Today, I continued to improve the second paper.
Summary:
I finish all improvement before 'case study'. There are now two parts left to be improved, which are 'case study' and 'conclusion'.
Tomorrow, I will try to finish all the rest part.
8/30/2017
Improve the second paper
Today, I improved part of the second paper.
Summary:
I will try to finish it on Thursday or Friday.
Tomorrow, I will continue to improve the second paper.
Summary:
I will try to finish it on Thursday or Friday.
Tomorrow, I will continue to improve the second paper.
8/29/2017
some ideas after reading papers combined with your suggestions
Today, I thought of some ideas after reading papers combined with your suggestions.
Summary:
1. CMIS: in other papers, people combine different models into CMIS like fuzzy-logic, neuro-fuzzy and ANN. Since ANN performs the best among selected models, I think one improvement may be to use different ANN models in CMIS instead of various models. For now, I have not found how to realize it in MATLAB. I will continue to look for it.
2. one way to use Vp/Vs is to predict Vp and Vp/Vs together instead of predicting Vp and Vs together. From yesterday's work, it is more accurate to predict Vp than Vs, so predicting Vp and Vp/Vs together may be a good choice.
Tomorrow, I will start to improve the second paper.
Summary:
1. CMIS: in other papers, people combine different models into CMIS like fuzzy-logic, neuro-fuzzy and ANN. Since ANN performs the best among selected models, I think one improvement may be to use different ANN models in CMIS instead of various models. For now, I have not found how to realize it in MATLAB. I will continue to look for it.
2. one way to use Vp/Vs is to predict Vp and Vp/Vs together instead of predicting Vp and Vs together. From yesterday's work, it is more accurate to predict Vp than Vs, so predicting Vp and Vp/Vs together may be a good choice.
Tomorrow, I will start to improve the second paper.
8/28/2017
predict sonic logs with basic ANN models
Today, I predicted sonic logs with basic ANN models.
Summary:
There are 13 inputs and 2 outputs (compressional and shear).
one hidden layer with 8 neurons
R2: 0.8570, 0.8184
NRMSE: 0.0631, 0.0673
two hidden layers with 9 and 5 neurons
R2: 0.8619, 0.8247
NRMSE: 0.0620, 0.0661
Asoodeh et al. (2011) improved accuracy using CMIS compared with ANN. But it is just 0.16% for compressional velocity and 0.63% for shear velocity with R2.
In our case, the accuracy is also improved by adding one more hidden layers. It is 0.57% for compressional velocity and 0.77% for shear velocity with R2.
The result shows that both of two methods improve little in accuracy and there is no need to use CMIS. Adding one more hidden layer is more efficient.
Tomorrow, I will search papers to see if I can find new methods.
Summary:
There are 13 inputs and 2 outputs (compressional and shear).
one hidden layer with 8 neurons
R2: 0.8570, 0.8184
NRMSE: 0.0631, 0.0673
two hidden layers with 9 and 5 neurons
R2: 0.8619, 0.8247
NRMSE: 0.0620, 0.0661
Asoodeh et al. (2011) improved accuracy using CMIS compared with ANN. But it is just 0.16% for compressional velocity and 0.63% for shear velocity with R2.
In our case, the accuracy is also improved by adding one more hidden layers. It is 0.57% for compressional velocity and 0.77% for shear velocity with R2.
The result shows that both of two methods improve little in accuracy and there is no need to use CMIS. Adding one more hidden layer is more efficient.
Tomorrow, I will search papers to see if I can find new methods.
8/25/2017
Possible improvement from former research
Today, I thought about possible improvement from former research about predicting sonic logs.
Summary:
1. from papers I read yesterday, most predictive models use Vp as inputs with other conventional logs to predict Vs. Most empirical equations predict Vp and Vs together with limited accuracy.
2. There is one paper where Vp and Vs are predicted together with CMIS. There are three different models in CMIS including ANN, FL (fuzzy logic) and NF (Neuro-Fuzzy) models. The accuracy of CMIS is a little higher than ANN and much higher than FL and NF. So maybe there is no need to use CMIS.
Possible improvements:
1. Just use ANN to predict Vp and Vs together instead of CMIS
2. improve the performance of ANN and obtain higher accuracy than CMIS with less time (contain more inputs, more hidden layers, predict one of Vs and Vp first and predict the other next to get higher accuracy, select the best training function)
Next week, I will see if it is possible to use ANN to obtain higher accuracy than CMIS.
Summary:
1. from papers I read yesterday, most predictive models use Vp as inputs with other conventional logs to predict Vs. Most empirical equations predict Vp and Vs together with limited accuracy.
2. There is one paper where Vp and Vs are predicted together with CMIS. There are three different models in CMIS including ANN, FL (fuzzy logic) and NF (Neuro-Fuzzy) models. The accuracy of CMIS is a little higher than ANN and much higher than FL and NF. So maybe there is no need to use CMIS.
Possible improvements:
1. Just use ANN to predict Vp and Vs together instead of CMIS
2. improve the performance of ANN and obtain higher accuracy than CMIS with less time (contain more inputs, more hidden layers, predict one of Vs and Vp first and predict the other next to get higher accuracy, select the best training function)
Next week, I will see if it is possible to use ANN to obtain higher accuracy than CMIS.
