Fracture Reactivation Modeling in a Depleted Reservoir

Injection-induced fracture reactivation during hydraulic fracturing processes in shale gas development as well as coal bed methane(CBM)and other unconventional oil and gas recovery is widely investigated because of potential permeability enhancement impacts.Less attention is paid to induced fracture reactivation during oil and gas production and its impacts on reservoir permeability,despite its relatively common occurrence.During production,a reservoir tends to shrink as effective stresses increase,and the deviatoric effective stresses also increase.These changes in the principal effective stresses may cause Coulomb fracture slip in existing natural fractures,depending on their strength,orientation,and initial stress conditions.In this work,an extended finite element model with contact constraints is used to investigate different fracture slip scenarios induced by general reservoir pressure depletion.The numerical experiments assess the effect of Young’s modulus,the crack orientation,and the frictional coefficient of the crack surface on the distribution of stress and displacement after some reservoir depletion.Results show that the crack orientation significantly affects the state of stress and displacement,particularly in the vicinity of the crack.Slip can only occur in permitted directions,as determined by the magnitudes of the principal stresses and the frictional coefficient.Lastly,a larger frictional coefficient(i.e.,a rougher natural fracture surface)makes the crack less prone to shear slip.

Evolving simple-to-use method to determine watereoil relative permeability in petroleum reservoirs

In the current research,a new approach constructed based on artificial intelligence concept is introduced to determine water/oil relative permeability at various conditions.To attain an effective tool,various artificial intelligence approaches such as artificial neural network(ANN),hybrid of genetic algorithm and particle swarm optimization(HGAPSO)are examined.Intrinsic potential of feed-forward artificial neural network(ANN)optimized by different optimization algorithms are composed to estimate water/oil relative permeability.The optimization methods such as genetic algorithm,particle swarm optimization and hybrid approach of them are implemented to obtain optimal connection weights involved in the developed smart technique.The constructed intelligent models are evaluated by utilizing extensive experimental data reported in open literature.Results obtained from the proposed intelligent tools were compared with the corresponding experimental relative permeability data.The average absolute deviation between the model predictions and the relevant experimental data was found to be less than 0.1%for hybrid genetic algorithm and particle swarm optimization technique.It is expected that implication of HGAPSO-ANN in relative permeability of water/oil estimation leads to more reliable water/oil relative permeability predictions,resulting in design of more comprehensive simulation and further plans for reservoir production and management.

Cross-flow analysis of injection wells in a multilayered reservoir

During fluid injection into a multilayered reservoir,a different pressure gradient is generated across the face of each permeable layer.This pressure gradient generates driving forces in the wellbore during well shut-in that causes the injected fluid moves from higher pressure layers to lower pressure layers,a phenomenon known as interwell cross-flow.Cross-flow behavior depends on the initial pressure in the permeable layers and may be referred to as natural cross-flow(identical or natural initial pressures)and forced cross-flow(different initial pressures because of exploitation).Cross-flow may induce sand production and liquefaction in the higher pressure layers as well as formation damage,filter cake build-up and permeability reduction in the lower pressure layers.Thus,understanding cross-flow during well shut-in is important from a production and reservoir engineering perspective,particularly in unconsolidated or poorly consolidated sandstone reservoirs.Natural and forced cross-flow is modeled for some injection wells in an oil reservoir located at North Sea.The solution uses a transient implicit finite difference approach for multiple sand layers with different permeabilities separated by impermeable shale layers.Natural and forced cross-flow rates for each reservoir layer during shut-in are calculated and compared with different production logging tool(PLT)measurements.It appears that forced cross-flow is usually more prolonged and subject to a higher flow rate when compared with natural cross-flow,and is thus worthy of more detailed analysis.

稠油井解堵新技术——一种新型的脉冲修井技术

一种新型的高幅、低频压力脉冲修井技术对稠油出砂冷采、由封堵的炮眼、不移动的细粉砂以及胶质沥青质所造成的油井严重封堵情况有特效。炮眼受堵塞、细粉砂堆积对井眼附近流线的限制、胶质沥青质在孔喉处的沉积以及井眼附近地层砂的重新压实都能造成油井快速减产。对稠油井来说 ,单靠化学处理法 ,其作用甚微 ,但发现对井眼附近进行大量的物理干扰 ,对老井复产有一定效果。研制一套井下设备 ,用该设备对射孔面进行 9～ 12小时的压力脉冲 ,并且边进行高振幅干扰 ,边向井内注入流体。该作用降低了机械表皮效应 ,即通过井眼周围地层砂的结构重组和液化 ,物理清除堵塞物。采出液化层 ,随即恢复采油。该技术在大多数情况下能使老井复活 ,特别对那些出砂不出油的情况 ,经压力脉冲后 ,可使这些低产井转成高产井。注入化学处理剂的同时通过压力脉冲较好地分散流入井中的处理液前缘 。