Gharib Moustafa Hamada

Functional Network softsensor for formation porosity and water saturation in oil wells

Formation porosity and water saturation play important role in evaluating potential oil reservoirs and for drafting development plans for new oil fields. This paper presents a novel method for estimating these two important parameters directly from conventional well measurements. The recently proposed Functional Networks technique is applied for rapid and accurate prediction of these parameters, using six and five basic well log measurements as data for estimating porosity and water saturation respectively. Functional network is a generalization of the conventional Feed Forward Neural Networks, which overcome many of the drawbacks of the conventional neural network techniques. The proposed functional network was trained using data gathered from two wells in the Middle East region. Results obtained from this case study using the proposed intelligent technique have shown to be fast and accurate.

Better Porosity Estimate of Gas Sandstone Reservoirs Using Density and NMR Logging Data

روخصلا عبشتو ةيماسمو ةذافن ةسارد يف ةلمعتسملا ةيلاحلا ايجولونكتلا نع يسيطانغملا نينرلا ايجولونكت زيمتت تانازخلل ةيرخصلا تانوكملاب رثأتت لا اھنأب ، صاوخلا سايقل ةقد رثكأ ةديدج ةليسو يسيطانغملا نينرلا مدقت كلاذل تيزلل ةلماحلا روخصلل ةيقيزيفورتبلا . ي ثحبلا اذھ نينرلا نم لكل جودزملا مادختسلاا ىلع دمتعت ةثيدح ةينقت مدق تازاغلا ريثأت كلاذكو تاقبطلا يف ةبرستملا ةلفطلا لئاوس ريثأت ىشاحتن ىتح كلاذو ةفاثكلا تلايجستو يسيطانغملا ةدرفنم تلايجستلا كلت ىلع و ، عت تاذو ةيندتم ةيماسمب ةفصتملاو ةيزاغلا نماكملا ميوقت تايلمع بلطتت تاديق تاينقتلا كلت نم تامولعملا جاتنتسا ةيفيكو اھعم لماعتلا يف تاربخو ةثيدح تاينقت مادختسا ةيرخص . اذھ يف جودزملا مادختسلاا ةينقت قيبطت مت ثحبلا ) رمد ( ةيماسمو ةذافن تاذ ةدقعملا تاقبطلا ميوقت يف هحاجن تبثاو زاغلل ةلماحلا و نيتيندتم .

Identification of Hydrocarbon Movability and Type from Resistivity Logs

Abstract Resistivity data is normally used to evaluate water saturation using porosity values from porosity logs (neutron and density). Determination of initial oil (gas) in place is based on hydrocarbon saturation, porosity, and thickness obtained from openhole logging data for a given drainage area. It is important not only to determine the initial hydrocarbon in place, but also to define the existing hydrocarbon movability, indicating the recoverable hydrocarbon and its type. This article presents a new approach of the hydrocarbon movability factor (HCM). This factor is derived from shallow and deep resistivity data. The relation F = a/φ m is correct in water-saturated zones; in partially saturated zones this relation becomes invalid, and it will give the apparent formation resistivity factor (Fa). Based on this idea, the HCM has been derived, with scale going from 0.0 to 1.0. It is found that for HCM less than 0.75, hydrocarbon is movable, and for HCM greater than 0.75, the hydrocarbon is immovable. When HCM is less than 0.25, the movable hydrocarbon is gas, and for HCM greater than 0.25 and less than 0.75, the movable hydrocarbon is oil. Field examples have been analyzed with the HCM factor. These field examples demonstrated the contribution of HCM in the field of hydrocarbon type identification and determination of hydrocarbon movability from openhole resistivity logging.