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

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.

Characterization of Mishrif Formation Reservoir in Amara Oil Field, Southeast Iraq, Using Geophysical Well-logging

Reservoir characterization requires reliable knowledge of certain fundamental properties of the reservoir. These properties can be defined or at least inferred by log measurements, including porosity, resistivity, volume of shale, lithology, water saturation, and permeability of oil or gas. The current research is an estimate of the reservoir characteristics of Mishrif Formation in Amara Oil Field, particularly well AM-1, in south eastern Iraq. Mishrif Formation (Cenomanin-Early Touronin) is considered as the prime reservoir in Amara Oil Field. The Formation is divided into three reservoir units (MA, MB, MC). The unit MB is divided into two secondary units (MB1, MB2) while the unit MC is also divided into two secondary units (MC1, MC2). Using Geoframe software, the available well log images (sonic, density, neutron, gamma ray, spontaneous potential, and resistivity logs) were digitized and updated. Petrophysical properties, such as porosity, saturation of water, saturation of hydrocarbon, etc. were calculated and explained. The total porosity was measured using the density and neutron log, and then corrected to measure the effective porosity by the volume content of clay. Neutron -density cross-plot showed that Mishrif Formation lithology consists predominantly of limestone. The reservoir water resistivity (Rw) values of the Formation were calculated using Pickett-Plot method.

Evaluation of Mishrif Reservoir in Abu Amood Oil Field, 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.

Bubble structure in superheavy nuclei around neutron and proton shell closure

We have performed a systematic study for the nuclear structure of superheavy nuclei with a special emphasis on the nuclei with possible central depletion of proton and neutron density in the mass region [Formula: see text] using the Relativistic Hartree–Bogoliubov (RHB) framework. It has been observed that in the case of neutron density distribution, the occurrence of central depletion is related to the occupancy of 4s orbital and it is found to decrease with increasing occupancy of the 4s orbital. On the other hand, in the case of proton density distribution, the central density depletion is mainly due to the lowering of weakly bound p-orbital states close to the continuum as it is energetically favored to lower the Coulomb repulsion in the case of superheavy nuclei. Also, occupation probability of the lower angular momentum states (p-orbitals) lying near the Fermi level is strongly suppressed due to the weak centrifugal barrier and strong Coulomb repulsion in comparison to large angular momentum states (contributing to surface region mainly), resulting in central density depletion. Among the considered cases in the present work, the maximum depletion is observed for [Formula: see text] and for [Formula: see text]Og under spherically symmetric and axially deformed cases, respectively.

Identification of Patches of Bitumen in a Carbonate Reservoir: A Case Study

Carbonate reservoir X has varying levels of maturity in terms of development. The South/West is highly matured; development activities have recently kicked-off in the Crestal part while the areas towards the Far North is not fully developed and posed the largest uncertainty in terms of reservoir quality, fluid contacts, oil saturation, well injectivity/ productivity, area potential and reserves due to poor well control. In reservoir X with segmented development areas, patches of bitumen have been found in the Far North. The extent of this Bitumen was unknown. In order to expand the CO2 development concept to achieve production target from the Far Northern flank, an understanding and mitigation of the area uncertainties is crucial. Reservoir bitumen is a highly viscous, asphaltene rich hydrocarbon that affects reservoir performance. Distinguishing between producible oil and reservoir bitumen is critical for recoverable hydrocarbon volume calculations and production planning, yet the lack of resistivity and density contrast between the reservoir bitumen and light oil makes it difficult, if not impossible, to make such differentiation using only conventional logs such as neutron, density, and resistivity. This paper highlights the utilization and integration of advanced logging tools such as nuclear magnetic resonance and dielectric, in conjunction with routine logs, pressure points, RCI samples, vertical interference test and core data to differentiate between reservoir bitumen and other hydrocarbon types in the pore space. The major findings from the studies shows bitumen doesn't form as a single layer but occurs in different subzones as patches which is a challenge for static modelling. When high molecular weight hydrocarbons are distributed in the pore space and coexist with light and producible hydrocarbons, reservoir bitumen is likely to block pore throats. The Bitumen present in this reservoir have a log response similar to conventional pore fluids. The outcome of this study has helped in refining the bitumen boundary, optimize well placement, resolved the uncertainties associated with deeper fluid contacts and provided realistic estimate of STOIIP.

Study of the matter density distributions of halo nuclei 6He and 16C using the binary cluster model

The harmonic oscillator (HO) and Gaussian (GS) wave functions within the binary cluster model (BCM) have been employ to investigate the ground state neutron, proton and matter densities as well as the elastic form factors of two-neutron 6He and 16C halo nuclei. The long tail is a property that is clearly revealed in the density of the neutrons since it is found in halo orbits. The existence of a long tail in the neutron density distributions of 6He and 16C indicating that these nuclei have a neutron halo structure. Moreover, the matter rms radii and the reaction cross section (σr) of these nuclei have been calculated using the Glauber model.

