scholarly journals A New Method To Estimate Resistivity Distribution Of Shaly Sand Reservoirs Using New Seismic Attributes

2021 ◽  
Vol 71 ◽  
pp. 149-157
Author(s):  
Nur Farhana Salleh ◽  
◽  
Maman Hermana ◽  
Deva Prasad Ghosh
Keyword(s):  
Water Saturation ◽  
Seismic Attributes ◽  
Effective Porosity ◽  
Seismic Attenuation ◽  
Hydrocarbon Exploration ◽  
Fluid Distribution ◽  
Similar Response ◽  
Petrophysical Properties ◽  
Resistivity Model ◽  
Shaly Sand

A subsurface resistivity model is important in hydrocarbon exploration primarily in the controlled-source electromagnetic (CSEM) method. CSEM forward modelling workflow uses resistivity model as the main input in feasibility studies and inversion process. The task of building a shaly sand resistivity model becomes more complex than clean sand due to the presence of a shale matrix. In this paper, a new approach is introduced to model a robust resistivity property of shaly sand reservoirs. A volume of seismic data and three wells located in the K-field of offshore Sarawak is provided for this study. Two new seismic attributes derived from seismic attenuation property called SQp and SQs are used as main inputs to predict the volume of shale, effective porosity, and water saturation before resistivity estimation. SQp attribute has a similar response to gamma-ray indicating the lithological variation and SQs attribute is identical to resistivity as an indicator to reservoir fluids. The petrophysical predictions are performed by solving the mathematical step-wise regression between the seismic multi-attributes and predicted petrophysical properties at the well locations. Subsequently, resistivity values are estimated using the Poupon-Leveaux (Indonesia) equation, an improvised model from Archie’s to derive the mathematical relationship of shaly sand’s resistivity to the volume and resistivity of clay matrix in shaly sand reservoirs. The resistivity modeled from the predicted petrophysical properties distributed consistently with sand distribution delineated from SQp attribute mainly in southeast, northeast, and west regions. The gas distribution of the net sand modeled by 5% and 90% of gas saturation scenarios also changed correspondingly to SQs attribute anomaly indicating the consistent fluid distribution between the modeled resistivity and SQs attribute.

ENHANCED ASSESSMENT OF FLUID SATURATION IN THE WOLFCAMP FORMATION OF THE PERMIAN BASIN

2021 ◽  
Author(s):  
Sabyasachi Dash ◽  
◽  
Zoya Heidari ◽  
Keyword(s):  
Water Saturation ◽  
Geometric Model ◽  
Rock Physics ◽  
Model Parameters ◽  
Permian Basin ◽  
Resistivity Measurements ◽  
Clay Concentration ◽  
Resistivity Model ◽  
Shaly Sand ◽  
Hydrocarbon Reserves

