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Keywords: prediction
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Proceedings Papers

Paper presented at the Abu Dhabi International Petroleum Exhibition & Conference, November 9–12, 2020
Paper Number: SPE-203423-MS
... inside the tool or at the tool inlet and result in increased operational time. Predicting sanding potential thus becomes critical to achieve both operational and formation characterization objectives, especially in deep-water environments, where operation costs are high. Calculating "Critical Draw Down...
Proceedings Papers

Paper presented at the Abu Dhabi International Petroleum Exhibition & Conference, November 9–12, 2020
Paper Number: SPE-203427-MS
... was used to train the network and 20 percent was used as test data. The framework was then used to predict the bit type and correlation value for several fields which gave a correlation rate between 0.83 and 0.96 ( Bilgesu et al. 2001 ). Gidh (2012) improved the rate of penetration and weight on...
Proceedings Papers

Paper presented at the Abu Dhabi International Petroleum Exhibition & Conference, November 9–12, 2020
Paper Number: SPE-202767-MS
...) was collected from the same drilling phase that penetrated the sam complex lithology to validate the ROP model. In this study, the new contribution is to assess the poly diamond crystalline (PDC) bit design on the ROP prediction performance. Three codes were used as inputs for the ANN model...
Proceedings Papers

Paper presented at the Abu Dhabi International Petroleum Exhibition & Conference, November 9–12, 2020
Paper Number: SPE-202775-MS
... reservoir analogues from outcrops is an additional scientific challenge addressed in the ALBION RD project. Abstract Improving carbonate reservoir prediction, field development and production forecasts, especially in zones lacking data, requires novel reservoir modelling approaches including...
Proceedings Papers

Paper presented at the Abu Dhabi International Petroleum Exhibition & Conference, November 9–12, 2020
Paper Number: SPE-202792-MS
... learning reservoir surveillance artificial intelligence production control neural network reservoir simulation upstream oil & gas dynamic mode decomposition prediction permittivity production logging deep learning flow rate multiphase rate production monitoring flow metering measurement...
Proceedings Papers

Paper presented at the Abu Dhabi International Petroleum Exhibition & Conference, November 9–12, 2020
Paper Number: SPE-203283-MS
... In these equations, y i p r e d and y i exp are predicted and actual values of the target curve, respectively. The collected dataset of the 25 wells contains 8 independent variables (7 predictors and 1 target) which was divided by the ratio of 6/4 to train...
Proceedings Papers

Paper presented at the Abu Dhabi International Petroleum Exhibition & Conference, November 9–12, 2020
Paper Number: SPE-203325-MS
... determine the significance of the different parameters. The most influential parameters have been selected and used as input to the representative model in order to predict pumpout volume and corresponding contamination. In this work, multiple data-driven models such as Neural network, Random Forest, and...
Proceedings Papers

Paper presented at the Abu Dhabi International Petroleum Exhibition & Conference, November 9–12, 2020
Paper Number: SPE-203366-MS
... Using pore pressure of offset wells as reference, the pore pressure profile in Wei202H34-3 was predicted using the same model and parameters as the offsets. The prediction was based on formation correlation and projecting the well logs of offset wells to the current well, and then conducted the...
Proceedings Papers

Paper presented at the Abu Dhabi International Petroleum Exhibition & Conference, November 9–12, 2020
Paper Number: SPE-203390-MS
...) model. Abstract Closed loop reservoir management is challenged with building reliable and fast predictive reservoir models to make field decisions. Traditional numerical simulation models can be difficult to characterize, tedious to build and calibrate, and at times computationally prohibitive for...
Proceedings Papers

Paper presented at the Abu Dhabi International Petroleum Exhibition & Conference, November 9–12, 2020
Paper Number: SPE-203402-MS
... considered easiest and most economical are fresh water washes to dissolve downhole halite deposits. The main objective of this study is to increase production by optimizing washing sequences. Having an accurate washing schedules predicted allows to anticipate on production degradation and its mitigating...
Proceedings Papers