8/24/2017
literature review of sonic logs
Today, I did literature review of sonic logs.
Summary:
There are two main kinds of methods of predicting Vp and Vs.
1. data from lab measurements
1.1. multiple regression
1.1.1. Inputs: NPHI, RHOB, GR, LLD(deep laterolog, resistivity), Vp
Outputs: Vs
1.1.2. Inputs: NPHI, RHOB, Vp
Outputs: Vs
1.2. ANN
Inputs: NPHI, RHOB, Vp
Outputs: Vs
2. data from well logs
Xu-White model
In conclusion, following logs can be selected as inputs and outputs for our research.
Inputs: GR, AT10, AT90, DPHZ, NPOR, PEFZ, RHOZ, VCL
Outputs: DTCO, DTSM
In the evening, more literature review are done for predicting sonic logs.
In Oregon Basin, Wyoming, Iverson and Walker (1992), empirical equations
inputs: shale content (from GR), lithology and porosity (nuclear logs)
outputs: shear and compressional transit times
sand/shale mixture, Dvorkin and Gutierrez (2001), empirical equations
inputs: mineral properties, rock porosity and shale volume
outputs: Vp and Vs
South Texas clastics, offshore gulf of mexico clastics, Greenberg and Castagna (1992), empirical equations
inputs: lothology, porosity, water saturation, Vp
outputs: Vs
Asmari formation (carbonate reservoir rock of Iranian oil field), Asoodeh (2011), CMIS (committee machine with intelligent sustems)
inputs: NPHI, RHOB, Rt, Vsh
outputs:Vp, Vs, stoneley wave velocity
sandstone reservoir of Carnarvon Basin, Australia, Rezaee et al. (2006), CMIS (committee machine with intelligent sustems)
inputs: NPHI, Vp, GR, RHOB, Rlld
outputs: Vs
carbonate reservoir in Iran, Maleki et al. (2014), empirical correlations and AI methods (SVM, ANN)
inputs: Vp, RHOZ, GR, PHIT, Rt, HCAL
outputs: Vs
Tomorrow, I will start to build ANN for DTCO and DTSM.
Summary:
There are two main kinds of methods of predicting Vp and Vs.
1. data from lab measurements
1.1. multiple regression
1.1.1. Inputs: NPHI, RHOB, GR, LLD(deep laterolog, resistivity), Vp
Outputs: Vs
1.1.2. Inputs: NPHI, RHOB, Vp
Outputs: Vs
1.2. ANN
Inputs: NPHI, RHOB, Vp
Outputs: Vs
2. data from well logs
Xu-White model
In conclusion, following logs can be selected as inputs and outputs for our research.
Inputs: GR, AT10, AT90, DPHZ, NPOR, PEFZ, RHOZ, VCL
Outputs: DTCO, DTSM
In the evening, more literature review are done for predicting sonic logs.
In Oregon Basin, Wyoming, Iverson and Walker (1992), empirical equations
inputs: shale content (from GR), lithology and porosity (nuclear logs)
outputs: shear and compressional transit times
sand/shale mixture, Dvorkin and Gutierrez (2001), empirical equations
inputs: mineral properties, rock porosity and shale volume
outputs: Vp and Vs
South Texas clastics, offshore gulf of mexico clastics, Greenberg and Castagna (1992), empirical equations
inputs: lothology, porosity, water saturation, Vp
outputs: Vs
Asmari formation (carbonate reservoir rock of Iranian oil field), Asoodeh (2011), CMIS (committee machine with intelligent sustems)
inputs: NPHI, RHOB, Rt, Vsh
outputs:Vp, Vs, stoneley wave velocity
sandstone reservoir of Carnarvon Basin, Australia, Rezaee et al. (2006), CMIS (committee machine with intelligent sustems)
inputs: NPHI, Vp, GR, RHOB, Rlld
outputs: Vs
carbonate reservoir in Iran, Maleki et al. (2014), empirical correlations and AI methods (SVM, ANN)
inputs: Vp, RHOZ, GR, PHIT, Rt, HCAL
outputs: Vs
Tomorrow, I will start to build ANN for DTCO and DTSM.
8/23/2017
finish some tasks
Today, I finished some tasks.
Summary:
1. finish compile BHP and Hess dataset.
2. check that VPVS=DTSM/DTCO
I check it in Hess well and it is true. I did not find VPVS in BHP well. I think it also means that VPVS is obtained by DTSM/DTCO.
3. do some research on sonic logs. There are some applications for them:
quality control of transit-time logs
refinement of porosity predictions
determination of lithology
improvement of fracture detection
improvement of cement bond evaluation
Tomorrow, I will learn more about sonic logs and start to predict them by conventional logs.
Summary:
1. finish compile BHP and Hess dataset.
2. check that VPVS=DTSM/DTCO
I check it in Hess well and it is true. I did not find VPVS in BHP well. I think it also means that VPVS is obtained by DTSM/DTCO.