Conventional resistivity models often overestimate water saturation in organic-rich mudrocks and require extensive calibration efforts. Conventional resistivity-porosity-saturation models assume brine in the formation as the only conductive component contributing to resistivity measurements. Enhanced resistivity models for shaly-sand analysis include clay concentration and clay-bound water as contributors to electrical conductivity. These shaly-sand models, however, consider the existing clay in the rock as dispersed, laminated, or structural, which does not reliably describe the distribution of clay network in organic-rich mudrocks. They also do not incorporate other conductive minerals and organic matter, which can significantly impact the resistivity measurements and lead to uncertainty in water saturation assessment. We recently introduced a method that quantitatively assimilates the type and spatial distribution of all conductive components to improve reserves evaluation in organic-rich mudrocks using electrical resistivity measurements. This paper aims to verify the reliability of the introduced method for the assessment of water/hydrocarbon saturation in the Wolfcamp formation of the Permian Basin. Our recently introduced resistivity model uses pore combination modeling to incorporate conductive (clay, pyrite, kerogen, brine) and non-conductive (grains, hydrocarbon) components in estimating effective resistivity. The inputs to the model are volumetric concentrations of minerals, the conductivity of rock components, and porosity obtained from laboratory measurements or interpretation of well logs. Geometric model parameters are also critical inputs to the model. To simultaneously estimate the geometric model parameters and water saturation, we develop two inversion algorithms (a) to estimate the geometric model parameters as inputs to the new resistivity model and (b) to estimate the water saturation. Rock type, pore structure, and spatial distribution of rock components affect geometric model parameters. Therefore, dividing the formation into reliable petrophysical zones is an essential step in this method. The geometric model parameters are determined for each rock type by minimizing the difference between the measured resistivity and the resistivity, estimated from Pore Combination Modeling. We applied the new rock physics model to two wells drilled in the Permian Basin. The depth interval of interest was located in the Wolfcamp formation. The rock-class-based inversion showed variation in geometric model parameters, which improved the assessment of water saturation. Results demonstrated that the new method improved water saturation estimates by 32.1% and 36.2% compared to Waxman-Smits and Archie's models, respectively, in the Wolfcamp formation. The most considerable improvement was observed in the Middle and Lower Wolfcamp formation, where the average clay concentration was relatively higher than the other zones. Results demonstrated that the proposed method was shown to improve the estimates of hydrocarbon reserves in the Permian Basin by 33%. The hydrocarbon reserves were underestimated by an average of 70000 bbl/acre when water saturation was quantified using Archie's model in the Permian Basin. It should be highlighted that the new method did not require any calibration effort to obtain model parameters for estimating water saturation. This method minimizes the need for extensive calibration efforts for the assessment of hydrocarbon/water saturation in organic-rich mudrocks. By minimizing the need for extensive calibration work, we can reduce the number of core samples acquired. This is the unique contribution of this rock-physics-based workflow.

scholarly journals Petrophysical Properties and Digenetic Evolution of Shuaiba Formation in Nasiriyah Oil Field, Southern Iraq

2021 ◽  
pp. 4810-4818
Author(s):  
Marwah H. Khudhair
Keyword(s):  
Gamma Ray ◽  
Water Saturation ◽  
Middle Part ◽  
Effective Porosity ◽  
Oil Field ◽  
Neutron Density ◽  
Petrophysical Properties ◽  
Secondary Porosity ◽  
Primary Porosity ◽  
Gamma Ray Log

     Shuaiba Formation is a carbonate succession deposited within Aptian Sequences. This research deals with the petrophysical and reservoir characterizations characteristics of the interval of interest in five wells of the Nasiriyah oil field. The petrophysical properties were determined by using different types of well logs, such as electric logs (LLS, LLD, MFSL), porosity logs (neutron, density, sonic), as well as gamma ray log. The studied sequence was mostly affected by dolomitization, which changed the lithology of the formation to dolostone and enhanced the secondary porosity that replaced the primary porosity. Depending on gamma ray log response and the shale volume, the formation is classified into three zones. These zones are A, B, and C, each can be split into three rock intervals in respect to the bulk porosity measurements. The resulted porosity intervals are: (I) High to medium effective porosity, (II) High to medium inactive porosity, and (III) Low or non-porosity intervals. In relevance to porosity, resistivity, and water saturation points of view, there are two main reservoir horizon intervals within Shuaiba Formation. Both horizons appear in the middle part of the formation, being located within the wells Ns-1, 2, and 3. These intervals are attributed to high to medium effective porosity, low shale content, and high values of the deep resistivity logs. The second horizon appears clearly in Ns-2 well only.

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 Petrophysical Properties and Well Log Interpretations of Tertiary Reservoir in Khabaz Oil Field / Northern Iraq

2020 ◽  
Vol 26 (6) ◽  
pp. 18-34
Author(s):  
Yousif Najeeb Abdul-majeed ◽  
Ahmad Abdullah Ramadhan ◽  
Ahmed Jubiar Mahmood
Keyword(s):  
Water Saturation ◽  
Total Porosity ◽  
Effective Porosity ◽  
Oil Field ◽  
Neutron Density ◽  
Petrophysical Properties ◽  
Secondary Porosity ◽  
Northern Iraq ◽  
Sonic Log ◽  
Oil Concentration

