A new correlation for water saturation calculation in gas shale reservoirs based on compensation of kerogen-clay conductivity

Determination of water saturation in gas shale reservoirs is a very challenging issue due to the incomplete understanding of the non-Archie components. Kerogen and clay content are the two main factors controlling the conductivity of gas shales and resistivity log responses. The presence of clays as conductive materials causes excessive conductivity for the rock that result in an overestimation of water saturation calculation. On the other hand, the presence of solid kerogen has an opposite effect to clays and causes reduction of rock conductivity and thus underestimation of water saturation.In this research, attempts have been made to develop an effective equation for water saturation determination in gas shale reservoirs based on compensation of kerogen and shale conductivities. The new equation is able to handle both high and low conductivity components. The proposed approach makes one step ahead towards reducing uncertainty in the petrophysical evaluation of gas shale reservoirs. Being independent of formation water resistivity and Archie parameters are of the important and effective aspects of the introduced equation in water saturation calculation of gas shale reservoirs.Finally, the kerogen-clay compensation equation has successfully been applied to the determination of water saturation in the Goldwyer shale formation, Canning basin, Western Australia

Intelligent sequence stratigraphy through a wavelet-based decomposition of well log data

Identification of sequence boundaries is an important task in geological characterization of gas reservoirs. In this study, a continuous wavelet transform (CWT) approach is applied to decompose gamma ray and porosity logs into a set of wavelet coefficients at varying scales. A discrete wavelet transform (DWT) is utilized to decompose well logs into smaller frequency bandwidths called Approximations (A) and Details (D). The methodology is illustrated by using a case study from the Ilam and upper Sarvak formations in the Dezful embayment, southwestern Iran. Different graphical visualization techniques of the continuous wavelet transform results allowed a better understanding of the main sequence boundaries. Using the DWT, maximum flooding surface was successfully recognised from both highest frequency and low frequency contents of signals. There is a sharp peak in all A&D corresponding to the maximum flooding surface (MFS), which can specifically be seen in fifth Approximation (a5), fifth Detail (d5), fourth Detail (d4) and third Detail (d3) coefficients. Sequence boundaries were best recognised from the low frequency contents of signals, especially the fifth Approximation (a5). Normally, the troughs of the fifth Approximation correspond to sequence boundaries where higher porosities developed in the Ilam and upper Sarvak carbonate rocks. Through hybridizing both CWT and DWT coefficient a more effective discrimination of sequence boundaries was achieved. The results of this study show that wavelet transform is a successful, fast and easy approach for identification of the main sequence boundaries from well log data. There is a good agreement between core derived system tracts and those derived from decomposition of well logs by using the wavelet transform approach

Estimation of vitrinite reflectance from well log data

Vitrinite reflectance (VR) data provide important information for thermal maturity assessment and source rock evaluation. The current study introduces a practical method for vitrinite reflectance determination from sonic and resistivity logs. The main determinant factor of the method is ΔRRS which is defined as the separation between cumulative frequency values of resistivity ratio (RR) and sonic log data. The values of ΔRRS range from −1 at ground level to +1 at bottom hole. The crossing point depth of the DT and RR cumulative frequency curves, where ΔRRS=0, indicates the onset of oil generation window. From the surface (ground level) to the crossing point depth ΔRRS takes negative values indicating organic material diagenesis window. Below the crossing point depth ΔRRS turns into positive values showing thermally-mature organic matter within the catagenesis window. Vitrinite reflectance measurements revealed strong exponential relationships with the calculated ΔRRS data. Accordingly, a new calibration chart was proposed for VR estimation based on ΔRRS data. Finally, an equation is derived for vitrinite reflectance estimation from ΔRRS and geothermal gradient. The proposed equation works well in the event of having limited VR calibration data

A Committee Machine with Intelligent Systems for Estimation of Total Organic Carbon Content from Petrophysical Data: an Example from Kangan and Dalan Reservoirs in South Pars Gas Field, Iran