3. do some research on sonic logs. There are some applications for them:
quality control of transit-time logs
refinement of porosity predictions
determination of lithology
improvement of fracture detection
improvement of cement bond evaluation
Tomorrow, I will learn more about sonic logs and start to predict them by conventional logs.
8/22/2017
prepare the compilation of Hess well
Today, I prepared the compilation of Hess well.
Summary:
I have not finished it yet.
Tomorrow, I will try to finish both the Hess well and the BHP well.
Summary:
I have not finished it yet.
Tomorrow, I will try to finish both the Hess well and the BHP well.
8/21/2017
make a conclusion of the past work and think about the next step
Today, I made a conclusion of the past work and wrote my SOP. In addition, I looked into RV and RH.
Summary:
Since the application deadline of Australian universities for next Fall is in October, I have to accelerate preparing for the application materials.
In addition, I considered about predicting RH and RV. It is possible because resistivity reflects the characteristics of both formation rocks and fluids, which are related to various logs. However, since resistivity logs are not quite expensive, maybe there is little application if the research can be done.
Tomorrow, we can talk about this as well as my next step of my research.
Summary:
Since the application deadline of Australian universities for next Fall is in October, I have to accelerate preparing for the application materials.
In addition, I considered about predicting RH and RV. It is possible because resistivity reflects the characteristics of both formation rocks and fluids, which are related to various logs. However, since resistivity logs are not quite expensive, maybe there is little application if the research can be done.
Tomorrow, we can talk about this as well as my next step of my research.
8/18/2017
Finish the draft of the second paper
Today, I finished the draft of the second paper.
Summary:
It is in my email.
Next week, I will do research on RV/RH.
Summary:
It is in my email.
Next week, I will do research on RV/RH.
8/17/2017
Finish part 2 of the second paper
Today, I finished part 2 of the second paper. I am now writing part 3 (case study), which is the only part left.
Summary:
I will send you an email.
Tomorrow, I will try to finish the draft.
Summary:
I will send you an email.
Tomorrow, I will try to finish the draft.
8/16/2017
continue to write the second paper
Today, I continued to write the second paper including some of the abstract, introduction and methodology. I also changed the flowchart of the third method.
Summary:
It is in my email.
Tomorrow, I will continue to write the second paper.
Summary:
It is in my email.
Tomorrow, I will continue to write the second paper.
8/15/2017
finish the instruction and start writing other parts
Today, I finished the instruction and started writing other parts of the second paper.
Summary:
It is in my email.
Tomorrow, I will write the following parts.
Summary:
It is in my email.
Tomorrow, I will write the following parts.
8/14/2017
Write introduction of the second paper
Today, I wrote introduction of the second paper.
Summary:
It is in my email attachment.
Tomorrow, I will finish the introduction and continue to write other parts.
Summary:
It is in my email attachment.
Tomorrow, I will finish the introduction and continue to write other parts.
8/08/2017
finish changing the paper to Fuel version
Today, I finish change the paper to Fuel version.
Summary:
I will send you an email.
Tomorrow, I will improve it if you have any instructions.
Summary:
I will send you an email.
Tomorrow, I will improve it if you have any instructions.
8/07/2017
finish the first paper
Today, I finish the first paper and write a little of the second paper.
Summary:
I will send you an email.
Tomorrow, I will select one journal for the submission of the first paper.
Summary:
I will send you an email.
Tomorrow, I will select one journal for the submission of the first paper.
8/04/2017
improve all figures and some contents of paper 1
Today, I improve all figures and some contents of paper 1.
Summary:
I will send you an email.
At weekends, I will finish improving paper 1.
Summary:
I will send you an email.
At weekends, I will finish improving paper 1.
8/03/2017
finish writing conclusions of the second paper
Today, I finish writing conclusions of the second paper.
Summary;
I will send you by an email.
Tomorrow, I will improve the first paper following your instructions.
Summary;
I will send you by an email.
Tomorrow, I will improve the first paper following your instructions.
8/02/2017
plot log data and build three models for atland well
Today, I plot log data and build three models for atland well.
Summary:
I will send you by an email.
Tomorrow, I will continue to write the second paper.
Summary:
I will send you by an email.
Tomorrow, I will continue to write the second paper.
8/01/2017
build the third model for abernathy well
Today, I compared two methods to build the third model.
Summary:
method 1: train all 8 models with log data and original dielectric data as inputs, test all 8 models with log data and predicted dielectric data as inputs.
method 2: train and test all 8 models one by one with log data as predicted dielectric data as inputs.
After comparison, it shows that method 1 has much worse accuracy than method 2 does. So method 2 should be used to build the third model.
I will send you by an email.
Tomorrow, I will start to write the second paper since I have all results of figures and tables now.
Summary:
method 1: train all 8 models with log data and original dielectric data as inputs, test all 8 models with log data and predicted dielectric data as inputs.
method 2: train and test all 8 models one by one with log data as predicted dielectric data as inputs.
After comparison, it shows that method 1 has much worse accuracy than method 2 does. So method 2 should be used to build the third model.
I will send you by an email.
Tomorrow, I will start to write the second paper since I have all results of figures and tables now.
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