The aim of this study is interpretation well logs to determine Petrophysical properties of tertiary reservoir in Khabaz oil field using IP software (V.3.5). The study consisted of seven wells which distributed in Khabaz oilfield. Tertiary reservoir composed from mainly several reservoir units. These units are : Jeribe, Unit (A), Unit (A'), Unit (B), Unit (BE), Unit (E),the Unit (B) considers best reservoir unit because it has good Petrophysical properties (low water saturation and high porous media ) with high existence of hydrocarbon in this unit. Several well logging tools such as Neutron, Density, and Sonic log were used to identify total porosity, secondary porosity, and effective porosity in tertiary reservoir. For Lithological identification for tertiary reservoir units using (NPHI-RHOB) cross plot composed of dolomitic-limestone and mineralogical identification using (M/N) cross plot consist of calcite and dolomite. Shale content was estimated less than (8%) for all wells in Khabaz field. CPI results were applied for all wells in Khabaz field which be clarified movable oil concentration in specific units are: Unit (B), Unit (A') , small interval of Jeribe formation , and upper part of Unit (EB).

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 A Comparison of Mishrif Formation Characteristics in Kumait and Dujaila Oil Fields, Southern Iraq, Using Seismic Inversion Method and Petrophysical Properties Analysis

2020 ◽  
pp. 3294-3307
Author(s):  
Ahmed S. Al-Banna ◽  
Nowfal A. Nassir ◽  
Ghazi H. Al-Sharaa
Keyword(s):  
Acoustic Impedance ◽  
Water Saturation ◽  
Water Reservoir ◽  
Seismic Inversion ◽  
Effective Porosity ◽  
Oil Fields ◽  
Inversion Method ◽  
Oil Reservoir ◽  
Petrophysical Properties ◽  
Southern Iraq

A comparison was conducted between two wells, Kt-1and Kt-2, in Kumait and two wells, Du-1and Du-2, in Dujaila oil fields that belong to Mishrif formation, southern Iraq.  Seismic inversion method was employed to detect oil and water reservoirs. The comparison included the behavior of acoustic impedance (AI) of fluids and the lithology with related petrophysical properties. The values of water saturation, Shale volume (Vsh), and effective porosity were compared between the AI,  two fluid reservoirs. It was found that the AI value for the oil reservoir unit is relatively low to medium, whereas it was relatively medium for the water reservoir. Effective porosity value showed, in general, an increase in the oil reservoir and a slightly decrease in the water reservoir. The Vsh and water saturation (Sw) values of the oil reservoir unit were in general lower than those in the water reservoir, which indicates the presence of hydrocarbons accumulation. The lithology and porosity are the main factors affecting the acoustic impedance values. Despite the small difference in density between oil and water, these two fluids still show perceptible variation in their properties.  

Coblending of seismic attributes for interpretation of channel geometries in Rence Field of Niger Delta, Nigeria

2015 ◽  
Vol 3 (4) ◽  
pp. T183-T195 ◽  
Author(s):  
Augustine Ifeanyi Chinwuko ◽  
Ajana Godwin Onwuemesi ◽  
Emmanuel Kenechukwu Anakwuba ◽  
Clement Udenna Onyekwelu ◽  
Harold Chinedu Okeke ◽  
...  
Keyword(s):  
Niger Delta ◽  
Water Saturation ◽  
Seismic Attributes ◽  
Hydrocarbon Exploration ◽  
Seismic Facies ◽  
Petrophysical Analysis ◽  
Net To Gross ◽  
Seismic Facies Analysis ◽  
Well Data ◽  
Channel Deposits

