatures and the model that was developed is less than 10%, showing that the predicted model has a good ability to forecast the geothermal gradient 12 .…”

Section: Introductionmentioning

confidence: 97%

Multilayer Perceptron Artificial Neural Network (Mlpann) Model to Predict Temperature During Rotary Drilling

Varadaraj,

Vijay Kumar,

Chethan

et al. 2023

jmmf

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In this paper, a multilayer perceptron neural network has been used to represent temperature measurement during rotary drilling of five types of rock samples. To forecast the temperature at various thermocouple depths, the experimentally collected data was standardized. Indicators of model performance was also obtained in order to assess the correctness of the model. One hidden layer and one output layer were employed with MLPANN, which has ten input parameters (bit diameter (DD), Spindle Speed (SS), Penetration Rate (PR), thrust, and torque) and rock properties. Levenberg Marquardt learning algorithm with transfer function of logsig is the most optimal neuron number of 10-16-1 was successfully forecasting the temperature with a correlation of 0.9936 and 0.9941 for training and testing algorithm during drilling after analysis based on the trial-and- error approach to identify the optimum algorithm. Ten input parameters, a logsig sigmoid transfer function, and the trainlm algorithm in this study provide good prediction ability with tolerable accuracy.

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Predicting Strata Temperature Distribution from Drilling Fluid Temperature

Cited by 6 publications

References 20 publications

Geochemical Features, Isotope Compositions and Environmental Impacts of Hot Springs in Kejie Fault and Changning-Menglian Structural Belt

Geochemical Features, Isotope Compositions and Environmental Impacts of Hot Springs in Kejie Fault and Changning-Menglian Structural Belt

Flat-rheology oil-based drilling fluid for deepwater drilling

Multilayer Perceptron Artificial Neural Network (Mlpann) Model to Predict Temperature During Rotary Drilling

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