A method for stimulation of hydrocarbon production via imbibition by utilization of surfactants. The method includes use of fuzzy logic and neural network architecture constructs to determine surfactant use.

Imbibition well stimulation via neural network design

AI applied to evaluate waterflood response, gas behind pipe, and imbibition stimulation treatments

High pour point oil reservoir contains various typical properties; such as a kind of high freezing point, high paraffin content and high cloud point temperature reservoir, while the temperature is regarded as high sensitive parameter for oil reservoirs. The current research aim is to develop and assess the effect by cold water flooding, the structure and properties model was built with the combination method of reservoir geological modeling and simulation. Various degrees of cold damage have deep relation with paraffin deposition and reservoir channel plug due to decline of temperature below the cloud point temperature. Precipitated paraffin has changed the rheological properties of crude oil, which can increase filtration resistance and reducing the oil displacement efficiency. Furthermore, model simulation analysis results compared under two different conditions cold and hot water flooding and predicted the inter well temperature field distribution belongs to reservoir through the model numerical simulation. Present study depicts that the integrated method base on log, geological data and experiment can predict and analysis the temperature variation efficiently, while thermal displacement method has efficiently improved the high pour-point oil reservoir development effect, increasing oil mobility and enhancing oil recovery.

Study on the Temperature Distribution of High Pour Point Oil by Integrated Method Based on Well Log, Geological Data and Experiment

Disclaimer " This report was prepared as an account of work sponsored by an agency of the United States Government. Neither the United States Government nor any agency thereof, nor any of their employees, makes any warranty, express or implied, or assumes any legal liability or responsibility for the accuracy, completeness, or usefulness of any information, apparatus, product, or process disclosed, or represents that its use would not infringe privately owned rights. Reference herein to any specific commercial product, process, or service by trade name, trademark, manufacture, or otherwise does not necessarily constitute or imply its endorsement, recommendation, or favoring by the United states Government or any agency thereof. The views and opinions of authors expressed herein do not necessarily state or reflect those of the United States Government or any agency thereof. "

http://www.netl.doe.gov/KMD/cds/disk44/C-Chemical%20Flooding/83226%20FinalRpt.pdf

Chemical Stimulation of Oil Wells Producing from Carbonate Reservoirs

Well logs and cores are used to define formation thickness, porosity, and water saturation. These data are required to design well completions and to prepare workover and reservoir management plans. The presence of shale (clay) in the pay zone complicates log interpretation. This paper presents a methodology utilizing a neural network to reconcile the differences between density log effective porosity and plug core total porosity values in a shaly, laminated Cretaceous sandstone. Core plug measurements are typically taken in the better pay intervals and generally do not include the shale laminations evident in core photographs. Log measurements do include the heterogeneity that is evident in core photographs, but the log measurements represent an average of a 6-to-36-in. section that does not reflect the small scale variability. A multivariable correlating technique was used to associate gamma ray, density, and shallow and deep resistivity logs with core plug porosity measurements. Core water saturation values were used to tune a shaly sand water saturation model. The S W model was used to choose between plug core porosity, density log porosity, or neural network porosity as the preferred measurement to use with induction log resistivity to estimate water saturation. The porosity and water saturation values were then used to construct bulk volume oil and bulk volume water logs that were combined to identify productive zones. A case history format is used to explain the approach developed to correlate the four dependent variables measured by the logs with the core porosity and water saturation measurements. The subject field is an 80-well Gallup pool located on the southwest flank of the San Juan Basin of northwest New Mexico. The high clay content of the Muddy Formation in the Powder River Basin is known for contributing to errors in water saturation estimates. If modern logs capable of resolving thin beds are not available, this methodology can be applied to the Muddy, the Gallup and other Cretaceous reservoirs in the Rockies that contain thin shale laminations.

J. Roe

Papers

Integrating Core Porosity and Sw Measurements with Log Values