Low-salinity-based enhanced oil recovery literature review and associated screening criteria

A thorough literature review is conducted that pertains to low-salinity-based enhanced oil recovery(EOR).This is meant to be a comprehensive review of all the refereed published papers,conference papers,master’s theses and other reports in this area.The review is specifically focused on establishing various relations/characteristics or"screening criteria"such as:(1)classification/grouping of clays that have shown or are amenable to low-salinity benefits;(2)clay types vs.range of residual oil saturations;(3)API gravity and down hole oil viscosity range that is amenable for low salinity;(4)salinity range for EOR benefits;(5)pore sizes,porosity,absolute permeability and wettability range for low-salinity EOR;(6)continuous low-salinity injection vs.slug-wise injection;(7)grouping of possible low-salinity mechanisms;(8)contradictions or similarities between laboratory experiments and field evidence;and(9)compositional variations in tested low-salinity waters.A proposed screening criterion for low-salinity waterflooding is introduced.It can be concluded that either one or more of these mechanisms,or a combination thereof,may be the case-specific mechanism,i.e.,depending on the particular oil–brine–rock(OBR)system rather than something that is"universal"or universally applicable.Therefore,every OBR system that is unique or specific ought to be individually investigated to determine the benefits(if any)of low-salinity water injection;however,the proposed screening criteria may help in narrowing down some of the dominant responsible mechanisms.Although this review primarily focuses on sandstones,given the prominence of carbonates containing^60%of the world’s oil reserves,a summary of possible mechanisms and screening criteria,pertaining to low-salinity waterflooding,for carbonates is also included.Finally,the enhancement of polymer flooding by using low-salinity water as a makeup water to further decrease the residual oil saturation is also discussed.

Evaluation of formation damages during filter cake deposition and removal process:The effect of primary damage on secondary damage

The properties of oil and gas formation could be significantly damaged during drilling and completion operations as a result of mud invasion,fluid incompatibility and interaction with rock minerals.This paper presents a systematic method for evaluating formation damage during filter cake deposition(primary damage)and removal process(secondary damage).The role of primary damage in the evolution of secondary damage was also investigated.The interaction of the filter cake solvent(chelating agent solution)with the rock samples was implemented through core flooding experiment.Nuclear Magnetic Resonance(NMR)was used to evaluate the properties of the rock sample,pre and post filter cake deposition and removal processes.The results show that secondary damaged is a strong function of the location and the intensity of the primary damage.The rock type and its pore structure also play important roles in both primary and secondary damage.The extent of secondary damage depends on the amount of barium sulphate deposited during primary damage.The chelating agent used to dissolve the barites in sandstones,deposited the barite in the small pores while it enlarges the bigger pores.In contrast,the chelating agent in the carbonate samples had multiple barite deposition points.

Statistical prediction of waterflooding performance by K-means clustering and empirical modeling

Statistical prediction is often required in reservoir simulation to quantify production uncertainty or assess potential risks.Most existing uncertainty quantification procedures aim to decompose the input random field to independent random variables,and may suffer from the curse of dimensionality if the correlation scale is small compared to the domain size.In this work,we develop and test a new approach,K-means clustering assisted empirical modeling,for efficiently estimating waterflooding performance for multiple geological realizations.This method performs single-phase flow simulations in a large number of realizations,and uses K-means clustering to select only a few representatives,on which the two-phase flow simulations are implemented.The empirical models are then adopted to describe the relation between the single-phase solutions and the two-phase solutions using these representatives.Finally,the two-phase solutions in all realizations can be predicted using the empirical models readily.The method is applied to both 2D and 3D synthetic models and is shown to perform well in the P10,P50 and P90 of production rates,as well as the probability distributions as illustrated by cumulative density functions.It is able to capture the ensemble statistics of the Monte Carlo simulation results with a large number of realizations,and the computational cost is significantly reduced.