scholarly journals Distribution of petrophysical properties for sandy-clayey reservoirs by fractal interpolation

2012 ◽  
Vol 19 (2) ◽  
pp. 239-250 ◽  
Author(s):  
M. Lozada-Zumaeta ◽  
R. D. Arizabalo ◽  
G. Ronquillo-Jarillo ◽  
E. Coconi-Morales ◽  
D. Rivera-Recillas ◽  
...  
Keyword(s):  
Interpolation Method ◽  
Exponential Model ◽  
Effective Porosity ◽  
Well Logs ◽  
Sequential Gaussian Simulation ◽  
Depth Interval ◽  
General Point ◽  
Petrophysical Properties ◽  
Fractal Modeling ◽  
The North

Abstract. The sandy-clayey hydrocarbon reservoirs of the Upper Paleocene and Lower Eocene located to the north of Veracruz State, Mexico, present highly complex geological and petrophysical characteristics. These reservoirs, which consist of sandstone and shale bodies within a depth interval ranging from 500 to 2000 m, were characterized statistically by means of fractal modeling and geostatistical tools. For 14 wells within an area of study of approximately 6 km2, various geophysical well logs were initially edited and further analyzed to establish a correlation between logs and core data. The fractal modeling based on the R/S (rescaled range) methodology and the interpolation method by successive random additions were used to generate pseudo-well logs between observed wells. The application of geostatistical tools, sequential Gaussian simulation and exponential model variograms contributed to estimate the spatial distribution of petrophysical properties such as effective porosity (PHIE), permeability (K) and shale volume (VSH). From the analysis and correlation of the information generated in the present study, it can be said, from a general point of view, that the results not only are correlated with already reported information but also provide significant characterization elements that would be hardly obtained by means of conventional techniques.

scholarly journals An Integrated Microfacies and Well Logs-Based Reservoir Characterization of Yamama Formation, Southern Iraq

2021 ◽  
pp. 3570-3586
Author(s):  
Mohanad M. Al-Ghuribawi ◽  
Rasha F. Faisal
Keyword(s):  
Reservoir Characterization ◽  
Water Saturation ◽  
Effective Porosity ◽  
Well Logs ◽  
Petrophysical Properties ◽  
Reservoir Properties ◽  
Thin Sections ◽  
Porosity And Permeability ◽  
South Of Iraq ◽  
Southern Iraq

     The Yamama Formation includes important carbonates reservoir that belongs to the Lower Cretaceous sequence in Southern Iraq. This study covers two oil fields (Sindbad and Siba) that are distributed Southeastern Basrah Governorate, South of Iraq. Yamama reservoir units were determined based on the study of cores, well logs, and petrographic examination of thin sections that required a detailed integration of geological data and petrophysical properties. These parameters were integrated in order to divide the Yamama Formation into six reservoir units (YA0, YA1, YA2, YB1, YB2 and YC), located between five cap rock units. The best facies association and petrophysical properties were found in the shoal environment, where the most common porosity types were the primary (interparticle) and secondary (moldic and vugs) . The main diagenetic process that occurred in YA0, YA2, and YB1 is cementation, which led to the filling of pore spaces by cement and subsequently decreased the reservoir quality (porosity and permeability). Based on the results of the final digital  computer interpretation and processing (CPI) performed by using the Techlog software, the units YA1 and YB2 have the best reservoir properties. The unit YB2 is characterized by a good effective porosity average, low water saturation, good permeability, and large thickness that distinguish it from other reservoir units.

scholarly journals Hartha Formation divisions Based on Well Logs Analysis in Majnoon Oil Field, Southern Iraq

2020 ◽  
pp. 1362-1369
Author(s):  
Gheed Chaseb ◽  
Thamer A. Mahdi
Keyword(s):  
Water Saturation ◽  
Effective Porosity ◽  
Oil Field ◽  
Well Logs ◽  
Petrophysical Properties ◽  
Reservoir Properties ◽  
Thin Sections ◽  
Facies Associations ◽  
Log Interpretation ◽  
Well Logs Interpretation

This study aims to evaluate reservoir characteristics of Hartha Formation in Majnoon oil field based on well logs data for three wells (Mj-1, Mj-3 and Mj-11). Log interpretation was carried out by using a full set of logs to calculate main petrophysical properties such as effective porosity and water saturation, as well as to find the volume of shale. The evaluation of the formation included computer processes interpretation (CPI) using Interactive Petrophysics (IP) software.  Based on the results of CPI, Hartha Formation is divided into five reservoir units (A1, A2, A3, B1, B2), deposited in a ramp setting. Facies associations is added to well logs interpretation of Hartha Formation, and was inferred by a microfacies analysis of thin sections from core and cutting samples. The CPI shows that the A2 is the main oil- bearing unit, which is characterized by good reservoir properties, as indicated by high effective porosity, low water saturation, and low shale volume. Less important units include A1 and A3, because they have low petrophysical properties compared to the unit A2.