Total Organic Carbon (TOC) content present in reservoir rocks is one of the important parameters which could be used for evaluation of residual production potential and geochemical characterization of hydrocarbon bearing units. In general, organic rich rocks are characterized by higher porosity, higher sonic transit time, lower density, higher gamma-ray, and higher resistivity than other rocks. Current study suggests an improved and optimal model for TOC estimation by integration of intelligent systems and the concept of committee machine with an example from Kangan and Dalan Formations, in South Pars Gas Field, Iran. This committee machine with intelligent systems (CMIS) combines the results of TOC predicted from intelligent systems including fuzzy logic (FL), neuro-fuzzy (NF), and neural network (NN), each of them has a weight factor showing its contribution in overall prediction. The optimal combination of weights is derived by a genetic algorithm (GA). This method is illustrated using a case study. One hundred twenty-four data points including petrophysical data and measured TOC from three wells of South Pars Gas Field were divided into eighty-seven training sets to build the CMIS model and thirty-seven testing sets to evaluate the reliability of the developed model. The results show that the CMIS performs better than any one of the individual intelligent systems acting alone for predicting TOC

Prediction of shear wave velocity from petrophysical data utilizing intelligent systems: An example from a sandstone reservoir of Carnarvon Basin, Australia

Shear wave velocity associated with compressional wave velocity can provide the accurate data for geophysical study of a reservoir. These so called petroacoustic studies have important role in reservoir characterization such as lithology determination, identifying pore fluid type, and geophysical interpretation. In this study, a fuzzy logic, a neuro-fuzzy and an artificial neural network approaches were used as intelligent tools to predict shear wave velocity from petrophysical data. The petrophysical data of two wells were used for constructing intelligent models in a sandstone reservoir of Carnarvon Basin, NW Shelf of Australia. A third well of the field was used to evaluate the reliability of the models. The results show that intelligent models have been successful for prediction of shear wave velocity from conventional well log data

A committee neural network for prediction of normalized oil content from well log data: An example from South Pars Gas Field, Persian Gulf

Normalized oil content (NOC) is an important geochemical factor for identifyingpotential pay zones in hydrocarbon source rocks. The present study proposes an optimaland improved model to make a quantitative and qualitative correlation between NOC andwell log responses by integration of neural network training algorithms and thecommittee machine concept. This committee machine with training algorithms (CMTA)combines Levenberg-Marquardt (LM), Bayesian regularization (BR), gradient descent(GD), one step secant (OSS), and resilient back-propagation (RP) algorithms. Each ofthese algorithms has a weight factor showing its contribution in overall prediction. Theoptimal combination of the weights is derived by a genetic algorithm. The method isillustrated using a case study. For this purpose, 231 data composed of well log data andmeasured NOC from three wells of South Pars Gas Field were clustered into 194modeling dataset and 37 testing samples for evaluating reliability of the models. Theresults of this study show that the CMTA provides more reliable and acceptable resultsthan each of the individual neural networks differing in training algorithms. Also CMTAcan accurately identify production pay zones (PPZs) from well logs

Seismic velocity deviation log: An effective method for evaluating spatial distribution of reservoir pore types

Velocity deviation log (VDL) is a synthetic log used to determine pore types in reservoir rocks based on a combination of the sonic log with neutron-density logs. The current study proposes a two step approach to create a map of porosity and pore types by integrating the results of petrographic studies, well logs and seismic data. In the first step, velocity deviation log was created from the combination of the sonic log with the neutron-density log. The results allowed identifying negative, zero and positive deviations based on the created synthetic velocity log. Negative velocity deviations (below − 500 m/s) indicate connected or interconnected pores and fractures, while positive deviations (above + 500 m/s) are related to isolated pores. Zero deviations in the range of [− 500 m/s, + 500 m/s] are in good agreement with intercrystalline and microporosities. The results of petrographic studies were used to validate the main pore type derived from velocity deviation log. In the next step, velocity deviation log was estimated from seismic data by using a probabilistic neural network model. For this purpose, the inverted acoustic impedance along with the amplitude based seismic attributes were formulated to VDL. The methodology is illustrated by performing a case study from the Hendijan oilfield, northwestern Persian Gulf. The results of this study show that integration of petrographic, well logs and seismic attributes is an instrumental way for understanding the spatial distribution of main reservoir pore types

Petrophysical data prediction from seismic attributes using committee fuzzy inference system

This study presents an intelligent model based on fuzzy systems for making aquantitative formulation between seismic attributes and petrophysical data. The proposed methodology comprises two major steps. Firstly, the petrophysical data, including water saturation (Sw) and porosity, are predicted from seismic attributes using various Fuzzy Inference Systems (FIS), including Sugeno (SFIS), Mamdani (MFIS) and Larsen (LFIS). Secondly, a Committee Fuzzy Inference System (CFIS) is constructed using a hybrid Genetic Algorithms-Pattern Search (GA-PS) technique. The inputs of the CFIS model are the output averages of theFIS petrophysical data. The methodology is illustrated using 3D seismic and petrophysical data of 11 wells of an Iranian offshore oil field in the Persian Gulf. The performance of the CFIS model is compared with a Probabilistic Neural Network (PNN). The results show that the CFIS method performed better than neural network, the best individual fuzzy model and a simple averaging method

