1-20 of 81
Keywords: neural network
Close
Follow your search
Access your saved searches in your account

Would you like to receive an alert when new items match your search?
Close Modal
Sort by
Proceedings Papers

Paper presented at the SPWLA 63rd Annual Logging Symposium, June 11–15, 2022
Paper Number: SPWLA-2022-0103
... and nonlinear problem, with the solution being possibly nonunique. The models introduced here comprise neural networks with dense hidden layers and nonlinear activation functions. Each model simultaneously provides an estimate of a matrix property value and its uncertainty, which are optimized together...
Proceedings Papers

Paper presented at the SPWLA 63rd Annual Logging Symposium, June 11–15, 2022
Paper Number: SPWLA-2022-0105
... classification, we have developed an algorithm using a supervised machine-learning approach. A neural network classifier was trained using a large volume of synthetic dispersions. The training data are generated using randomly sampled input physical parameters covering effective borehole ovality model...
Proceedings Papers

Paper presented at the SPWLA 63rd Annual Logging Symposium, June 11–15, 2022
Paper Number: SPWLA-2022-0106
... reservoir characterization production control machine learning drilling data acquisition log analysis neural network artificial intelligence borehole imaging wellbore seismic production monitoring reservoir surveillance deep learning real time system drilling measurement well...
Proceedings Papers

Paper presented at the SPWLA 63rd Annual Logging Symposium, June 11–15, 2022
Paper Number: SPWLA-2022-0107
... in lithofacies recognition. Nevertheless, prevailing machine learning models such as CNN (Convolutional Neural Network) and DNN (Deep Neural Network) still show some disadvantages, such as: significant amounts of human interpreted data are required for data labeling, which means the accuracy level of model...
Proceedings Papers

Paper presented at the SPWLA 63rd Annual Logging Symposium, June 11–15, 2022
Paper Number: SPWLA-2022-0112
... and in automated workflows, multiple interpretations are seldom used. We describe a deep neural network (DNN) that outputs a selected number of stratigraphic interpretations using a single evaluation of the input log data in two milliseconds. The input data defined prior to training consists of one or several log...
Proceedings Papers

Paper presented at the SPWLA 63rd Annual Logging Symposium, June 11–15, 2022
Paper Number: SPWLA-2022-0114
... of machine learning to solve the above problems. A long short-term memory network (LSTM) is used to characterize the time series characteristics of logs varying with depth domain. The kernel of the convolutional neural network (CNN) is used to slide on log curves to characterize their relationships...
Proceedings Papers

Paper presented at the SPWLA 63rd Annual Logging Symposium, June 11–15, 2022
Paper Number: SPWLA-2022-0115
... reservoir characterization production control well logging reservoir surveillance machine learning log analysis production monitoring deep learning neural network wellbore seismic spwla-2022-0115 spwla 63 feature map university hydraulic fracturing borehole imaging artificial...
Proceedings Papers

Paper presented at the SPWLA 63rd Annual Logging Symposium, June 11–15, 2022
Paper Number: SPWLA-2022-0122
... (A-Sands), algorithm was developed, which employs a trained, Mugrosa (B-Sands) and La Paz (C-Sands), deposited in deep-learning artificial neural network (ANN) to invert the Paleogene period. These sands are typically isolated the large quantity of data acquired. The algorithm by interbedded, impermeable...
Proceedings Papers

Paper presented at the SPWLA 63rd Annual Logging Symposium, June 11–15, 2022
Paper Number: SPWLA-2022-0125
... solutions that have been widely adopted within the data science and machine learning domains. To evaluate the impact of missing data on machine learning models, three commonly used algorithms, namely support vector regression, random forests, and artificial neural networks, were adopted for the prediction...
Proceedings Papers

Paper presented at the SPWLA 63rd Annual Logging Symposium, June 11–15, 2022
Paper Number: SPWLA-2022-0129
... processes and their correlation with the pre-salt carbonates reservoir quality, but to establish a more efficient, reliable method for borehole image interpretation in general. neural network statistics tsne reservoir characterization upstream oil & gas machine learning structural geology...
Proceedings Papers