Paper presented at the Abu Dhabi International Petroleum Exhibition & Conference, November 9–12, 2020
Paper Number: SPE-203414-MS
... perception. Moreover, such models neglect the influence of geological events that are essential in characterizing and modeling carbonate reservoirs. This mentioned approach leads to conceptual errors because ideally, a reservoir model would enable heterogeneities predictability and mitigate reservoir...
Proceedings Papers

Paper presented at the Abu Dhabi International Petroleum Exhibition & Conference, November 9–12, 2020
Paper Number: SPE-203213-MS
... parameter prediction new well tight sand artificial neural network wireline log structural geology lithology classification porosity porosity classification porous gas Wireline logging is the characterization of geophysical data performed as a function of wellbore depth and is performed by...
Proceedings Papers

Paper presented at the Abu Dhabi International Petroleum Exhibition & Conference, November 9–12, 2020
Paper Number: SPE-203229-MS
... predictive and optimization model for ROP that utilizes a hybrid artificial intelligence model based on an improved genetic algorithm (IGA) and artificial neural network (ANN) for further optimization of drilling processes. Real field drilling datasets such as the bit type, bit drilling time, rotation per...
Proceedings Papers

Paper presented at the Abu Dhabi International Petroleum Exhibition & Conference, November 9–12, 2020
Paper Number: SPE-203238-MS
... avoid it, is essential. In order to achieve this objective, a proper sand production prediction analysis is required using a geomechanical model. Selection of methodology and technology will be key for accuracy of the prediction, analysis and solution. We proposed a few techniques in this article, that...
Proceedings Papers

Paper presented at the Abu Dhabi International Petroleum Exhibition & Conference, November 9–12, 2020
Paper Number: SPE-203094-MS
... Abstract Automation has impacted our everyday lives through increased speed of operations and execution of decisions. However, these processes and decisions are wholly dependent on choices made during automation model creation. Quick selection of input variables is key to the predictive...
Proceedings Papers

Paper presented at the Abu Dhabi International Petroleum Exhibition & Conference, November 9–12, 2020
Paper Number: SPE-203096-MS
... CFD methodology in an initial undeformed geometry proved to be ultra-conservative, so a new quasi dynamic mesh (QDM) methodology was developed, which yielded more realistic (albeit still conservative) erosion-depth predictions. The results revealed areas for improving the design of key components, and...
Proceedings Papers

Paper presented at the Abu Dhabi International Petroleum Exhibition & Conference, November 9–12, 2020
Paper Number: SPE-202679-MS
... fast and accurate prediction while considering combined effect of all these parameters. Here, we proposed a data driven approach based on supervised deep learning to estimate rheological property of CO 2 foam as a function of foam quality, temperature, pressure, and shear rate. We exploit deep neural...
Proceedings Papers

Paper presented at the Abu Dhabi International Petroleum Exhibition & Conference, November 9–12, 2020
Paper Number: SPE-202685-MS
... dependent on amount of available data. In general, more labelled data during training of the neural network results in accurate predictions. Therefore, seismic based rock property prediction models and their calibration needs to be fed with labelled data coming from well logs in adequate amount. The fact...
Proceedings Papers

Paper presented at the Abu Dhabi International Petroleum Exhibition & Conference, November 9–12, 2020
Paper Number: SPE-202700-MS
... to estimate K r and P c curves based on available experimental results. The values of the coefficient of determination (R2) was used to assess the accuracy and efficiency of the developed model. The respective cross plots indicate that the model is capable of making accurate predictions with error...
Proceedings Papers

Paper presented at the Abu Dhabi International Petroleum Exhibition & Conference, November 9–12, 2020
Paper Number: SPE-202708-MS
... Abstract This paper presents a data-driven model built using machine learning technique, namely Support-Vector Regression (SVR), for predicting rock mechanical properties (RMP) of tight sands and shale formations based on measured elemental information. This study utilized 324 data points...

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