Hydrocarbon Reservoir Characterization of ‘Khume’ Field, Offshore Niger Delta, Nigeria

The integrative approach of well log correlation and seismic interpretation was adopted in this study to adequately characterize and evaluate the hydrocarbon potentials of Khume field, offshore Niger Delta, Nigeria. 3-D seismic data and well logs data from ten (10) wells were utilized to delineate the geometry of the reservoirs in Khume field, and as well as to estimate the hydrocarbon reserves. Three hydrocarbon-bearing reservoirs of interest (D-04, D-06, and E-09A) were delineated using an array of gamma-ray logs, resistivity log, and neutron/density log suites. Stratigraphic interpretation of the lithologies in Khume field showed considerable uniform gross thickness across all three sand bodies. Results of petrophysical evaluations conducted on the three reservoirs correlated across the field showed that; shale volume ranged from 7-14%, total and effective porosity ranged from 19-26% and 17-23% respectively, NTG from 42 to 100%, water saturation from 40%-100% and permeability from 1265-2102 mD. Seismic interpretation established the presence of both synthetic and antithetic faults. A total of six synthetic and four antithetic faults were interpreted from the study area. Horizons interpretation was done both in the strike and dip directions. Time and depth structure maps revealed reservoir closures to be anticlinal and fault supported in the field. Hydrocarbon volumes were calculated using the deterministic (map-based) approach. Stock tank oil initially in place (STOIIP) for the proven oil column estimated for the D-04 reservoir was 11.13 MMSTB, 0.54 MMSTB for D-06, and 2.16 MMSTB for E-09A reservoir. For the possible oil reserves, a STOIIP value of 7.28 MMSTB was estimated for D-06 and 6.30 MMSTB for E-09A reservoir, while a hydrocarbon initially in place (HIIP) of 4.13 MMSTB of oil equivalents was derived for the undefined fluid (oil/gas) in D-06 reservoir. A proven gas reserve of 1.07 MMSCF was derived for the D-06 reservoir. This study demonstrated the effectiveness of 3-D seismic and well logs data in delineating reservoir structural architecture and in estimating hydrocarbon volumes

Discriminating Shale Layers by Pseudo CGR Logs Created Using Artificial Intelligence

The discrimination of shale vs. non-shale layers significantly influences the quality of reservoir geological model. In this study, a novel approach was implemented to enhance the model by creating Pseudo Corrected Gamma Ray (CGR) logs using Artificial Intelligence methods to identify the thin shale beds within the reservoir. The lithology of the carbonate reservoir understudy is mostly composed of dolomite and limestone rock with minor amounts of anhydrite and thin shale layers. The identification of shale layers is challenging because of the nature of such reservoirs. The high organic content of the shales and the presence of dolomites, particularly the floatstones and rudstones, can adversely affect the log quality and interpretation and may result in inaccurate log correlations, overestimating/ underestimating Original Oil In Place (OOIP) and reservoir net pays. In such cases, Corrected Gamma Ray (CGR) curves are typically used to identify shale layers. The CGR curve response is due to the combination of thorium and potassium that is associated with the clay content. The difference between the total GR and the CGR is essentially the amount of uranium-associated organic matter. Because of the very limited number of CGR logs in this reservoir, Artificial Intelligence (AI) approach was used to identify shale volume across the entire reservoir. Synthetic CGR curves were generated for the wells lacking CGR logs using AI methods. Resistivity, Density, Neutron and total GR logs were used as inputs while CGR was set as the target. Five wells that have CGR logs were used to train the model. The created pseudo logs were then used to identify shale layers and could also be used to correct effective porosity logs. After statistical analysis of the data, two different Artificial Intelligence Techniques were tested to predict CGR logs; Adaptive Neuro-Fuzzy Inference System (ANFIS) and Artificial Neural Network (ANN). A Sugeno-type FIS structure using subtractive clustering demonstrated the best prediction with correlation coefficient of 0.96 and mean absolute percentage error (MAPE) of 20%. The resulting synthetic CGR curves helped identify shale layers that do not extend over the entire reservoir area and ultimately correct the effective porosity logs in the reservoir model. Porosity was primarily obtained from the neutron-density logs which results in very high porosity measurements across the shale layers. This study shows a new workflow to predict shale layers in Carbonate reservoirs. The created pseudo CGR logs would help predict shale and is an added-value data that could be incorporated into the Earth model.

Low Resistivity Reservoir Pay Evaluation, New Opportunity for Further Development, Case Study On Gumai Formation Of B Field, Jambi Sub Basin, South Sumatera Basin

The understanding of low resistivity reservoir zone is one of the most challenging cases for further development in order to optimize the remaining oil and gas field productions. In the Intra-Gumai Formation “B” Field where marine clastic reservoirs are deposited, a low resistivity reservoir is being developed as a new perforation and workover target. This study discusses how to identify the cause of low resistivity case and evaluate the proper petrophysical parameters to unlock the potential reservoir pay zones. The data set consists of petrographic, X-Ray Diffraction (XRD), Cation Exchange Capacity (CEC), routine core, Drill Stem Test ((DST) and wireline logs data. Petrographic, XRD, CEC and routine analysis were performed to recognize the low resistivity causes characterized by the presence of framework grain (quartz, K-feldspar and glaucony, calcite and kaolinite) observed in intergranular pore and also quartz overgrowth developed prior to kaolinite precipitation. Petrophysical analysis defines the reservoir property parameters by comparing some equations also validated with routine core and DST result. Based on the quantitative analysis carried out, namely the evaluation of the distribution of shale volume, calculation of porosity, and determination of water saturation, it is recommended to use the Stieber method for the distribution of shale volume in the reservoir and its properties, the neutron density porosity method to calculate porosity model, and the Waxman Smits method to determine the final fluid saturation model. Finally, by using the hydrocarbon saturation results in the current study, this interval was improved as pay zone. This method will be applied to other wells and other structures that have a similar depositional environment to increase hydrocarbon reserves in the same field.