scholarly journals Evaluation of Mishrif Reservoir in Abu Amood Oil Field, Southern Iraq

2021 ◽  
pp. 4758-4768
Author(s):  
Ahmed Hussain ◽  
Medhat E. Nasser ◽  
Ghazi Hassan
Keyword(s):  
Total Porosity ◽  
Effective Porosity ◽  
Oil Field ◽  
Well Logs ◽  
Neutron Density ◽  
High Porosity ◽  
Petrophysical Properties ◽  
Density Method ◽  
Southern Iraq

     The main goal of this study is to evaluate Mishrif Reservoir in Abu Amood oil field, southern Iraq, using the available well logs. The sets of logs were acquired for wells AAm-1, AAm-2, AAm-3, AAm-4, and AAm-5. The evaluation included the identification of the reservoir units and the calculation of their petrophysical properties using the Techlog software. Total porosity was calculated using the neutron-density method and the values were corrected from the volume of shale in order to calculate the effective porosity. Computer processed interpretation (CPI) was accomplished for the five wells. The results show that Mishrif Formation in Abu Amood field consists of three reservoir units with various percentages of hydrocarbons that were concentrated in all of the three units, but in different wells. All of the units have high porosity, especially unit two, although it is saturated with water.

Monitoring of diffuse CO2 degassing at NERZ, NWRZ and NSRZ volcanic systems of Tenerife, Canary Islands

2021 ◽  
Author(s):  
Fátima Rodríguez ◽  
Eleazar Padrón ◽  
Gladys Melián ◽  
María Asensio-Ramos ◽  
Mar Alonso ◽  
...  
Keyword(s):  
Rift Zone ◽  
Emission Rate ◽  
Interpolation Method ◽  
Sampling Site ◽  
Sequential Gaussian Simulation ◽  
Rift System ◽  
Volcanic Complex ◽  
North East ◽  
The North ◽  
Volcanic Seismicity

<p>One of the main volcano-structural and geomorphological feature in Tenerife (2,034 km<sup>2</sup>) is the triple rift system, formed by aligned of hundreds of monogenetic eruptive products of shield basaltic volcanism. At the intersection of this triple rift system rises the Teide-Pico Viejo volcanic complex. These volcanic rifts are considered as active volcanic edifices. The North East volcanic Rift Zone (NERZ, 210 km<sup>2</sup>) form a main NE-SW structure. The North West volcanic Rift Zone (NWRZ, 72 km<sup>2</sup>) is oriented in NW-SE direction and the North South volcanic Rift Zone (NSRZ, 325 km<sup>2</sup>) comprises a more scattered area on the south of these monogenetic cones. The most recent eruptive activity of Tenerife has taken place in these rift systems. NERZ host the fissural eruption of Arafo-Fasnia-Siete Fuentes (1704-1705). NWRZ host two historical eruptions: Arenas Negras in 1706 and Chinyero in 1909. Recently the eruption of Boca Cangrejo (1492) has been added to the historical register through <sup>14</sup>C dating. NSRZ does not host historical volcanism, although it is recent, up to 10,000 years old.</p><p>In order to provide a multidisciplinary approach to monitor potential volcanic activity changes at the NERZ, NWRZ and NSRZ, diffuse CO<sub>2</sub> emission surveys have been undertaken since 2000, in general in a yearly basis, but with a higher frequency when seismic swarms have occurred in and around NWRZ volcano. Each study area for NERZ, NWRZ and NSRZ comprises hundreds of sampling sites homogenously distributed. Soil CO<sub>2</sub> efflux measurements at each sampling site were conducted at the surface environment by means of a portable non-dispersive infrared spectrophotometer (NDIR) LICOR Li820 following the accumulation chamber method. To quantify the CO<sub>2</sub> emission rate from the NERZ, NWRZ and NSRZ a sequential Gaussian simulation (sGs) was used as interpolation method.</p><p>The diffuse CO<sub>2</sub> emission rate for the NERZ ranged from 532 up to 2823 t d<sup>-1 </sup>between 2001 and 2020, with the highest value measured in 2020. In the case of NWRZ, the diffuse CO<sub>2</sub> emission rate ranged from 52 up to 867 t d<sup>-1 </sup>between 2000 and 2020, with the highest value measured in one of the surveys of 2005. Finally, and for NSRZ, the diffuse CO<sub>2</sub> emission rate ranged from 78 up to 819 t d<sup>-1 </sup>between 2002 and 2020, with the highest value measured in 2019. The temporal evolution of diffuse CO<sub>2</sub> emission at the NERZ, NWRZ and NSRZ shows a nice and clear relationship with the volcanic seismicity in and around Tenerife Island, which started to take place from the end of 2016. The good temporal correlation between the volcanic seismicity and the increase trend observed in the time series of diffuse CO<sub>2</sub> emission rates at NERZ, NWRZ and NSRZ is also coincident with the observed increase of diffuse CO<sub>2</sub> emission rate at the summit crater of Teide. This work demonstrates the importance of performing soil CO<sub>2</sub> efflux surveys at active rift systems in volcanic oceanic islands as an effective geochemical monitoring tool.</p>