Paper presented at the SPWLA 63rd Annual Logging Symposium, June 11–15, 2022
Paper Number: SPWLA-2022-0024
... by the application of an Artificial Neural Network (ANN) whose performance is applicable for real-time applications. Injection water override and the base of the reservoir boundary were detected using 1D inversions along the horizontal borehole at distances of 14-43 ft and 6-20 ft TVD respectively. Continuous...
Proceedings Papers

Paper presented at the SPWLA 63rd Annual Logging Symposium, June 11–15, 2022
Paper Number: SPWLA-2022-0067
... promising machine-learning (ML) methods for predicting missing logs. We include the following methods in the comparison: the window-based convolutional neural network autoencoder (WAE), the pointwise fully connected autoencoder (PAE), and the tree-based pointwise eXtreme Gradient Boosting (XGBoost). We also...
Proceedings Papers

Paper presented at the SPWLA 63rd Annual Logging Symposium, June 11–15, 2022
Paper Number: SPWLA-2022-0070
... by the first step and trains a convolutional neural network (CNN) with a U-Net architecture to identify and correct systematic errors such as shifts, gains, random noises, and small local disturbances. The training process is self-supervised and does not require any human labels. This self-supervised deep...
Proceedings Papers

Paper presented at the SPWLA 63rd Annual Logging Symposium, June 11–15, 2022
Paper Number: SPWLA-2022-0082
... well logging log analysis machine learning artificial intelligence reservoir characterization neural network spwla-2022-0082 statistical fluctuation formation condition structural geology annual logging symposium spwla 63 interpretation spectrum east china deep learning accuracy...
Proceedings Papers

Paper presented at the SPWLA 63rd Annual Logging Symposium, June 11–15, 2022
Paper Number: SPWLA-2022-0095
... and Basic logs as input, improving the recognition of the textural heterogeneities and refine the traditional Rock typing of these complex Pre-Salt carbonate reservoirs. well logging neural network log analysis complex reservoir upstream oil & gas barra velha formation amplitude brazil...
Proceedings Papers

Paper presented at the SPWLA 63rd Annual Logging Symposium, June 11–15, 2022
Paper Number: SPWLA-2022-0097
.... flowline corrosion data mining subsurface corrosion well integrity anomaly machine learning artificial intelligence deep learning segmentation detection pipeline corrosion neural network riser corrosion segmentation map axial groove materials and corrosion wellbore design spwla-2022-0097...
Proceedings Papers

Paper presented at the SPWLA 63rd Annual Logging Symposium, June 11–15, 2022
Paper Number: SPWLA-2022-0098
... to minimize data storage, and if using multiple sensors only the best sensor reading for each depth can be stored and sent to the interpreter. To create this scoring network two main problems had to be overcome: how to capture the preferences of the experts, and how to train a neural network to replicate...
Proceedings Papers

Paper presented at the SPWLA 62nd Annual Logging Symposium, May 17–20, 2021
Paper Number: SPWLA-2021-0033
...% to make them more realistic like downhole logs. The synthetic conductivity and permittivity logs are used as inputs in a neural network application to explore possible correlations with water-filled porosity. It is found that while the conductivity and permittivity logs are generated from randomly...
Proceedings Papers

Paper presented at the SPWLA 62nd Annual Logging Symposium, May 17–20, 2021
Paper Number: SPWLA-2021-0036
... neural network accuracy spwla-2021-0036 machine learning model outlier noise subset nd annual logging symposium interpretation well log data algorithm dataset SPWLA 62nd Annual Logging Symposium, May 17-20, 2021 DOI: 10.30632/SPWLA-2021-0036 DATA QUALITY CONSIDERATIONS FOR PETROPHYSICAL...
Proceedings Papers

Paper presented at the SPWLA 62nd Annual Logging Symposium, May 17–20, 2021
Paper Number: SPWLA-2021-0003
... speed upstream oil & gas phase velocity reservoir surveillance neural network reservoir characterization spwla 62 well logging underbalanced drilling frequency nd annual logging symposium spwla-2021-0003 spinner velocity doppler frequency shift particle velocity measurement doppler...

Product(s) added to cart

Close Modal