Water flooding effect evaluation is considered as the basic work to formulate comprehensive adjustment measures and improve the effectiveness of oilfield development. However, natural edge-bottom water energy is seldom considered in the conventional evaluation method. So, it cannot reflect the comprehensive effect of both natural edge-bottom water and injected water. Principal component analysis is a kind of multivariate statistical analysis method, which has been widely used in social science and other fields. Based on this method, the water flooding effect of 5 edge-bottom water reservoirs is comprehensively evaluated. First, 11 indicators are selected from four aspects, including natural edge-bottom water energy, production change, water injection development and utilization, energy maintenance and deficit compensation. Then, the selection of principal components is optimized. Based on the consideration of keeping as much information as possible to get more convincing results, three principal components are obtained. Finally, take five oilfields as examples to realize comprehensive evaluation. Results indicate that the natural energy of B oilfield is quite sufficient and water injection is timely in the later stage of development. So the water flooding effect is the best among five oilfields and the comprehensive principal component value is 1.434. That of A and C oilfields are 0.527 and 1.021, respectively, ranking 3 and 2. Although D oilfield has quite sufficient natural energy, water injection is not timely. So the water flooding effect is poor and the comprehensive principal component value is 0.259. That of E oilfield is − 3.241, indicating that it has the worst water flooding effect. The ranking results of five oilfields are consistent based on principal component analysis and Tong's chart, which are both B, C, A, D and E oilfield, verifying this method’s feasibility and practicability. Additionally, compared with the single index, it can reflect the comprehensive water flooding effect of both natural edge-bottom water and injected water. Specific oilfield cases are evaluated by the proposed method, which help for better understanding its application potential for evaluating the water flooding effect of natural edge-bottom water reservoirs.

注水效果评价是制定综合调整措施，提高油田开发效益的基础性工作。然而，在常规评估方法中很少考虑自然的底部边缘水能。因此，它不能反映出自然界底水和注入水的综合效果。主成分分析是一种多元统计分析方法，已广泛应用于社会科学等领域。在此方法的基础上，对5个边底水库的注水效果进行了综合评价。首先，从四个方面来选择11个指标：自然边缘水能，生产变化，注水开发和利用，能源维护和赤字补偿。然后，优化了主成分的选择。基于保留尽可能多的信息以获得更令人信服的结果的考虑，获得了三个主要成分。最后，以五个油田为例，进行综合评价。结果表明，在开发后期，Ｂ油田的自然能充足，注水及时。因此，在五个油田中注水效果最好，综合主成分值为1.434。A和C油田分别为0.527和1.021，排在第3和第2位。尽管D油田具有足够的自然能，但注水并不及时。因此注水效果差，综合主成分值为0.259。E油田的为-3.241，表明它的水驱效果最差。根据B，C，A，D和E油田的主成分分析和Tong图表，对五个油田的排名结果是一致的，证明了该方法的可行性和实用性。另外，与单一指标相比，它可以反映出自然界底水和注入水的综合驱水效果。通过提出的方法对特定的油田案例进行评估，有助于更好地了解其在评估天然边底水库水驱效果方面的应用潜力。另外，与单一指标相比，它可以反映出自然界底水和注入水的综合驱水效果。通过提出的方法对特定的油田案例进行评估，有助于更好地了解其在评估天然边底水库水驱效果方面的应用潜力。此外，与单一指标相比，它可以反映出自然界底水和注入水的综合驱水效果。通过提出的方法对特定的油田案例进行评估，有助于更好地了解其在评估天然边底水库水驱效果方面的应用潜力。