Coblending of seismic attributes is used in the interpretation of channel geometries in the Rence Field of Niger Delta, Nigeria. We aimed at seismically defining the geometries of hydrocarbon reservoirs with particular emphasis on channels in the shallow marine (offshore) Niger Delta. The coblending application enhanced the ease of detection and the continuity of the channels, leaving the channel environs unchanged. The result of the seismic facies analysis revealed that the Rence Field can be distinguished into two seismic facies, namely, layered complexes and chaotic complexes. The result of well to seismic ties revealed high- and low-amplitude reflection events for sand and shale units, respectively. Seismic structural interpretation of the Rence Field revealed 4 major regional faults and 12 minor faults. Seven of the faults were antithetic, and the rest were synthetic faults. One mega-channel feature that trends east–west was identified in the attribute maps generated. It was characterized by sinuosity of 1.3, with a length of 22,500 m, and a distance of 17,500 m. The average depth of the channel was approximately 170 m with amplitude of 1670 m and the wavelength as high as 7640 m. A depositional model generated from the attribute maps indicated a prograding fluvial environment of deposition. The attribute map also determined that there was shifting in the location of barrier bars within the area. This shifting could be attributed to the growth fault mechanism. At the stoss side of the sinusoidal channel, there were prominent sand point bar sequences. The petrophysical analysis of the well data revealed 90% net-to-gross, 28% porosity, 27% volume of shale, and 24% water saturation indicating that the reservoir was of pay quality. Based on the petrophysical analysis, results, and identification of channel deposits, the study area proved highly promising for hydrocarbon exploration.

Formation-Resistivity Theory: How Archie Equations, Shaly-Reservoir Models, Conductive Rock-Matrix Model, and Dual-Triple-Porosity Models Are Related

2014 ◽  
Vol 17 (02) ◽  
pp. 141-151 ◽  
Author(s):  
Philip C. Iheanacho
Keyword(s):  
Water Saturation ◽  
Control Volume ◽  
Single Parameter ◽  
Rock Matrix ◽  
Heterogeneous Reservoirs ◽  
Resistivity Logs ◽  
Resistivity Model ◽  
Formation Resistivity ◽  
Shaly Sand ◽  
New Equation

Summary The estimation of hydrocarbon pore volume (HCPV) from resistivity logs can be quite troublesome in some complex heterogeneous reservoirs. Most water-saturation/formation-resistivity models that work well for some reservoirs give unreliable results for others. No single model works for all types of reservoir scenarios. This paper presents the theory of formation resistivity in porous media. The paper develops the theory from the parallel-resistivity model and then extends it for the series-resistivity model. When applied for clean sand, the theory derives Archie equations from the first principle. The derivations show that both porosity exponent and saturation exponent are of the same origin and should have the same name. A better name for both parameters should be the tortuosity exponent of a component with respect to its fraction in a control volume. It is also advantageous to treat as a single parameter rather than two separate parameters. In addition, this theory derives new shaly-sand models for estimating HCPV. These new shaly-sand models can be used for different types of shale distribution by adjusting the value of a single parameter in the models. The formation-resistivity theory is also used to derive formation-resistivity models for conductive rock-matrix reservoirs and dual-triple-porosity reservoirs. A new equation for calculating the composite-porosity exponent is also developed. Field data are used to validate this work. The theory, when applied for each scenario, derives formation-resistivity models for estimating the reliable HCPV of different reservoir scenarios and types. Moreover, the strength of this theory is its ability to generate models that closely resemble models that have proved to work well for the reservoir cases for which they were developed. Although this work does not test the theory for the cases of tight-sand, shale-gas, and other unconventional reservoirs because of the unavailability of such data, the author is of the opinion that the theory can easily be extended for such reservoirs if the necessary data are available.

scholarly journals Comparative Characterization of Petrophysical and Mechanical Properties of Siliciclastic Reservoir Rocks within a compressional structure of the Teapot Dome Oilfield, Wyoming, USA

2020 ◽  
Vol 5 (2) ◽  
pp. 1-12
Author(s):  
Rotimi Oluwatosin John ◽  
Ogunkunle Fred Temitope ◽  
Onuh Charles Yunusa ◽  
Ameloko Aduojo Anthony ◽  
Enaworu Efeoghene ◽  
...  
Keyword(s):  
Mechanical Properties ◽  
Seismic Data ◽  
Water Saturation ◽  
Accurate Determination ◽  
Hydrocarbon Exploration ◽  
Rock Properties ◽  
Petrophysical Properties ◽  
Fluid Movement ◽  
Property Variation ◽  
Reservoir Rocks