scholarly journals 3D Petrophysical Modelling Of Queen Field, Onshore Niger Delta, Nigeria

2021 ◽  
Vol 24 (11) ◽  
pp. 1941-1947
Author(s):  
C Eze ◽  
G Emujakporue ◽  
DC Okujagu
Keyword(s):  
Seismic Data ◽  
Niger Delta ◽  
Best Practice ◽  
Total Porosity ◽  
Effective Porosity ◽  
Sequential Gaussian Simulation ◽  
Petrophysical Properties ◽  
Shale Volume ◽  
Fine Grain ◽  
Constrained Models

Petrophysical-Modelling is indispensable in upstream Projects, considering the high cost, risks and uncertainties associated with this sector. Petrophysical qualities for Queen Field was modeled using Information obtained and analyzed from well-logs and 3-D Seismic data. Coarse-grain, Medium- grain and fine-grain Sands as well as Shale were all delineated by GR log. Results of petrophysical evaluation conducted on seven reservoir intervals correlated across the field showed that; Shale volume was below 35%, Total Porosity are > 20% Effective Porosity are >15% Permeability is > 380.00mD all of this conforms to excellent reservoir quantity. Seismic interpretation showed the presence of synthetic and antithetic faults. Two horizons were mapped on seismic data and utilized for modeling. These models were the framework for facies and petrophysical properties distribution. Facies models were generated using sequential indicator simulation while petrophysical properties were generated using sequential gaussian simulation algorithm. A comparison was further done between facies constrained and non-facies constrained models. It was found that for Porosity, Permeability, Water of Saturation and Shale Volume Models not constrained to facies all showed overestimated Models, in addition Stochastic STOIIP not constrained to facies gave an Over Estimated P50 value for Surface I and O Reservoir Interval as 624.028M, 76.28MM, when compared to Stochastic Hydrocarbon STOIIP when constrained to facies that showed Stochastic P50 value of 513,247 and 67.04MM for surface I and O and Deterministic STOIIP of 742.90M and 87.88MM. This study validates the practice of constraining Petrophysical model to facies available on the field as the best practice. Keywords: Queen Field, Onshore, Niger Delta, 3D Petrophysical.

Surface diffuse degassing monitoring of the Tenerife Northeastern Rift Zone (NERZ) volcano, Canary Islands

2020 ◽  
Author(s):  
Lucía Sáez-Gabarrón ◽  
Jazlyn Beeck ◽  
Sian Reilly ◽  
Mar Alonso ◽  
Víctor Ortega-Ramos ◽  
...  
Keyword(s):  
Interpolation Method ◽  
Graphical Analysis ◽  
Point Of View ◽  
Sequential Gaussian Simulation ◽  
Contour Maps ◽  
Average Value ◽  
North East ◽  
The North ◽  
Tenerife Island ◽  
Total Data

