the prediction of porosity is achieved by using available core and log data; however, the estimationof permeability is limited to the scare core data. hence, porosity and saturation data through theframework of flow units can be used to make an estimation of reservoir permeability. the purposeof this study is to predict the permeability of a carbonate gas reservoir by using physical-basedempiri...

Abstract The application of machine learning methods is aimed at providing efficiency and avoiding subjectivity in estimating reservoir porosity data. This study proposes the eXtreme Gradient Boost (XGBoost) algorithm which known to be effective accurate predictions a short time for porosity. model was optimized using GridSearchCV (GS) module, then applied 7 wells from Damar field, Indonesia wi...

different methods exist for the zonation of oil reservoirs based on petrophysical data and well logs. among them are: permeability-porosity cross polt, pickett and soder and gill methods. in this study a statistical zonation technique has been used for the marun and pazanan oil reservoirs in iran based on effective porosity, density, sonic, neutron and resistivity data. petrophysical interpreta...

[1] Estimation of the three-dimensional (3-D) distribution of hydrologic properties and related uncertainty is a key for improved predictions of hydrologic processes in the subsurface. However it is difficult to gain high-quality and high-density hydrologic information from the subsurface. In this regard a promising strategy is to use highresolution geophysical data (that are relatively sensiti...

In this paper we present a method to integrate well test, production, shut-in pressure, log, core, and geological data to obtain a reservoir description for the Pagerungan field, offshore Indonesia. The method computes spatial distributions of permeability and porosity and generates a pressure response for comparison to field data. This technique produced a good match with well-test data from t...

Rock classification or assigning a type or class to a specific rock sample based on petrophysical characteristics is a fundamental technique to reduce the uncertainty in prediction of reservoir properties due to heterogeneity. One of the popular approaches is to classify a reservoir rock from the fundamentals of geology and the physics of flow at pore network scale. In this approach, rocks of s...

Porosity is considered as an important petrophysical parameter in characterizing reservoirs, calculating in-situ oil reserves, and production evaluation. Nowadays, using intelligent techniques has become a popular method for porosity estimation. Support vector machine (SVM) a new intelligent method with a great generalization potential of modeling non-linear relationships has been introduced fo...

Water saturation determination is one of the most important tasks in reservoir studies to predict oil and gas in place needed to be calculated with more accuracy. The estimation of this important reservoir parameter is commonly determined by various well logs data and by applying some correlations that may not be so accurate in some real practical cases, especially for carbonate reservoirs. Sin...

The petrophysical analysis of the early Eocene Sui Main Limestone (SML) has been conducted in Kharnhak-1 well for the prospect of the hydrocarbon exploration of the Khairpur-Jacobabad High, Middle Indus Basin, Pakistan. The petrophysical analysis of SML is carried out on the basis of well logs including gamma ray, spontaneous potential, resistivity, neutron, and density logs. These analyses lea...

Petrophysical parameters such as porosity, water and oil saturations, formation resistivity factor, etc. describe the storage capability of the porous media or the capacity of rocks to hold fluids. The modified Archie’s equation . / . , also called the saturation equation, is used to determine the water saturation. Archie’s parameters, namely , , and , are sometimes assumed constant to simp...