AbstractWorking with subsurface engineering problems in Hydrocarbon exploration as regard rock elastic and petrophysical properties necessitate accurate determination of in-situ physical properties. Several techniques have been adopted in correlating log-derived parameters with petrophysical and mechanical behavior of the rocks. However, limited field applications show there are no particular parameters and correlations that are generally acceptable due to the regional variation in geologic features (i.e., degree of mineralogy, texture, etc.). This study presents a method that assesses the disparity in petrophysical properties of oil and gas reservoir rocks in relation to their elastic/mechanical properties from 10 well-logs and 3D migrated seismic data. Two distinct facies were identified from seismic data after computing attributes. Reflection strength attribute of 2.5 and above depicts Bright spots within the central section of the field as clearly revealed by Variance and Chaos attributes. Formation properties calculated from logs were conformally gridded in consonance with the reflection patterns from the seismic data. The average Brittleness index (BI) of 0.52 corresponds to Young’s modulus (E) values of between 8 and 16 for the dense portion. This portion is the laminated, reasonably parallel, and undeformed part, flanked by the unlaminated and chaotic zones. From cross plots, the distinguished lower portion on the plot is the segment with higher sand of more than 50 %. This segment corresponds to the reservoir in this study as confirmed from the genetic algorithm neural network Acoustic impedance inversion process result. Similarly, the plot of Compressional velocity (Vp) and Poisson’s ratio (ν), reveals the laminated sand value of not less than 0.32 of ν, and Vp of about 4.2 km/s. The average porosity is about 16 %, average water saturation is about 16 %, and average permeability is approximately 25 md. Rock properties trends in a unique pattern and showing fluctuation that confirms the compressive nature of the structure with corresponding petrophysical properties. This trend is sustained in permeability computed and suggests a significant gravity-assisted compaction trend and fluid movement. It gives a reasonable idea of the fluid movement interplay and mechanical property variation within the sequence and across the dome. This part probably has been subjected to fair compressional deformational forces initiated from outside the survey.

scholarly journals Petrophysical interpretation in shaly sand formation of a gas field in Tanzania

2019 ◽  
Vol 10 (3) ◽  
pp. 1201-1213
Author(s):  
Oras Joseph Mkinga ◽  
Erik Skogen ◽  
Jon Kleppe
Keyword(s):  
Volume Fraction ◽  
Water Saturation ◽  
Total Porosity ◽  
Published Data ◽  
Petrophysical Properties ◽  
Production Forecast ◽  
Sand Fraction ◽  
Gas Field ◽  
Shale Volume ◽  
Shaly Sand

AbstractAn onshore gas field (hereafter called the R field—real name not revealed) is in the southeast coast of Tanzania which includes a Tertiary aged shaly sand formation (sand–shale sequences). The formation was penetrated by an exploration well R–X wherein no core was acquired, and there is no layer-wise published data of the petrophysical properties of the R field in the existing literature, which are essential to reserves estimation and production forecast. In this paper, the layer-wise interpretation of petrophysical properties was undertaken by using wireline logs to obtain parameters to build a reservoir simulation model. The properties extracted include shale volume, total and effective porosities, sand fractions and sand porosity, and water saturation. Shale volume was computed using Clavier equation from gamma ray. Density method was used to calculate total and effective porosities. Thomas–Stieber method was used to determine sand porosity and sand fraction, and water saturation was computed using Poupon–Leveaux model. The statistics of the parameters extracted are presented, where shale volume obtained that varies with zones is between 6 and 54% volume fraction, with both shale laminations and dispersed shale were identified. Total porosity obtained is in a range from 12 to 22%. Sand porosity varies between 15 and 25%, and sand fraction varies between 33 and 93% height fraction. Average water saturation obtained is between 32 and 49% volume fraction.

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