<p>The North East Rift volcanic Zone (NERZ) of Tenerife Island is one of the three volcanic rift-zones of the island, oriented NW-SE (NWRZ), NE-SW (NERZ) and a more scattered area on the south (NSRZ). From a volcano-structural point of view, NERZ is more complex than NW or NS rifts due the existence of Pedro Gil stratovolcano that broke the main NE-SW structure. Pedro Gil Caldera was formed  0.8  Ma ago by a vertical collapse of this stratovolcano. The most recent eruptive activity along the NERZ took place during 1704 and 1705 along a 13 km of fissural eruption of Arafo-Fasnia-Siete Fuentes. Diffuse CO<sub>2</sub> emission surveys have been undertaken in a yearly basis since 2001 in order to provide a multidisciplinary approach to monitor potential volcanic activity changes at the NERZ. The aim of this study is to report the results of the last soil CO<sub>2</sub> efflux survey undertaken in summer 2019, with 639 measuring sites homogeneously distributed in an area of 210 km<sup>2</sup>. In-situ measurements of CO<sub>2</sub> efflux from the surface environment of NERZ were performed by means of a portable non-dispersive infrared spectrophotometer (NDIR) following the accumulation chamber method. Soil CO<sub>2</sub> efflux contour maps were constructed to identify spatio-temporal anomalies and to quantify the total CO<sub>2</sub> emission using the sequential Gaussian simulation (sGs) interpolation method. The CO<sub>2</sub> efflux values ranged from non-detectable (0.5 g m<sup>-2</sup> d<sup>-1</sup>) up to 72,3 g m<sup>-2</sup> d<sup>-1</sup>, with an average value of 10,9 g m<sup>-2</sup> d<sup>-1</sup>. Statistical-graphical analysis of the 2019 data show two different geochemical populations; background (B) and peak (P) represented by 70.4% and 1.9% of the total data, respectively. The geometric means of the B and P populations are 0.4 and 4.3 g m<sup>-2</sup> d<sup>-1</sup>, respectively. The diffuse CO<sub>2</sub> emission rate was estimated in 2,205 t d<sup>-1</sup>. Studying the long-term variations on the diffuse CO<sub>2</sub> emission since 2001, two main pulses are identified: one in 2007 and a second one sustained over time between 2014 and 2019. Enhanced endogenous contributions of deep-seated CO<sub>2</sub> might have been responsible for the higher CO<sub>2</sub> emissions values observed during those pulses. The 2014-2019 pulse appears to be related to the seismic activity that started taking place in Tenerife at the end of 2016. This study denotes the importance of soil CO<sub>2</sub> efflux surveys at the NERZ volcano of Tenerife Island as an effective volcanic monitoring tool.</p>

Bayesian inversion of well logs for petrophysical properties estimation

2017 ◽  
Author(s):  
Ruidong Qin ◽  
Heping Pan* ◽  
Peiqiang Zhao ◽  
Yutao Liu ◽  
Chengxiang Deng
Keyword(s):  
Well Logs ◽  
Bayesian Inversion ◽  
Petrophysical Properties

Machine Learning for Multiple Petrophysical Properties Regression Based on Core Images and Well Logs in a Heterogenous Reservoir

2021 ◽  
Author(s):  
Tao Lin ◽  
Mokhles Mezghani ◽  
Chicheng Xu ◽  
Weichang Li
Keyword(s):  
Machine Learning ◽  
Model Building ◽  
Image Features ◽  
Well Logs ◽  
Model Complexity ◽  
Rock Properties ◽  
Core Analysis ◽  
Petrophysical Properties ◽  
Blind Test ◽  
Porosity And Permeability

Abstract Reservoir characterization requires accurate prediction of multiple petrophysical properties such as bulk density (or acoustic impedance), porosity, and permeability. However, it remains a big challenge in heterogeneous reservoirs due to significant diagenetic impacts including dissolution, dolomitization, cementation, and fracturing. Most well logs lack the resolution to obtain rock properties in detail in a heterogenous formation. Therefore, it is pertinent to integrate core images into the prediction workflow. This study presents a new approach to solve the problem of obtaining the high-resolution multiple petrophysical properties, by combining machine learning (ML) algorithms and computer vision (CV) techniques. The methodology can be used to automate the process of core data analysis with a minimum number of plugs, thus reducing human effort and cost and improving accuracy. The workflow consists of conditioning and extracting features from core images, correlating well logs and core analysis with those features to build ML models, and applying the models on new cores for petrophysical properties predictions. The core images are preprocessed and analyzed using color models and texture recognition, to extract image characteristics and core textures. The image features are then aggregated into a profile in depth, resampled and aligned with well logs and core analysis. The ML regression models, including classification and regression trees (CART) and deep neural network (DNN), are trained and validated from the filtered training samples of relevant features and target petrophysical properties. The models are then tested on a blind test dataset to evaluate the prediction performance, to predict target petrophysical properties of grain density, porosity and permeability. The profile of histograms of each target property are computed to analyze the data distribution. The feature vectors are extracted from CV analysis of core images and gamma ray logs. The importance of each feature is generated by CART model to individual target, which may be used to reduce model complexity of future model building. The model performances are evaluated and compared on each target. We achieved reasonably good correlation and accuracy on the models, for example, porosity R2=49.7% and RMSE=2.4 p.u., and logarithmic permeability R2=57.8% and RMSE=0.53. The field case demonstrates that inclusion of core image attributes can improve petrophysical regression in heterogenous reservoirs. It can be extended to a multi-well setting to generate vertical distribution of petrophysical properties which can be integrated into reservoir modeling and characterization. Machine leaning algorithms can help automate the workflow and be flexible to be adjusted to take various inputs for prediction.

