Production logging is used to diagnose well production problems by evaluating the flow profile, entries of unwanted fluids and downhole flow regimes. Evaluating wells production performance can be easily induce from production logs through interpretation of production log data to provide velocity profile and contribution of each zone on total production. Production logging results supply information for reservoir modeling, provide data to optimize the productivity of existing wells and plan drilling and completion strategies for future wells. Production logging was carried out in a production oil well from Mishrif formation of West Qurna field, with the objective to determine the flow profile and fluid contributions from the perforations af

Production logging is used to diagnose well production problems by evaluating the flow profile, entries of unwanted fluids and downhole flow regimes. Evaluating wells production performance can be easily induce from production logs through interpretation of production log data to provide velocity profile and contribution of each zone on total production. Production logging results supply information for reservoir modeling, provide data to optimize the productivity of existing wells and plan drilling and completion strategies for future wells. Production logging was carried out in a production oil well from Mishrif formation of West Qurna field, with the objective to determine the flow profile and fluid contributions from the perforations af

Production logging is used to diagnose well production problems by evaluating the flow profile, entries of unwanted fluids and downhole flow regimes. Evaluating wells production performance can be easily induce from production logs through interpretation of production log data to provide velocity profile and contribution of each zone on total production. Production logging results supply information for reservoir modeling, provide data to optimize the productivity of existing wells and plan drilling and completion strategies for future wells. Production logging was carried out in a production oil well from Mishrif formation of West Qurna field, with the objective to determine the flow profile and fluid contributions from the perforations

     This study is achieved in the local area of the Eridu oil field, where the Mishrif Formation is considered the main productive reservoir. The Mishrif Formation was deposited during the Cretaceous period in the secondary sedimentary cycle (Cenomanian-Early Turonian as a part of the Wasia Group, a carbonate succession widespread throughout the Arabian Plate.

     The Mishrif Formation already have been evaluated in terms of depositional environments and their diagenetic processes. Here, it will test the previous conclusions with petrophysical properties delineated by using well logging. The results show there is a fully matching with two reservoir units (MA and MB). Dissolution and primary porosity are responsible for f

Ahdeb oil field is located in the central block of Mesopotamia plain in Iraq. It has three domes AD-1,   AD-2, and AD-4.The current study represents characterization of carbonate Mishrif reservoir (Cenomanian-Early Turonian) in three wells (AD-A,AD-B,AD-C) at southern dome of Ahdeb oil field. Petrophysical properties were calculated using available well logs data such as neutron, density, sonic, gamma ray, resistivity and self-potential logs. These logs are digitized and then environmental corrections and interpretations were carried out using Techlog software. Petrophysical parameters such as shale volume, porosity, water saturation, hydrocarbon saturation, bulk water volume, etc. were determined and interpreted and illustrate

Wellbore instability and sand production onset modeling are very affected by Sonic Shear Wave Time (SSW). In any field, SSW is not available for all wells due to the high cost of measuring. Many authors developed empirical correlations using information from selected worldwide fields for SSW prediction. Recently, researchers have used different Artificial Intelligence methods for estimating SSW. Three existing empirical correlations of Carroll, Freund, and Brocher are used to estimate SSW in this paper, while a fourth new empirical correlation is established. For comparing with the empirical correlation results, another study's Artificial Neural Network (ANN) was used. The same data t

This research was aimed to determine the petrophysical properties (porosity, permeability and fluid saturation) of a reservoir. Petrophysical properties of the Shuiaba Formation at Y field are determined from the interpretation of open hole log data of six wells. Depending on these properties, it is possible to divide the Shuiaba Formation which has thickness of a proximately 180-195m, into three lithological units: A is upper unit (thickness about 8 to 15 m) involving of moderately dolomitized limestones; B is a middle unit (thickness about 52 to 56 m) which is composed of dolomitic limestone, and C is lower unit ( >110 m thick) which consists of shale-rich and dolomitic limestones. The results showed that the average formation water