An integrated approach to study the impact of fractures distribution on the Ilam-Sarvak carbonate reservoirs: a case study from the Strait of Hormuz, the Persian Gulf

Most of the Iranian hydrocarbon reservoirs in the Persian Gulf Basin and the Zagros Fold-Thrust Belt are composed of fractured carbonate rocks. In this regard, determining the spatial distribution of fractures has been a challenging issue. In this study, an integrated approach was applied for understanding the impact of fractures spatial distribution on the Ilam-Sarvak (Cenomanian to Santonian) carbonate reservoir rocks. For this purpose, seismic interpretation techniques along with geomechanical and geostatistical modeling were employed to characterize fractures at different scales. Initially, the relationship between fractures origin and the normal faults was investigated by conducting an in-situ stress analysis. Afterwards, the velocity deviation log (VDL) and fracture intensity log (FIL) were derived as fracture attributes from the interpretation of Formation Micro Imager (FMI) and conventional well logs. A 3D model of VDL and FIL was achieved by using a sequential Gaussian simulation (SGS) method. In order to achieve a more realistic and accurate model of the factures distribution, variations of the shear-wave velocity and geomechanical properties (Young's modulus and Poisson's ratio) were estimated by applying the advanced seismic interpretation techniques in the normal faults domain. The results show that the intensity of fractures increases once they are introduced to the normal faults, especially in the central part of the study area around well#2. Such a fractured zone is verified by fracture density log derived from FMI logs of the mentioned well. Obviously, there is a close-knit relationship between the fracture system and the normal faults. Eventually, secondary porosity caused by features was determined though identification of Hydraulic Flow Units (HFUs). Based on the porosity and permeability data, seven HFUs were determined for the Ilam-Sarvak reservoirs. The very high values of Log FZI indicate the possible presence of fractures. Overall, the fractures contributed to enhance the secondary porosity of the reservoir rocks though increasing matrix permeability. To sum up, the fractures system plays a critical role in controlling reservoir properties especially in the hanging-wall of normal faults where the majority of the macro and micro fractures are distributed

Integrated approach for zonation of a mid-Cenomanian carbonate reservoir in a sequence stratigraphic framework

The mid-Cenomanian Mishrif Formation (Fm.) is considered as one of the most important rudist-bearing reservoir horizons in the Sirri Oil Fields of the Persian Gulf. Due to the general heterogeneity of carbonate reservoirs, the use of an integrated approach is helpful for investigating porosity and permeability distribution along with recognizing controlling pore system factors in the reservoir. Thus, for the reservoir characterization of the Mishrif Fm., an integrated approach including facies analysis, diagenetic history and sequence stratigraphic analysis is considered. Detailed petrographic studies showed a total of eight microfacies and seven facies belts, related to inner ramp to the basin of a homoclinal carbonate ramp. Humid climatic condition and tectonic activity, associated with eustatic sea-level fluctuations during the mid-Cretaceous, led to meteoric diagenesis of the Mishrif carbonates during subaerial exposures (mid-Cenomanian and Cenomanian-Turonian disconformities). General diagenetic overprints and modifications include micritization, cementation, dissolution, compaction, dolomitization, pyritization and fracturing. Considering this reservoir in the sequence stratigraphic framework reveals that the reservoir zones development is basically related to the Cenomanian–Turonian sequence boundary, recognized in the three studied wells, and also to the mid-Cenomanian boundary, identified only in one well. In addition, pore system properties were inspected by differentiation of Hydraulic Flow Units (HFUs) within the reservoir. The identified flow units, based on their capability for fluid flow, can be classified into four main rock types with very high- (HFUD), high- (HFUC), medium- (HFUB) and low-quality (HFUA). Accordingly, this study shows that the main part of the Mishrif Reservoir is affected by diagenetic processes related to subaerial exposures, resulting in zones with higher storage capacity and fluid flow rates. So, the study of depositional and diagenetic characteristics of the Mishrif carbonates in the sequence stratigraphy framework is essential to unravel the reservoir heterogeneity, and to describe the reservoir zones and their distribution in the field and regional scale. In addition, observed changes in the thickness of hydrocarbon column are attributed to the different location of the studied wells on the anticline structures, which show a tilted oil-water contact with a slope to the North