scholarly journals Geostatistical analysis of crop yield maps in a long term no tillage system

Bragantia ◽  
2010 ◽  
Vol 69 (suppl) ◽  
pp. 9-18 ◽  
Author(s):  
Osvaldo Guedes Filho ◽  
Sidney Rosa Vieira ◽  
Marcio Koiti Chiba ◽  
Célia Regina Grego
Keyword(s):  
Crop Yield ◽  
Crop Yields ◽  
Spherical Model ◽  
Exponential Model ◽  
Spatial And Temporal Variability ◽  
No Tillage ◽  
Yield Data ◽  
The North ◽  
Tillage System

It is known, for a long time, that crop yields are not uniform at the field. In some places, it is possible to distinguish sites with both low and high yields even within the same area. This work aimed to evaluate the spatial and temporal variability of some crop yields and to identify potential zones for site specific management in an area under no-tillage system for 23 years. Data were analyzed from a 3.42 ha long term experimental area at the Centro Experimental Central of the Instituto Agronômico, located in Campinas, Sao Paulo State, Brazil. The crop yield data evaluated included the following crops: soybean, maize, lablab and triticale, and all of them were cultivated since 1985 and sampled at a regular grid of 302 points. Data were normalized and analyzed using descriptive statistics and geostatistical tools in order to demonstrate and describe the structure of the spatial variability. All crop yields showed high variability. All of them also showed spatial dependence and were fitted to the spherical model, except for the yield of the maize in 1999 productivity which was fitted to the exponential model. The north part of the area presented repeated high values of productivity in some years. There was a positive cross correlation amongst the productivity values, especially for the maize crops.

scholarly journals Rates of consumption of atmospheric CO<sub>2</sub> through the weathering of loess during the next 100 yr of climate change

2013 ◽  
Vol 10 (1) ◽  
pp. 135-148 ◽  
Author(s):  
Y. Goddéris ◽  
S. L. Brantley ◽  
L. M. François ◽  
J. Schott ◽  
D. Pollard ◽  
...  
Keyword(s):  
Climate Change ◽  
Reaction Front ◽  
Numerical Models ◽  
Atmospheric Co2 ◽  
Co2 Production ◽  
Depth Interval ◽  
Mississippi Valley ◽  
The South ◽  
The North ◽  
The Future

Abstract. Quantifying how C fluxes will change in the future is a complex task for models because of the coupling between climate, hydrology, and biogeochemical reactions. Here we investigate how pedogenesis of the Peoria loess, which has been weathering for the last 13 kyr, will respond over the next 100 yr of climate change. Using a cascade of numerical models for climate (ARPEGE), vegetation (CARAIB) and weathering (WITCH), we explore the effect of an increase in CO2 of 315 ppmv (1950) to 700 ppmv (2100 projection). The increasing CO2 results in an increase in temperature along the entire transect. In contrast, drainage increases slightly for a focus pedon in the south but decreases strongly in the north. These two variables largely determine the behavior of weathering. In addition, although CO2 production rate increases in the soils in response to global warming, the rate of diffusion back to the atmosphere also increases, maintaining a roughly constant or even decreasing CO2 concentration in the soil gas phase. Our simulations predict that temperature increasing in the next 100 yr causes the weathering rates of the silicates to increase into the future. In contrast, the weathering rate of dolomite – which consumes most of the CO2 – decreases in both end members (south and north) of the transect due to its retrograde solubility. We thus infer slower rates of advance of the dolomite reaction front into the subsurface, and faster rates of advance of the silicate reaction front. However, additional simulations for 9 pedons located along the north–south transect show that the dolomite weathering advance rate will increase in the central part of the Mississippi Valley, owing to a maximum in the response of vertical drainage to the ongoing climate change. The carbonate reaction front can be likened to a terrestrial lysocline because it represents a depth interval over which carbonate dissolution rates increase drastically. However, in contrast to the lower pH and shallower lysocline expected in the oceans with increasing atmospheric CO2, we predict a deeper lysocline in future soils. Furthermore, in the central Mississippi Valley, soil lysocline deepening accelerates but in the south and north the deepening rate slows. This result illustrates the complex behavior of carbonate weathering facing short term global climate change. Predicting the global response of terrestrial weathering to increased atmospheric CO2 and temperature in the future will mostly depend upon our ability to make precise assessments of which areas of the globe increase or decrease in precipitation and soil drainage.

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